diff --git a/.gitignore b/.gitignore
index 9ed8e86..2ad9ccc 100644
--- a/.gitignore
+++ b/.gitignore
@@ -20,6 +20,7 @@ notebook/static/lab/*bundle.js
notebooks/itslive/data/*.nc
notebooks/iceflow/data
notebooks/*/Outputs
+notebooks/SMAP/data
.python-version
node_modules
*.py[co]
diff --git a/notebooks/SMAP/01_download_smap_data.ipynb b/notebooks/SMAP/01_download_smap_data.ipynb
index 59c0039..a2a6ad6 100644
--- a/notebooks/SMAP/01_download_smap_data.ipynb
+++ b/notebooks/SMAP/01_download_smap_data.ipynb
@@ -21,7 +21,7 @@
"source": [
"## **1. Tutorial Introduction/Overview**\n",
"\n",
- "We will use the `earthaccess` library to authenticate with our Earthdata Login credentials and to search for and bulk download SMAP data. For this tutorial we wil use SPL3SMP version 008 as an example, but the same method can be applied to any other SMAP data sets archived at NSIDC. \n"
+ "We will use the `earthaccess` library to authenticate with our Earthdata Login credentials and to search for and bulk download SMAP data. For this tutorial we wil use SPL3SMP version 009 as an example, but the same method can be applied to any other SMAP data sets archived at NSIDC. \n"
]
},
{
@@ -31,7 +31,7 @@
"source": [
"### **Credits**\n",
"\n",
- "This tutorial is based on the notebooks originally provided to NSIDC by Adam Purdy. Jennifer Roebuck of NSIDC updated the tutorials to include the latest version of SMAP data and use `earthaccess` for authentication, seatching for and downloading the data in order to incorporate it into the NSIDC-Data-Tutorials repo. \n",
+ "This tutorial is based on the notebooks originally provided to NSIDC by Adam Purdy. Jennifer Roebuck of NSIDC updated the tutorials to include the latest version of SMAP data and use `earthaccess` for authentication, searching for and downloading the data in order to incorporate it into the NSIDC-Data-Tutorials repo. Andy Barrett refactored the notebook to use `pathlib.Path` and updated the version of the data set used.\n",
"\n",
"For questions regarding the notebook, or to report problems, please create a new issue in the [NSIDC-Data-Tutorials repo](https://github.com/nsidc/NSIDC-Data-Tutorials/issues)."
]
@@ -85,7 +85,7 @@
"metadata": {},
"source": [
"### **Import libraries**\n",
- "We need just two libraries, `os` for creating the directory to store the downloaded data in and `earthaccess` to authenticate, search for and download the data. "
+ "We need two libraries for this tutorial: `pathlib` for creating the directory to store the downloaded data; and `earthaccess` to authenticate, search for and download the data. "
]
},
{
@@ -95,9 +95,7 @@
"metadata": {},
"outputs": [],
"source": [
- "#Import libraries \n",
- "\n",
- "import os # needed to create the directory to store the downloaded data\n",
+ "from pathlib import Path # used for creating paths and listing directory contents\n",
"import earthaccess # used for authentication and searching for downloading the data"
]
},
@@ -131,14 +129,16 @@
"tags": []
},
"source": [
- "### **Search for SPL3SMP data using spatial and temporal filters**\n",
- "We will use the `search_data` method from the `earthaccess` library and the following variabes to search for granules within the SPL3SMP data set:\n",
+ "### **Search for SPL3SMP data using a temporal filter**\n",
+ "We will use the `search_data` method from the `earthaccess` library to search for granules in the SPL3SMP data set for March 2017.\n",
+ "\n",
+ "We use the following search parameters: \n",
"* `short_name` - this is the data set ID e.g. SPL3SMP. It can be found in the data set title on the data set landing page.\n",
"* `version` - data set version number, also included in the data set title.\n",
- "* `cloud_hosted` - NSIDC is in the process of migrating data sets to the cloud. The data set we are interested is currently still archived on-premises so we will set this to False.\n",
+ "* `cloud_hosted` - SMAP data are available both from NASA Earthdata Cloud on AWS and from the severs on-premises at NSIDC_DAAC. We will access the cloud-hosted version.\n",
"* `temporal` - set a temporal filter by specifying a start and end date in the format YYYY-MM-DD. In this tutorial we will look for data for the month of March 2017.\n",
"\n",
- "It will output the number of granules that meet the search criteria."
+ "You can find the number of results returned by getting the number of elements in `results` using the `len` function."
]
},
{
@@ -148,14 +148,13 @@
"metadata": {},
"outputs": [],
"source": [
- "#Search for SPL3SMP files \n",
- "\n",
"results = earthaccess.search_data(\n",
" short_name = 'SPL3SMP',\n",
- " version = '008',\n",
+ " version = '009',\n",
" cloud_hosted = False,\n",
" temporal = ('2017-03-01','2017-03-31')\n",
- ")"
+ ")\n",
+ "print(f\"Found: {len(results)}\")"
]
},
{
@@ -174,11 +173,8 @@
"metadata": {},
"outputs": [],
"source": [
- "this_dir = os.getcwd()\n",
- "DATA_DIR = os.path.join(this_dir, 'data/L3_SM_P')\n",
- "\n",
- "if not os.path.exists(DATA_DIR):\n",
- " os.makedirs(DATA_DIR)\n"
+ "DOWNLOAD_PATH = Path.cwd() / \"data\" / \"L3_SM_P\"\n",
+ "DOWNLOAD_PATH.mkdir(parents=True, exist_ok=True) # creates parents if they don't exist and fails silently if path exists"
]
},
{
@@ -196,7 +192,7 @@
"metadata": {},
"outputs": [],
"source": [
- "smap_files = earthaccess.download(results,DATA_DIR)"
+ "smap_files = earthaccess.download(results,DOWNLOAD_PATH)"
]
},
{
@@ -236,7 +232,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.9.15"
+ "version": "3.10.14"
}
},
"nbformat": 4,
diff --git a/notebooks/SMAP/environment/environment.yml b/notebooks/SMAP/environment/environment.yml
index 6688db2..a2e44b0 100644
--- a/notebooks/SMAP/environment/environment.yml
+++ b/notebooks/SMAP/environment/environment.yml
@@ -9,9 +9,17 @@ dependencies:
- xarray
- rioxarray
- h5netcdf
+- dask
- matplotlib
- cartopy
- affine
+- numpy<2.1
+
+#- vaex
+#- jupyter-offlinenotebook
+#- sidecar
+#- geoviews
+
- pipreqsnb
- conda-lock>=1.2.1
- mamba>=1.0
diff --git a/notebooks/SMAP/smap_as_datatree.ipynb b/notebooks/SMAP/smap_as_datatree.ipynb
new file mode 100644
index 0000000..6a734d7
--- /dev/null
+++ b/notebooks/SMAP/smap_as_datatree.ipynb
@@ -0,0 +1,51708 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "e55a759f-e465-41d7-9674-71b73e4f8412",
+ "metadata": {},
+ "source": [
+ "
\n",
+ "\n",
+ "\n",
+ "# 2.0 Read and Plot SMAP data using `xarray.DataTree`\n",
+ "\n",
+ "
\n",
+ "---"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "3e5b1d2e-04df-40f1-a9f8-f4fb48e32656",
+ "metadata": {},
+ "source": [
+ "## 1. Overview \n",
+ "In this tutorial, we will read the SMAP data we downloaded in 1.0 Download SMAP data notebook, read the data into an `xarray.DataTree`, create a map of soil moisture and plot a time-series soil moisture for a location on Earth.\n",
+ "\n",
+ "`xarray.DataTree` was created to work with hierachical datasets. Hierachical datasets are those datasets that use tree-like, nested, directory structures to group and store complex data. The SMAP Level-3 is a relatively simple hierachical data structure, with only two groups; one group for data from AM satellite overpasses and one group for data from PM satellite overpasses. To make working with this data easy, we also add meaningful names for the dimensions of the data and geospatial coordinates. "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "6060c844-782d-4510-b643-0b78273f069d",
+ "metadata": {},
+ "source": [
+ "### **Credits**\n",
+ "\n",
+ "This tutorial is based on the notebooks originally provided to NSIDC by Adam Purdy. Jennifer Roebuck of NSIDC updated the tutorials to include the latest version of SMAP data and use earthaccess for authentication, seatching for and downloading the data in order to incorporate it into the NSIDC-Data-Tutorials repo. \n",
+ "\n",
+ "For questions regarding the notebook, or to report problems, please create a new issue in the [NSIDC-Data-Tutorials repo](https://github.com/nsidc/NSIDC-Data-Tutorials/issues)."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "56a6afe4-c559-412e-86bc-3f9530dc3d36",
+ "metadata": {},
+ "source": [
+ "### **Learning Goals**\n",
+ "\n",
+ "1. Read in SMAP data and navigate the metadata\n",
+ "2. Create a map with SMAP data\n",
+ "3. Plot a time-series at a location on Earth. "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "c275f5c7-fa1b-4423-9967-03f46344ade0",
+ "metadata": {},
+ "source": [
+ "### **Prerequisites**\n",
+ "\n",
+ "1. The nsidc-tutorials environment is set up and activated. This [README](https://github.com/nsidc/NSIDC-Data-Tutorials/blob/main/README.md) has setup instructions.\n",
+ "2. SMAP data that were downloaded in the previous notebook tutorial 1.0 Download SMAP data. \n",
+ "3. The EASE-Grid 2.0 longitude and latitude data sets. The binary format of these files have been provided within this repo for use in this tutorial, but please note they are also available in NetCDF format from the NSIDC website at this [page](https://nsidc.org/data/NSIDC-0772/versions/1). \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a0b23d36-8b5a-4bcf-b8a7-5dbc235853bf",
+ "metadata": {},
+ "source": [
+ "### **Time requirement**\n",
+ "\n",
+ "Allow 15 to 20 minutes to complete this tutorial."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e7eb2e5f-39e1-4bad-8fc2-65984e8527ce",
+ "metadata": {},
+ "source": [
+ "## 2. Tutorial steps"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "3b14efdc-c8d6-4831-93a3-0ab7d8f9a491",
+ "metadata": {},
+ "source": [
+ "### Import libraries\n",
+ "\n",
+ "As with all Python code, we need to import some libraries to read the data, add coordinates and plot the data."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "3cf68262-b0d5-4601-bc52-7aa3c68670aa",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# For opening the data\n",
+ "from pathlib import Path\n",
+ "import xarray as xr\n",
+ "import datetime\n",
+ "\n",
+ "# For adding coordinates\n",
+ "import numpy as np\n",
+ "from affine import Affine\n",
+ "from pyproj import CRS\n",
+ "\n",
+ "# For plotting\n",
+ "import matplotlib.pyplot as plt\n",
+ "import cartopy.crs as ccrs\n",
+ "\n",
+ "DATAPATH = Path(\"data/L3_SM_P\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "672a11e2-7fef-4ac6-9809-c0ed276bf3ee",
+ "metadata": {},
+ "source": [
+ "### Get a list of HDF5 files in the data directory"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "4f43e868-aeb1-499d-8db9-54eec5a6791d",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "filelist = sorted(list(DATAPATH.glob(\"*.h5\")))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "403ba053-0e4e-412d-9513-3dccf4941ec3",
+ "metadata": {},
+ "source": [
+ "### Load a data file into an `xarray.DataTree` object\n",
+ "\n",
+ "`xarray.DataTree` objects allow us to work with hierachical data structures and file formats such as HDF5, Zarr and NetCDF4 with groups. The SMAP level 3 files are hierachical data structures.\n",
+ "\n",
+ "We use `xr.open_datatree` to open a SMAP HDF5 file. We add the `phony_dims=\"sort\"` because data variables in the SMAP files do not have any assigned dimension scales. `xarray` names dimensions `phony_dim0`, `phony_dim1`, etc."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "f3f729bc-41df-4420-9e2e-b7f8467364d5",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
The SMAP observatory houses an L-band radiometer that operates at 1.414 GHz and an L-band radar that operates at 1.225 GHz. The instruments share a rotating reflector antenna with a 6 meter aperture that scans over a 1000 km swath. The bus is a 3 axis stabilized spacecraft that provides momentum compensation for the rotating antenna.
Percentage of EASE2 grid cells that lack soil moisture retrieval values relative to the total number of grid cells where soil moisture retrieval was attempted.
Daily global composite of up-to 15 half-orbit L2_SM_P soil moisture estimates based on radiometer brightness temperature measurements acquired by the SMAP radiometer during descending half-orbits at approximately 6 AM local solar time.
characterSet :
utf8
creationDate :
2024-05-02
credit :
The software that generates the Level 3 SM_P product and the data system that automates its production were designed and implemented at the Jet Propulsion Laboratory, California Institute of Technology in Pasadena, California.
fileName :
SMAP_L3_SM_P_20170301_R19240_001.h5
format :
HDF5
formatVersion :
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language :
eng
maintenanceAndUpdateFrequency :
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maintenanceDate :
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originatorOrganizationName :
Jet Propulsion Laboratory
otherCitationDetails :
The Calibration and Validation Version 2 Release of the SMAP Level 3 Daily Global Composite Passive Soil Moisture Science Processing Software.
purpose :
The SMAP L3_SM_P effort provides soil moistures based on radiometer data on a 36 km grid.
Soil moisture is retrieved over land targets on the descending (AM) SMAP half-orbits when the SMAP spacecraft is travelling from North to South, while the SMAP instruments are operating in the nominal mode. The L3_SM_P product represents soil moisture retrieved over the entre UTC day. Retrievals are performed but flagged as questionable over urban areas, mountainous areas with high elevation variability, and areas with high ( > 5 kg/m**2) vegetation water content; for retrievals using the high-resolution radar, cells in the nadir region are also flagged. Retrievals are inhibited for permanent snow/ice, frozen ground, and excessive static or transient open water in the cell, and for excessive RFI in the sensor data.
The Equal-Area Scalable Earth Grid (EASE-Grid 2.0) is used for gridding satellite data sets. The EASE-Grid 2.0 is defined on the WGS84 ellipsoid to allow users to import data into standard GIS software formats such as GeoTIFF without reprojection.
Precomputed longitude at each EASEGrid cell on 36-km grid on Global Cylindrical Projection
fileName :
EZ2Lon_M36_002.float32
version :
002
\n",
+ "
<xarray.DatasetView> Size: 0B\n",
+ "Dimensions: ()\n",
+ "Data variables:\n",
+ " *empty*\n",
+ "Attributes:\n",
+ " creationDate: 2024-05-02\n",
+ " description: A configuration file that specifies the complete set of el...\n",
+ " fileName: SMAP_L3_SM_P_SPS_InputConfig_L2_SM_P.xml\n",
+ " version: R19240
InputConfiguration
creationDate :
2024-05-02
description :
A configuration file that specifies the complete set of elements within the input Level 2 SM_P Product that the Radiometer Level 3_SM_P Science Processing Software (SPS) needs in order to function.
Passive soil moisture estimates onto a 36-km global Earth-fixed grid, based on radiometer measurements acquired when the SMAP spacecraft is travelling from North to South at approximately 6:00 AM local time.
<xarray.DatasetView> Size: 0B\n",
+ "Dimensions: ()\n",
+ "Data variables:\n",
+ " *empty*\n",
+ "Attributes:\n",
+ " creationDate: 2024-05-02\n",
+ " description: A configuration file that specifies the source of the valu...\n",
+ " fileName: SMAP_L3_SM_P_SPS_MetConfig_L2_SM_P.xml\n",
+ " version: R19240
MetadataConfiguration
creationDate :
2024-05-02
description :
A configuration file that specifies the source of the values for each of the data elements that comprise the metadata in the output Radiometer Level 3_SM_P product.
fileName :
SMAP_L3_SM_P_SPS_MetConfig_L2_SM_P.xml
version :
R19240
\n",
+ "
<xarray.DatasetView> Size: 0B\n",
+ "Dimensions: ()\n",
+ "Data variables:\n",
+ " *empty*\n",
+ "Attributes:\n",
+ " creationDate: 2024-05-02\n",
+ " description: A configuration file that lists the entire content of the ...\n",
+ " fileName: SMAP_L3_SM_P_SPS_OutputConfig_L3_SM_P.xml\n",
+ " version: R19240
OutputConfiguration
creationDate :
2024-05-02
description :
A configuration file that lists the entire content of the output Radiometer Level 3_SM_P_ product.
A configuration file generated automatically within the SMAP data system that specifies all of the conditions required for each individual run of the Radiometer Level 3 SM P Science Processing Software (SPS).
Algorithm Theoretical Basis Document: SMAP L2 and L3 Radiometer Soil Moisture (Passive) Data Products: L2_SM_P & L3_SM_P
ATBDVersion :
Version 1.1
SWVersionID :
026
algorithmDate :
2021-08-17
algorithmDescription :
Level 3 soil moisture product is formed by mosaicking Level 2 soil moisture granule data acquired over one day.
algorithmTitle :
Soil Moisture Active Passive (SMAP) Radiometer processing algorithm
algorithmVersionID :
023
documentDate :
2012-10-26
documentVersion :
Preliminary
documentation :
Algorithm Theoretical Basis Document: SMAP L2 and L3 Radiometer Soil Moisture (Passive) Data Products: L2_SM_P & L3_SM_P
epochJulianDate :
2451545.0
epochUTCDateTime :
2000-01-01T11:58:55.816Z
identifier :
L3_SM_P_SPS
parameterVersionID :
015
processDescription :
Soil moisture retrieved using default retrieval algorithm from brightness temperatures acquired by the SMAP radiometer during the spacecraft descending pass. Level 2 granule data are then mosaicked on a daily basis to form the Level 3 product.
processor :
Soil Moisture Active Passive Mission (SMAP) Science Data System (SDS) Operations Facility
Product Specification Document for the SMAP Level 3 Passive Soil Moisture Product (L3_SM_P)
\n",
+ "
<xarray.DatasetView> Size: 0B\n",
+ "Dimensions: ()\n",
+ "Data variables:\n",
+ " *empty*\n",
+ "Attributes:\n",
+ " abstract: An ASCII product that contains statistical information on ...\n",
+ " creationDate: 2024-05-02\n",
+ " fileName: SMAP_L3_SM_P_20170301_R19240_001.qa
QADatasetIdentification
abstract :
An ASCII product that contains statistical information on data product results. These statistics enable data producers and users to assess the quality of the data in the data product granule.
Daily global composite of up-to 30 half-orbit L2_SM_P soil moisture estimates based on radiometer brightness temperature measurements acquired by the SMAP radiometer during ascending and descending half-orbits at approximately 6 PM and 6 AM local solar time.
characterSet :
utf8
credit :
The software that generates the Level 3 Soil Moisture Passive product and the data system that automates its production were designed and implemented \n",
+ " at the Jet Propulsion Laboratory, California Institute of Technology in Pasadena, California.
identifier_product_DOI :
doi:10.5067/4XXOGX0OOW1S
language :
eng
longName :
SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture
mission :
SMAP
otherCitationDetails :
The Calibration and Validation Version 2 Release of the SMAP Level 3 Daily Global Composite Passive Soil Moisture Science Processing Software.
pointOfContact :
National Snow and Ice Data Center
purpose :
The SMAP L3_SM_P algorithm provides daily global composite of soil moistures based on radiometer data on a 36 km grid.
resourceProviderOrganizationName :
National Aeronautics and Space Administration (NASA)
revisionDate :
2023-08-31
shortName :
SPL3SMP
spatialRepresentationType :
grid
status :
onGoing
topicCategory :
geoscientificInformation
iso_19139_dataset_xml :
<?xml version="1.0" encoding="UTF-8" standalone="no" ?>\n",
+ "<gmd:DS_Series xmlns:gmd="http://www.isotc211.org/2005/gmd" xmlns="http://www.isotc211.org/2005/gmi" xmlns:eos="http://earthdata.nasa.gov/schema/eos" xmlns:gco="http://www.isotc211.org/2005/gco" xmlns:gmi="http://www.isotc211.org/2005/gmi" xmlns:gml="http://www.opengis.net/gml/3.2" xmlns:gmx="http://www.isotc211.org/2005/gmx" xmlns:gsr="http://www.isotc211.org/2005/gsr" xmlns:gss="http://www.isotc211.org/2005/gss" xmlns:gts="http://www.isotc211.org/2005/gts" xmlns:srv="http://www.isotc211.org/2005/srv" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.isotc211.org/2005/gmi http://cdn.earthdata.nasa.gov/iso/schema/1.0/ISO19115-2_EOS.xsd">\n",
+ "\n",
+ " <gmd:composedOf xlink:type="simple">\n",
+ " <gmd:DS_DataSet>\n",
+ " <gmd:has xlink:type="simple">\n",
+ " <gmi:MI_Metadata>\n",
+ " <gmd:fileIdentifier>\n",
+ " <gmx:FileName>SMAP_L3_SM_P_20170301_R19240_001.h5</gmx:FileName>\n",
+ " </gmd:fileIdentifier>\n",
+ " <gmd:language>\n",
+ " <gco:CharacterString>eng</gco:CharacterString>\n",
+ " </gmd:language>\n",
+ " <gmd:characterSet>\n",
+ " <gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode" codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>\n",
+ " </gmd:characterSet>\n",
+ " <gmd:hierarchyLevel>\n",
+ " <gmd:MD_ScopeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ScopeCode" codeListValue="dataset">dataset</gmd:MD_ScopeCode>\n",
+ " </gmd:hierarchyLevel>\n",
+ " <gmd:contact xlink:type="simple">\n",
+ " <gmd:CI_ResponsibleParty>\n",
+ " <gmd:organisationName>\n",
+ " <gco:CharacterString>NSIDC DAAC &gt; National Snow and Ice Data Center DAAC</gco:CharacterString>\n",
+ " </gmd:organisationName>\n",
+ " <gmd:contactInfo xlink:type="simple">\n",
+ " <gmd:CI_Contact>\n",
+ " <gmd:address xlink:type="simple">\n",
+ " <gmd:CI_Address>\n",
+ " <gmd:electronicMailAddress>\n",
+ " <gco:CharacterString>nsidc@nsidc.org</gco:CharacterString>\n",
+ " </gmd:electronicMailAddress>\n",
+ " </gmd:CI_Address>\n",
+ " </gmd:address>\n",
+ " <gmd:onlineResource xlink:type="simple">\n",
+ " <gmd:CI_OnlineResource>\n",
+ " <gmd:linkage>\n",
+ " <gmd:URL>http://nsidc.org/daac/</gmd:URL>\n",
+ " </gmd:linkage>\n",
+ " </gmd:CI_OnlineResource>\n",
+ " </gmd:onlineResource>\n",
+ " </gmd:CI_Contact>\n",
+ " </gmd:contactInfo>\n",
+ " <gmd:role>\n",
+ " <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode" codeListValue="pointOfContact">pointOfContact</gmd:CI_RoleCode>\n",
+ " </gmd:role>\n",
+ " </gmd:CI_ResponsibleParty>\n",
+ " </gmd:contact>\n",
+ " <gmd:dateStamp>\n",
+ " <gco:Date>2014-06-17</gco:Date>\n",
+ " </gmd:dateStamp>\n",
+ " <gmd:metadataStandardName>\n",
+ " <gco:CharacterString>ISO 19115-2 Geographic information - Metadata - Part 2: Extensions for imagery and gridded data</gco:CharacterString>\n",
+ " </gmd:metadataStandardName>\n",
+ " <gmd:metadataStandardVersion>\n",
+ " <gco:CharacterString>ISO 19115-2:2009-02-15</gco:CharacterString>\n",
+ " </gmd:metadataStandardVersion>\n",
+ " <gmd:spatialRepresentationInfo xlink:type="simple">\n",
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+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gmx:FileName>SMAP_L3_SM_P_SPS_OutputConfig_L3_SM_P.xml</gmx:FileName>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2024-05-02</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="creation">creation</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>R19240</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " <gmd:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>OutputConfig</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:sourceCitation>\n",
+ " </gmi:LE_Source>\n",
+ " </gmd:source>\n",
+ " <gmd:source xlink:type="simple">\n",
+ " <gmi:LE_Source>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>A configuration file generated automatically within the SMAP data system that specifies all of the conditions required for each individual run of the Radiometer Level 3 SM P Science Processing Software (SPS).</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " <gmd:sourceCitation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gmx:FileName>SMAP_L3_SM_P_SPS_RunConfig_20240502T191336188.xml</gmx:FileName>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2024-05-02</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="creation">creation</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>R19240</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " <gmd:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>RunConfig</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:sourceCitation>\n",
+ " </gmi:LE_Source>\n",
+ " </gmd:source>\n",
+ " </gmd:LI_Lineage>\n",
+ " </gmd:lineage>\n",
+ " </gmd:DQ_DataQuality>\n",
+ " </gmd:dataQualityInfo>\n",
+ " <gmi:acquisitionInformation xlink:type="simple">\n",
+ " <gmi:MI_AcquisitionInformation>\n",
+ " <gmi:platform xlink:type="simple">\n",
+ " <eos:EOS_Platform>\n",
+ " <gmi:citation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>SMAP Handbook</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2014-07-01</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="publication">publication</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>JPL CL#14-2285, JPL 400-1567</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmi:citation>\n",
+ " <gmi:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>SMAP</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>http://smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmi:identifier>\n",
+ " <gmi:description>\n",
+ " <gco:CharacterString>The SMAP observatory houses an L-band radiometer that operates at 1.414 GHz and an L-band radar that operates at 1.225 GHz. The instruments share a rotating reflector antenna with a 6 meter aperture that scans over a 1000 km swath. The bus is a 3 axis stabilized spacecraft that provides momentum compensation for the rotating antenna.</gco:CharacterString>\n",
+ " </gmi:description>\n",
+ " <gmi:instrument xlink:type="simple">\n",
+ " <gmi:MI_Instrument>\n",
+ " <gmi:citation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>SMAP Handbook</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2014-07-01</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="publication">publication</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>JPL CL#14-2285, JPL 400-1567</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmi:citation>\n",
+ " <gmi:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>SMAP SAR</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmi:identifier>\n",
+ " <gmi:type>\n",
+ " <gco:CharacterString>L-Band Synthetic Aperture Radar</gco:CharacterString>\n",
+ " </gmi:type>\n",
+ " <gmi:description>\n",
+ " <gco:CharacterString>The SMAP 1.225 GHz L-Band Radar Instrument</gco:CharacterString>\n",
+ " </gmi:description>\n",
+ " </gmi:MI_Instrument>\n",
+ " </gmi:instrument>\n",
+ " <gmi:instrument xlink:type="simple">\n",
+ " <gmi:MI_Instrument>\n",
+ " <gmi:citation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>SMAP Handbook</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2014-07-01</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="publication">publication</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>JPL CL#14-2285, JPL 400-1567</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmi:citation>\n",
+ " <gmi:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>SMAP RAD</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmi:identifier>\n",
+ " <gmi:type>\n",
+ " <gco:CharacterString>L-Band Radiometer</gco:CharacterString>\n",
+ " </gmi:type>\n",
+ " <gmi:description>\n",
+ " <gco:CharacterString>The SMAP 1.414 GHz L-Band Radiometer</gco:CharacterString>\n",
+ " </gmi:description>\n",
+ " </gmi:MI_Instrument>\n",
+ " </gmi:instrument>\n",
+ " <eos:otherProperty xlink:type="simple">\n",
+ " <gco:Record xlink:type="simple" xsi:type="eos:EOS_AdditionalAttributes_PropertyType">\n",
+ " <eos:EOS_AdditionalAttributes>\n",
+ " <eos:additionalAttribute xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttribute>\n",
+ " <eos:reference xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttributeDescription>\n",
+ " <eos:type>\n",
+ " <eos:EOS_AdditionalAttributeTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/" codeListValue="processingInformation">processingInformation</eos:EOS_AdditionalAttributeTypeCode>\n",
+ " </eos:type>\n",
+ " <eos:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>uuid for stopRevNumber</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>http://smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " </gmd:MD_Identifier>\n",
+ " </eos:identifier>\n",
+ " <eos:name>\n",
+ " <gco:CharacterString>stopRevNumber</gco:CharacterString>\n",
+ " </eos:name>\n",
+ " <eos:dataType>\n",
+ " <eos:EOS_AdditionalAttributeDataTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/Codelists.xml#EOS_AdditionalAttributeDataTypeCode" codeListValue="int">int</eos:EOS_AdditionalAttributeDataTypeCode>\n",
+ " </eos:dataType>\n",
+ " </eos:EOS_AdditionalAttributeDescription>\n",
+ " </eos:reference>\n",
+ " <eos:value>\n",
+ " <gco:CharacterString>11121</gco:CharacterString>\n",
+ " </eos:value>\n",
+ " </eos:EOS_AdditionalAttribute>\n",
+ " </eos:additionalAttribute>\n",
+ " <eos:additionalAttribute xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttribute>\n",
+ " <eos:reference xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttributeDescription>\n",
+ " <eos:type>\n",
+ " <eos:EOS_AdditionalAttributeTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/" codeListValue="processingInformation">processingInformation</eos:EOS_AdditionalAttributeTypeCode>\n",
+ " </eos:type>\n",
+ " <eos:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>uuid for startRevNumber</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>http://smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " </gmd:MD_Identifier>\n",
+ " </eos:identifier>\n",
+ " <eos:name>\n",
+ " <gco:CharacterString>startRevNumber</gco:CharacterString>\n",
+ " </eos:name>\n",
+ " <eos:dataType>\n",
+ " <eos:EOS_AdditionalAttributeDataTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/Codelists.xml#EOS_AdditionalAttributeDataTypeCode" codeListValue="int">int</eos:EOS_AdditionalAttributeDataTypeCode>\n",
+ " </eos:dataType>\n",
+ " </eos:EOS_AdditionalAttributeDescription>\n",
+ " </eos:reference>\n",
+ " <eos:value>\n",
+ " <gco:CharacterString>11107</gco:CharacterString>\n",
+ " </eos:value>\n",
+ " </eos:EOS_AdditionalAttribute>\n",
+ " </eos:additionalAttribute>\n",
+ " <eos:additionalAttribute xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttribute>\n",
+ " <eos:reference xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttributeDescription>\n",
+ " <eos:type>\n",
+ " <eos:EOS_AdditionalAttributeTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/" codeListValue="processingInformation">processingInformation</eos:EOS_AdditionalAttributeTypeCode>\n",
+ " </eos:type>\n",
+ " <eos:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>uuid for AntennaRotationRate</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>http://smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " </gmd:MD_Identifier>\n",
+ " </eos:identifier>\n",
+ " <eos:name>\n",
+ " <gco:CharacterString>AntennaRotationRate</gco:CharacterString>\n",
+ " </eos:name>\n",
+ " <eos:dataType>\n",
+ " <eos:EOS_AdditionalAttributeDataTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/Codelists.xml#EOS_AdditionalAttributeDataTypeCode" codeListValue="float">float</eos:EOS_AdditionalAttributeDataTypeCode>\n",
+ " </eos:dataType>\n",
+ " </eos:EOS_AdditionalAttributeDescription>\n",
+ " </eos:reference>\n",
+ " <eos:value>\n",
+ " <gco:CharacterString>14.6</gco:CharacterString>\n",
+ " </eos:value>\n",
+ " </eos:EOS_AdditionalAttribute>\n",
+ " </eos:additionalAttribute>\n",
+ " </eos:EOS_AdditionalAttributes>\n",
+ " </gco:Record>\n",
+ " </eos:otherProperty>\n",
+ " </eos:EOS_Platform>\n",
+ " </gmi:platform>\n",
+ " </gmi:MI_AcquisitionInformation>\n",
+ " </gmi:acquisitionInformation>\n",
+ " </gmi:MI_Metadata>\n",
+ " </gmd:has>\n",
+ " </gmd:DS_DataSet>\n",
+ " </gmd:composedOf>\n",
+ "\n",
+ " <gmd:seriesMetadata gco:nilReason="missing" xlink:type="simple"/>\n",
+ "\n",
+ "</gmd:DS_Series>\n",
+ "
iso_19139_dataset_xml_md5 :
8575fcbb24fb9331cbb74df74abd5b15
iso_19139_series_xml :
<?xml version="1.0" encoding="UTF-8"?>\n",
+ "<gmd:DS_Series xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"\n",
+ " xsi:schemaLocation="http://www.isotc211.org/2005/gmi http://cdn.earthdata.nasa.gov/iso/schema/1.0/ISO19115-2_EOS.xsd"\n",
+ " xmlns:gco="http://www.isotc211.org/2005/gco"\n",
+ " xmlns:gmd="http://www.isotc211.org/2005/gmd"\n",
+ " xmlns:xlink="http://www.w3.org/1999/xlink"\n",
+ " xmlns:gml="http://www.opengis.net/gml/3.2"\n",
+ " xmlns:gsr="http://www.isotc211.org/2005/gsr"\n",
+ " xmlns:gss="http://www.isotc211.org/2005/gss"\n",
+ " xmlns:gts="http://www.isotc211.org/2005/gts"\n",
+ " xmlns:gmi="http://www.isotc211.org/2005/gmi"\n",
+ " xmlns:gmx="http://www.isotc211.org/2005/gmx">\n",
+ " <gmd:composedOf gco:nilReason="inapplicable"/>\n",
+ " <gmd:seriesMetadata>\n",
+ " <gmi:MI_Metadata>\n",
+ " <!-- With reference to file name here, do we need to use MD_Identification/CI_Citation to reference the file. -->\n",
+ " <gmd:fileIdentifier>\n",
+ " <gco:CharacterString>L3_SM_P</gco:CharacterString>\n",
+ " <!-- Assume that the file Identifier for series metadata would be the identifier that denotes that a file belongs to this series. -->\n",
+ " </gmd:fileIdentifier>\n",
+ " <gmd:language>\n",
+ " <gco:CharacterString>eng</gco:CharacterString>\n",
+ " </gmd:language>\n",
+ " <gmd:characterSet>\n",
+ " <gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode" codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>\n",
+ " </gmd:characterSet>\n",
+ " <gmd:hierarchyLevel>\n",
+ " <gmd:MD_ScopeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ScopeCode" codeListValue="series">series</gmd:MD_ScopeCode>\n",
+ " </gmd:hierarchyLevel>\n",
+ " <gmd:contact>\n",
+ " <gmd:CI_ResponsibleParty>\n",
+ " <gmd:organisationName>\n",
+ " <gco:CharacterString>NSIDC DAAC > National Snow and Ice Data Center DAAC</gco:CharacterString>\n",
+ " </gmd:organisationName>\n",
+ " <gmd:contactInfo>\n",
+ " <gmd:CI_Contact>\n",
+ " <gmd:address>\n",
+ " <gmd:CI_Address>\n",
+ " <gmd:electronicMailAddress>\n",
+ " <gco:CharacterString>nsidc@nsidc.org</gco:CharacterString>\n",
+ " </gmd:electronicMailAddress>\n",
+ " </gmd:CI_Address>\n",
+ " </gmd:address>\n",
+ " <gmd:onlineResource>\n",
+ " <gmd:CI_OnlineResource>\n",
+ " <gmd:linkage>\n",
+ " <gmd:URL>http://nsidc.org/daac/</gmd:URL>\n",
+ " </gmd:linkage>\n",
+ " </gmd:CI_OnlineResource>\n",
+ " </gmd:onlineResource>\n",
+ " </gmd:CI_Contact>\n",
+ " </gmd:contactInfo>\n",
+ " <gmd:role>\n",
+ " <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode" codeListValue="pointOfContact">pointOfContact</gmd:CI_RoleCode>\n",
+ " </gmd:role>\n",
+ " </gmd:CI_ResponsibleParty>\n",
+ " </gmd:contact>\n",
+ " <gmd:dateStamp>\n",
+ " <gco:Date>2019-04-15</gco:Date>\n",
+ " </gmd:dateStamp>\n",
+ " <gmd:metadataStandardName>\n",
+ " <gco:CharacterString>ISO 19115-2 Geographic information - Metadata - Part 2: Extensions for imagery and gridded data</gco:CharacterString>\n",
+ " </gmd:metadataStandardName>\n",
+ " <gmd:metadataStandardVersion>\n",
+ " <gco:CharacterString>ISO 19115-2:2009-02-15</gco:CharacterString>\n",
+ " </gmd:metadataStandardVersion>\n",
+ " <gmd:identificationInfo>\n",
+ " <gmd:MD_DataIdentification>\n",
+ " <gmd:citation>\n",
+ " <!-- If file name reference in MI_Metadata is sufficient, can use this CI_Citation to reference Product Specification Document. -->\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <!-- This field provides the product Long Name required by the ECS. -->\n",
+ " <gco:CharacterString>SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date>\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <!-- This field provides the date of a particular release or build. For the ECS, this is the RevisionDate, a required field. -->\n",
+ " <gco:Date>2023-08-31</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="revision">revision</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <!-- Specifies the SMAP Release ID -->\n",
+ " <gco:CharacterString>R19</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " <gmd:identifier>\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <!-- This field provides the product Short Name. This is the ECS Short Name rather than the SMAP Short Name. -->\n",
+ " <gco:CharacterString>SPL3SMP</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <!-- This field is intended to provide a namespace identifier for SMAP data product Short Names. Team should devise an identifier. -->\n",
+ " <gco:CharacterString>smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>The ECS Short Name</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " <gmd:identifier>\n",
+ " <gmd:MD_Identifier> <!-- This field provides the ECS Version ID. -->\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>009</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace> <!-- This field is intended to provide the namespace for ECS Version IDs for the SMAP mission. Team should devise an identifier.-->\n",
+ " <gco:CharacterString>gov.nasa.esdis</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>The ECS Version ID</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " <gmd:identifier>\n",
+ " <gmd:MD_Identifier> <!-- This field provides the Digital Object Identifier (DOI). -->\n",
+ " <gmd:code>\n",
+ " <gmx:Anchor xlink:actuate="onRequest" xlink:href="http://dx.doi.org/10.5067/4XXOGX0OOW1S" >doi:10.5067/4XXOGX0OOW1S</gmx:Anchor>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace> <!-- This field is intended to provide a namespace identifier for DOIs. What would be best specification?-->\n",
+ " <gco:CharacterString>gov.nasa.esdis</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>A Digital Object Identifier (DOI)</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " <gmd:citedResponsibleParty>\n",
+ " <gmd:CI_ResponsibleParty>\n",
+ " <gmd:organisationName>\n",
+ " <gco:CharacterString>National Aeronautics and Space Administration (NASA)</gco:CharacterString>\n",
+ " </gmd:organisationName>\n",
+ " <gmd:role>\n",
+ " <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode" codeListValue="resourceProvider">resourceProvider</gmd:CI_RoleCode>\n",
+ " </gmd:role>\n",
+ " </gmd:CI_ResponsibleParty>\n",
+ " </gmd:citedResponsibleParty>\n",
+ " <gmd:citedResponsibleParty>\n",
+ " <gmd:CI_ResponsibleParty>\n",
+ " <gmd:organisationName>\n",
+ " <!-- This field provides the ProcessingCenter, a required field for the ECS. The ECS will need to check the roleCode to ensure they're viewing the correct field.-->\n",
+ " <gco:CharacterString>Jet Propulsion Laboratory</gco:CharacterString>\n",
+ " </gmd:organisationName>\n",
+ " <gmd:role>\n",
+ " <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode" codeListValue="originator">originator</gmd:CI_RoleCode>\n",
+ " </gmd:role>\n",
+ " </gmd:CI_ResponsibleParty>\n",
+ " </gmd:citedResponsibleParty>\n",
+ " <gmd:presentationForm>\n",
+ " <gmd:CI_PresentationFormCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_PresentationFormCode" codeListValue="documentDigital">documentDigital</gmd:CI_PresentationFormCode>\n",
+ " </gmd:presentationForm>\n",
+ " <gmd:otherCitationDetails>\n",
+ " <gco:CharacterString>The Calibration and Validation Version 2 Release of the SMAP Level 3 Daily Global Composite Passive Soil Moisture Science Processing Software.</gco:CharacterString>\n",
+ " </gmd:otherCitationDetails>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:citation>\n",
+ " <gmd:abstract>\n",
+ " <!-- This field contains the CollectionDescription required by the ECS. -->\n",
+ " <gco:CharacterString>Daily global composite of up-to 30 half-orbit L2_SM_P soil moisture estimates based on radiometer brightness temperature measurements acquired by the SMAP radiometer during ascending and descending half-orbits at approximately 6 PM and 6 AM local solar time.</gco:CharacterString>\n",
+ " </gmd:abstract>\n",
+ " <gmd:purpose>\n",
+ " <gco:CharacterString>The SMAP L3_SM_P algorithm provides daily global composite of soil moistures based on radiometer data on a 36 km grid.</gco:CharacterString>\n",
+ " </gmd:purpose>\n",
+ " <gmd:credit>\n",
+ " <!-- This field can name individuals or organizations for credit. For now, it specifies NASA. -->\n",
+ " <gco:CharacterString>The software that generates the Level 3 Soil Moisture Passive product and the data system that automates its production were designed and implemented \n",
+ " at the Jet Propulsion Laboratory, California Institute of Technology in Pasadena, California.</gco:CharacterString>\n",
+ " </gmd:credit>\n",
+ " <gmd:status>\n",
+ " <gmd:MD_ProgressCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ProgressCode" codeListValue="onGoing">onGoing</gmd:MD_ProgressCode>\n",
+ " </gmd:status>\n",
+ " <gmd:pointOfContact>\n",
+ " <gmd:CI_ResponsibleParty>\n",
+ " <gmd:organisationName>\n",
+ " <!-- This field provides the ArchiveCenter, a required entry for the ECS. -->\n",
+ " <gco:CharacterString>National Snow and Ice Data Center</gco:CharacterString>\n",
+ " </gmd:organisationName>\n",
+ " <gmd:role>\n",
+ " <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode" codeListValue="distributor">distributor</gmd:CI_RoleCode>\n",
+ " </gmd:role>\n",
+ " </gmd:CI_ResponsibleParty>\n",
+ " </gmd:pointOfContact>\n",
+ " <gmd:resourceMaintenance>\n",
+ " <gmd:MD_MaintenanceInformation>\n",
+ " <gmd:maintenanceAndUpdateFrequency>\n",
+ " <gmd:MD_MaintenanceFrequencyCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_MaintenanceFrequencyCode" codeListValue="asNeeded">asNeeded</gmd:MD_MaintenanceFrequencyCode>\n",
+ " </gmd:maintenanceAndUpdateFrequency>\n",
+ " <gmd:dateOfNextUpdate>\n",
+ " <gco:Date>2017-04-01</gco:Date>\n",
+ " </gmd:dateOfNextUpdate>\n",
+ " <gmd:updateScope>\n",
+ " <gmd:MD_ScopeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ScopeCode" codeListValue="series">series</gmd:MD_ScopeCode>\n",
+ " </gmd:updateScope>\n",
+ " </gmd:MD_MaintenanceInformation>\n",
+ " </gmd:resourceMaintenance>\n",
+ " <gmd:resourceFormat>\n",
+ " <gmd:MD_Format>\n",
+ " <gmd:name>\n",
+ " <gco:CharacterString>HDF5</gco:CharacterString>\n",
+ " </gmd:name>\n",
+ " <gmd:version>\n",
+ " <gco:CharacterString>1.8.13</gco:CharacterString>\n",
+ " </gmd:version>\n",
+ " </gmd:MD_Format>\n",
+ " </gmd:resourceFormat>\n",
+ " <gmd:descriptiveKeywords>\n",
+ " <gmd:MD_Keywords>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > LAND SURFACE > SOILS > SOIL MOISTURE/WATER CONTENT</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > CLIMATE INDICATORS > LAND SURFACE/AGRICULTURE INDICATORS > SOIL MOISTURE</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > SPECTRAL/ENGINEERING > MICROWAVE > BRIGHTNESS TEMPERATURE</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SNOW/ICE > FREEZE/THAW</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > CRYOSPHERE > SNOW/ICE > FREEZE/THAW</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > BIOSPHERE > VEGETATION > PLANT CHARACTERISTICS > VEGETATION WATER CONTENT</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > LAND SURFACE > SURFACE RADIATIVE PROPERTIES > ALBEDO</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > SURFACE ROUGHNESS</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > LAND SURFACE > SURFACE RADIATIVE PROPERTIES > ALBEDO</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > TERRESTRIAL HYDROSPHERE> SNOW/ICE > FREEZE/THAW</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:type>\n",
+ " <gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode" codeListValue="theme">theme</gmd:MD_KeywordTypeCode>\n",
+ " </gmd:type>\n",
+ " <gmd:thesaurusName>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>NASA/GCMD Earth Science Keywords</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date gco:nilReason="unknown"/>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:thesaurusName>\n",
+ " </gmd:MD_Keywords>\n",
+ " </gmd:descriptiveKeywords>\n",
+ " <gmd:descriptiveKeywords>\n",
+ " <gmd:MD_Keywords>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>Earth Remote Sensing Instruments > Passive Remote Sensing > Spectrometers/Radiometers > Imaging Spectrometers/Radiometers > SMAP L-BAND RADIOMETER > SMAP L-Band Radiometer</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:type>\n",
+ " <gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode" codeListValue="theme">theme</gmd:MD_KeywordTypeCode>\n",
+ " </gmd:type>\n",
+ " <gmd:thesaurusName>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>NASA/GCMD Earth Science Keywords</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date gco:nilReason="unknown"/>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:thesaurusName>\n",
+ " </gmd:MD_Keywords>\n",
+ " </gmd:descriptiveKeywords>\n",
+ " <gmd:descriptiveKeywords>\n",
+ " <gmd:MD_Keywords>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>Earth Observation Satellites > NASA Decadal Survey > SMAP > Soil Moisture Active and Passive Observatory</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:type>\n",
+ " <gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode" codeListValue="theme">theme</gmd:MD_KeywordTypeCode>\n",
+ " </gmd:type>\n",
+ " <gmd:thesaurusName>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>NASA/GCMD Earth Science Keywords</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date gco:nilReason="unknown"/>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:thesaurusName>\n",
+ " </gmd:MD_Keywords>\n",
+ " </gmd:descriptiveKeywords>\n",
+ " <gmd:descriptiveKeywords>\n",
+ " <gmd:MD_Keywords>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>GEOGRAPHIC REGION > GLOBAL</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:type>\n",
+ " <gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode" codeListValue="theme">theme</gmd:MD_KeywordTypeCode>\n",
+ " </gmd:type>\n",
+ " <gmd:thesaurusName>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>NASA/GCMD Earth Science Keywords</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date gco:nilReason="unknown"/>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:thesaurusName>\n",
+ " </gmd:MD_Keywords>\n",
+ " </gmd:descriptiveKeywords> \n",
+ " <gmd:aggregationInfo>\n",
+ " <gmd:MD_AggregateInformation>\n",
+ " <gmd:aggregateDataSetIdentifier>\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>SMAP</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:aggregateDataSetIdentifier>\n",
+ " <gmd:associationType>\n",
+ " <gmd:DS_AssociationTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#DS_AssociationTypeCode" codeListValue="largerWorkCitation">largerWorkCitation</gmd:DS_AssociationTypeCode>\n",
+ " </gmd:associationType>\n",
+ " <gmd:initiativeType>\n",
+ " <gmd:DS_InitiativeTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#DS_AssociationTypeCode" codeListValue="mission">mission</gmd:DS_InitiativeTypeCode>\n",
+ " </gmd:initiativeType>\n",
+ " </gmd:MD_AggregateInformation>\n",
+ " </gmd:aggregationInfo>\n",
+ " <gmd:spatialRepresentationType>\n",
+ " <gmd:MD_SpatialRepresentationTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_SpatialRepresentationTypeCode" codeListValue="grid">grid</gmd:MD_SpatialRepresentationTypeCode>\n",
+ " </gmd:spatialRepresentationType>\n",
+ " <gmd:spatialResolution>\n",
+ " <gmd:MD_Resolution>\n",
+ " <gmd:distance>\n",
+ " <gco:Distance uom="km">36</gco:Distance>\n",
+ " </gmd:distance>\n",
+ " </gmd:MD_Resolution>\n",
+ " </gmd:spatialResolution>\n",
+ " <gmd:language>\n",
+ " <gco:CharacterString>eng</gco:CharacterString>\n",
+ " </gmd:language>\n",
+ " <gmd:characterSet>\n",
+ " <gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode" codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>\n",
+ " </gmd:characterSet>\n",
+ " <gmd:topicCategory>\n",
+ " <gmd:MD_TopicCategoryCode>geoscientificInformation</gmd:MD_TopicCategoryCode>\n",
+ " </gmd:topicCategory>\n",
+ " <gmd:environmentDescription>\n",
+ " <gco:CharacterString>Data product generated by the SMAP mission in HDF5 format with metadata that conforms to the ISO 19115 model.</gco:CharacterString>\n",
+ " </gmd:environmentDescription>\n",
+ " <gmd:extent>\n",
+ " <gmd:EX_Extent>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>Soil moisture is\n",
+ "\t\t\t\tretrieved over land targets on the\n",
+ "\t\t\t\tdescending (AM) and ascending (PM) SMAP half-orbits, \n",
+ " while the SMAP instruments are operating in the nominal mode. Retrievals are performed but flagged as questionable \n",
+ " over urban areas, mountainous areas with high elevation variability, and areas with high ( > 5 kg/m**2) vegetation \n",
+ " water content; for retrievals using the high-resolution radar, cells in the nadir region are also flagged.\n",
+ " Retrievals are inhibited for permanent snow/ice, frozen ground, and excessive static or transient open water in the cell,\n",
+ " and for excessive RFI in the sensor data.</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " <gmd:geographicElement>\n",
+ " <!-- This defines the bounding box for all SMAP Level 3 Passive Soil Moisture data products. -->\n",
+ " <gmd:EX_GeographicBoundingBox>\n",
+ " <gmd:extentTypeCode>\n",
+ " <gco:Boolean>1</gco:Boolean>\n",
+ " </gmd:extentTypeCode>\n",
+ " <gmd:westBoundLongitude>\n",
+ " <gco:Decimal>-180.00</gco:Decimal>\n",
+ " </gmd:westBoundLongitude>\n",
+ " <gmd:eastBoundLongitude>\n",
+ " <gco:Decimal>180.00</gco:Decimal>\n",
+ " </gmd:eastBoundLongitude>\n",
+ " <gmd:southBoundLatitude>\n",
+ " <gco:Decimal>-85.0445</gco:Decimal>\n",
+ " </gmd:southBoundLatitude>\n",
+ " <gmd:northBoundLatitude>\n",
+ " <gco:Decimal>85.0445</gco:Decimal>\n",
+ " </gmd:northBoundLatitude>\n",
+ " </gmd:EX_GeographicBoundingBox>\n",
+ " </gmd:geographicElement>\n",
+ " <gmd:temporalElement>\n",
+ " <gmd:EX_TemporalExtent>\n",
+ " <!-- Mimics use in GHRSST. See no evidence of conformance to standard -->\n",
+ " <gmd:extent>\n",
+ " <gml:TimePeriod gml:id="swathTemporalExtent">\n",
+ " <!-- This defines the time period covered by all SMAP Level 3 Passive Soil Moisture data products. \n",
+ " ECS indicates that they will automatically extend the final time based on receipt of data products. -->\n",
+ " <gml:beginPosition>2015-03-31T00:00:00.000Z</gml:beginPosition>\n",
+ " <gml:endPosition>2020-12-31T00:00:00.000Z</gml:endPosition>\n",
+ " </gml:TimePeriod>\n",
+ " </gmd:extent>\n",
+ " </gmd:EX_TemporalExtent>\n",
+ " </gmd:temporalElement>\n",
+ " </gmd:EX_Extent>\n",
+ " </gmd:extent>\n",
+ " </gmd:MD_DataIdentification>\n",
+ " </gmd:identificationInfo>\n",
+ " <gmd:identificationInfo>\n",
+ " <!-- This field is used to reference the Product Specification Document. If and when the model moves to ISO 19115-1, move this reference to additionalDocumentation. -->\n",
+ " <gmd:MD_DataIdentification>\n",
+ " <gmd:citation>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>Product Specification Document for the SMAP Level 3 Passive Soil Moisture Product (L3_SM_P)</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date>\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2013-02-08</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="publication">publication</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>1.0</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " <gmd:identifier>\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>L3_SM_P</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <!-- This field is intended to provide a namespace identifier for SMAP data product Short Names. Team should devise an identifier. -->\n",
+ " <gco:CharacterString>smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>Short name used by the Soil Moisture Active Passive (SMAP) mission to identify the Level 3 Passive Soil Moisture product.</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " <gmd:presentationForm>\n",
+ " <gmd:CI_PresentationFormCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_PresentationFormCode" codeListValue="documentDigital">documentDigital</gmd:CI_PresentationFormCode>\n",
+ " </gmd:presentationForm>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:citation>\n",
+ " <gmd:abstract>\n",
+ " <gco:CharacterString>The Product Specification Document that fully describes the content and format of this data product.</gco:CharacterString>\n",
+ " </gmd:abstract>\n",
+ " <gmd:language>\n",
+ " <gco:CharacterString>eng</gco:CharacterString>\n",
+ " </gmd:language>\n",
+ " <gmd:characterSet>\n",
+ " <gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode" codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>\n",
+ " </gmd:characterSet>\n",
+ " </gmd:MD_DataIdentification>\n",
+ " </gmd:identificationInfo>\n",
+ " </gmi:MI_Metadata>\n",
+ " </gmd:seriesMetadata>\n",
+ "</gmd:DS_Series>\n",
+ "
The column index of the 36 km EASE grid cell that contains the associated data.
valid_max :
963
valid_min :
0
[391384 values with dtype=float32]
EASE_row_index
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The row index of the 36 km EASE grid cell that contains the associated data.
valid_max :
405
valid_min :
0
[391384 values with dtype=float32]
albedo
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_dca
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scah
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-H within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scav
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-V within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
boresight_incidence
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Representative angle between the antenna boresight vector and the normal to the Earth's surface for all footprints within the cell.
units :
degrees
valid_max :
90.0
valid_min :
0.0
[391384 values with dtype=float32]
bulk_density
(phony_dim_0, phony_dim_1)
float32
...
long_name :
A unitless value that is indicative of aggregated bulk_density within the 36 km grid cell.
valid_max :
2.65
valid_min :
0.0
[391384 values with dtype=float32]
clay_fraction
(phony_dim_0, phony_dim_1)
float32
...
long_name :
A unitless value that is indicative of aggregated clay fraction within the 36 km grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
freeze_thaw_fraction
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
grid_surface_status
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Indicates if the grid point lies on land (0) or water (1).
valid_max :
1
valid_min :
0
[391384 values with dtype=float32]
landcover_class
(phony_dim_0, phony_dim_1, phony_dim_2)
float32
...
long_name :
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
[1174152 values with dtype=float32]
landcover_class_fraction
(phony_dim_0, phony_dim_1, phony_dim_2)
float32
...
long_name :
The fraction of the grid cell that contains the most common land cover in that area based on the IGBP landcover map.
valid_max :
1.0
valid_min :
0.0
[1174152 values with dtype=float32]
latitude
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Latitude of the center of the Earth based grid cell.
units :
degrees_north
[391384 values with dtype=float32]
latitude_centroid
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Weighted average of the latitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
longitude
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Longitude of the center of the Earth based grid cell.
units :
degrees_east
[391384 values with dtype=float32]
longitude_centroid
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Weighted average of the longitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
radar_water_body_fraction
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The fraction of the area of the 36 km grid cell that is covered by water based on the radar detection algorithm.
Bit flags that represent the quality of the vertical polarization brightness temperature within each grid cell
[391384 values with dtype=float32]
tb_time_seconds
(phony_dim_0, phony_dim_1)
float64
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
units :
seconds
valid_max :
940000000.0
valid_min :
-999999.9
[391384 values with dtype=float64]
tb_time_utc
(phony_dim_0, phony_dim_1)
|S24
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in UTC.
[391384 values with dtype=|S24]
tb_v_corrected
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell adjusted for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
tb_v_uncorrected
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell before adjustment for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
vegetation_opacity
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_dca
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scah
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-H retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scav
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-V retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_water_content
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Representative measure of water in the vegetation within the 36 km grid cell.
The column index of the 36 km EASE grid cell that contains the associated data.
valid_max :
963
valid_min :
0
[391384 values with dtype=float32]
EASE_row_index_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
The row index of the 36 km EASE grid cell that contains the associated data.
valid_max :
405
valid_min :
0
[391384 values with dtype=float32]
albedo_dca_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scah_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-H retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scav_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-V retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
boresight_incidence_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
Representative angle between the antenna boresight vector and the normal to the Earth's surface for all footprints within the cell.
units :
degrees
valid_max :
90.0
valid_min :
0.0
[391384 values with dtype=float32]
bulk_density_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
A unitless value that is indicative of aggregated bulk density within the 36 km grid cell.
valid_max :
2.65
valid_min :
0.0
[391384 values with dtype=float32]
clay_fraction_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
A unitless value that is indicative of aggregated clay fraction within the 36 km grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
freeze_thaw_fraction_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
grid_surface_status_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
Indicates if the grid point lies on land (0) or water (1).
valid_max :
1
valid_min :
0
[391384 values with dtype=float32]
landcover_class_fraction_pm
(phony_dim_3, phony_dim_4, phony_dim_5)
float32
...
long_name :
The fraction of the grid cell that contains the most common land cover in that area based on the IGBP landcover map.
valid_max :
1.0
valid_min :
0.0
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landcover_class_pm
(phony_dim_3, phony_dim_4, phony_dim_5)
float32
...
long_name :
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
[1174152 values with dtype=float32]
latitude_centroid_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
Weighted average of the latitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
latitude_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
Latitude of the center of the Earth based grid cell.
units :
degrees_north
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
longitude_centroid_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
Weighted average of the longitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
longitude_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
Longitude of the center of the Earth based grid cell.
units :
degrees_east
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
radar_water_body_fraction_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
The fraction of the area of the 36 km grid cell that is covered by water based on the radar detection algorithm.
Bit flags that represent the quality of the vertical polarization brightness temperature within each grid cell
[391384 values with dtype=float32]
tb_time_seconds_pm
(phony_dim_3, phony_dim_4)
float64
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
units :
seconds
valid_max :
940000000.0
valid_min :
-999999.9
[391384 values with dtype=float64]
tb_time_utc_pm
(phony_dim_3, phony_dim_4)
|S24
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in UTC.
[391384 values with dtype=|S24]
tb_v_corrected_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell adjusted for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
tb_v_uncorrected_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell before adjustment for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
vegetation_opacity_dca_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
The measured opacity of the vegetation used in DCA retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
The measured opacity of the vegetation used in DCA retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scah_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
The measured opacity of the vegetation used in SCA-H retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scav_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
The measured opacity of the vegetation used in SCA-V retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_water_content_pm
(phony_dim_3, phony_dim_4)
float32
...
long_name :
Representative measure of water in the vegetation within the 36 km grid cell.
The SMAP observatory houses an L-band radiometer that operates at 1.414 GHz and an L-band radar that operates at 1.225 GHz. The instruments share a rotating reflector antenna with a 6 meter aperture that scans over a 1000 km swath. The bus is a 3 axis stabilized spacecraft that provides momentum compensation for the rotating antenna.
Percentage of EASE2 grid cells that lack soil moisture retrieval values relative to the total number of grid cells where soil moisture retrieval was attempted.
Daily global composite of up-to 15 half-orbit L2_SM_P soil moisture estimates based on radiometer brightness temperature measurements acquired by the SMAP radiometer during descending half-orbits at approximately 6 AM local solar time.
characterSet :
utf8
creationDate :
2024-05-02
credit :
The software that generates the Level 3 SM_P product and the data system that automates its production were designed and implemented at the Jet Propulsion Laboratory, California Institute of Technology in Pasadena, California.
fileName :
SMAP_L3_SM_P_20170301_R19240_001.h5
format :
HDF5
formatVersion :
1.8.13
language :
eng
maintenanceAndUpdateFrequency :
asNeeded
maintenanceDate :
2016-05-01
originatorOrganizationName :
Jet Propulsion Laboratory
otherCitationDetails :
The Calibration and Validation Version 2 Release of the SMAP Level 3 Daily Global Composite Passive Soil Moisture Science Processing Software.
purpose :
The SMAP L3_SM_P effort provides soil moistures based on radiometer data on a 36 km grid.
Soil moisture is retrieved over land targets on the descending (AM) SMAP half-orbits when the SMAP spacecraft is travelling from North to South, while the SMAP instruments are operating in the nominal mode. The L3_SM_P product represents soil moisture retrieved over the entre UTC day. Retrievals are performed but flagged as questionable over urban areas, mountainous areas with high elevation variability, and areas with high ( > 5 kg/m**2) vegetation water content; for retrievals using the high-resolution radar, cells in the nadir region are also flagged. Retrievals are inhibited for permanent snow/ice, frozen ground, and excessive static or transient open water in the cell, and for excessive RFI in the sensor data.
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+ "Dimensions without coordinates: y, x, igbp_class\n",
+ "Data variables:\n",
+ " *empty*\n",
+ "Attributes:\n",
+ " description: The Equal-Area Scalable Earth Grid (EASE-Grid 2.0) is used ...\n",
+ " identifier: Equal-Area Scalable Earth Grid
GridDefinition
y: 406
x: 964
igbp_class: 3
description :
The Equal-Area Scalable Earth Grid (EASE-Grid 2.0) is used for gridding satellite data sets. The EASE-Grid 2.0 is defined on the WGS84 ellipsoid to allow users to import data into standard GIS software formats such as GeoTIFF without reprojection.
Precomputed longitude at each EASEGrid cell on 36-km grid on Global Cylindrical Projection
fileName :
EZ2Lon_M36_002.float32
version :
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+ "
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+ "Data variables:\n",
+ " *empty*\n",
+ "Attributes:\n",
+ " creationDate: 2024-05-02\n",
+ " description: A configuration file that specifies the complete set of el...\n",
+ " fileName: SMAP_L3_SM_P_SPS_InputConfig_L2_SM_P.xml\n",
+ " version: R19240
InputConfiguration
y: 406
x: 964
igbp_class: 3
creationDate :
2024-05-02
description :
A configuration file that specifies the complete set of elements within the input Level 2 SM_P Product that the Radiometer Level 3_SM_P Science Processing Software (SPS) needs in order to function.
Passive soil moisture estimates onto a 36-km global Earth-fixed grid, based on radiometer measurements acquired when the SMAP spacecraft is travelling from North to South at approximately 6:00 AM local time.
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+ "Dimensions without coordinates: y, x, igbp_class\n",
+ "Data variables:\n",
+ " *empty*\n",
+ "Attributes:\n",
+ " creationDate: 2024-05-02\n",
+ " description: A configuration file that specifies the source of the valu...\n",
+ " fileName: SMAP_L3_SM_P_SPS_MetConfig_L2_SM_P.xml\n",
+ " version: R19240
MetadataConfiguration
y: 406
x: 964
igbp_class: 3
creationDate :
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description :
A configuration file that specifies the source of the values for each of the data elements that comprise the metadata in the output Radiometer Level 3_SM_P product.
fileName :
SMAP_L3_SM_P_SPS_MetConfig_L2_SM_P.xml
version :
R19240
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+ "Attributes:\n",
+ " creationDate: 2024-05-02\n",
+ " description: A configuration file that lists the entire content of the ...\n",
+ " fileName: SMAP_L3_SM_P_SPS_OutputConfig_L3_SM_P.xml\n",
+ " version: R19240
OutputConfiguration
y: 406
x: 964
igbp_class: 3
creationDate :
2024-05-02
description :
A configuration file that lists the entire content of the output Radiometer Level 3_SM_P_ product.
fileName :
SMAP_L3_SM_P_SPS_OutputConfig_L3_SM_P.xml
version :
R19240
\n",
+ "
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+ "Data variables:\n",
+ " *empty*\n",
+ "Attributes:\n",
+ " creationDate: 2024-05-02\n",
+ " description: A configuration file generated automatically within the SM...\n",
+ " fileName: SMAP_L3_SM_P_SPS_RunConfig_20240502T191336188.xml\n",
+ " version: R19240
RunConfiguration
y: 406
x: 964
igbp_class: 3
creationDate :
2024-05-02
description :
A configuration file generated automatically within the SMAP data system that specifies all of the conditions required for each individual run of the Radiometer Level 3 SM P Science Processing Software (SPS).
Algorithm Theoretical Basis Document: SMAP L2 and L3 Radiometer Soil Moisture (Passive) Data Products: L2_SM_P & L3_SM_P
ATBDVersion :
Version 1.1
SWVersionID :
026
algorithmDate :
2021-08-17
algorithmDescription :
Level 3 soil moisture product is formed by mosaicking Level 2 soil moisture granule data acquired over one day.
algorithmTitle :
Soil Moisture Active Passive (SMAP) Radiometer processing algorithm
algorithmVersionID :
023
documentDate :
2012-10-26
documentVersion :
Preliminary
documentation :
Algorithm Theoretical Basis Document: SMAP L2 and L3 Radiometer Soil Moisture (Passive) Data Products: L2_SM_P & L3_SM_P
epochJulianDate :
2451545.0
epochUTCDateTime :
2000-01-01T11:58:55.816Z
identifier :
L3_SM_P_SPS
parameterVersionID :
015
processDescription :
Soil moisture retrieved using default retrieval algorithm from brightness temperatures acquired by the SMAP radiometer during the spacecraft descending pass. Level 2 granule data are then mosaicked on a daily basis to form the Level 3 product.
processor :
Soil Moisture Active Passive Mission (SMAP) Science Data System (SDS) Operations Facility
Product Specification Document for the SMAP Level 3 Passive Soil Moisture Product (L3_SM_P)
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+ " abstract: An ASCII product that contains statistical information on ...\n",
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QADatasetIdentification
y: 406
x: 964
igbp_class: 3
abstract :
An ASCII product that contains statistical information on data product results. These statistics enable data producers and users to assess the quality of the data in the data product granule.
creationDate :
2024-05-02
fileName :
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+ "Attributes: (12/18)\n",
+ " CompositeReleaseID: R19\n",
+ " ECSVersionID: 009\n",
+ " abstract: Daily global composite of up-to 30 hal...\n",
+ " characterSet: utf8\n",
+ " credit: The software that generates the Level ...\n",
+ " identifier_product_DOI: doi:10.5067/4XXOGX0OOW1S\n",
+ " ... ...\n",
+ " resourceProviderOrganizationName: National Aeronautics and Space Adminis...\n",
+ " revisionDate: 2023-08-31\n",
+ " shortName: SPL3SMP\n",
+ " spatialRepresentationType: grid\n",
+ " status: onGoing\n",
+ " topicCategory: geoscientificInformation
SeriesIdentification
y: 406
x: 964
igbp_class: 3
CompositeReleaseID :
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ECSVersionID :
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abstract :
Daily global composite of up-to 30 half-orbit L2_SM_P soil moisture estimates based on radiometer brightness temperature measurements acquired by the SMAP radiometer during ascending and descending half-orbits at approximately 6 PM and 6 AM local solar time.
characterSet :
utf8
credit :
The software that generates the Level 3 Soil Moisture Passive product and the data system that automates its production were designed and implemented \n",
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identifier_product_DOI :
doi:10.5067/4XXOGX0OOW1S
language :
eng
longName :
SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture
mission :
SMAP
otherCitationDetails :
The Calibration and Validation Version 2 Release of the SMAP Level 3 Daily Global Composite Passive Soil Moisture Science Processing Software.
pointOfContact :
National Snow and Ice Data Center
purpose :
The SMAP L3_SM_P algorithm provides daily global composite of soil moistures based on radiometer data on a 36 km grid.
resourceProviderOrganizationName :
National Aeronautics and Space Administration (NASA)
revisionDate :
2023-08-31
shortName :
SPL3SMP
spatialRepresentationType :
grid
status :
onGoing
topicCategory :
geoscientificInformation
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x: 964
igbp_class: 3
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+ " <gmd:sourceCitation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gmx:FileName>SMAP_L3_SM_P_SPS_OutputConfig_L3_SM_P.xml</gmx:FileName>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2024-05-02</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="creation">creation</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>R19240</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " <gmd:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>OutputConfig</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:sourceCitation>\n",
+ " </gmi:LE_Source>\n",
+ " </gmd:source>\n",
+ " <gmd:source xlink:type="simple">\n",
+ " <gmi:LE_Source>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>A configuration file generated automatically within the SMAP data system that specifies all of the conditions required for each individual run of the Radiometer Level 3 SM P Science Processing Software (SPS).</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " <gmd:sourceCitation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gmx:FileName>SMAP_L3_SM_P_SPS_RunConfig_20240502T191336188.xml</gmx:FileName>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2024-05-02</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="creation">creation</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>R19240</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " <gmd:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>RunConfig</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:sourceCitation>\n",
+ " </gmi:LE_Source>\n",
+ " </gmd:source>\n",
+ " </gmd:LI_Lineage>\n",
+ " </gmd:lineage>\n",
+ " </gmd:DQ_DataQuality>\n",
+ " </gmd:dataQualityInfo>\n",
+ " <gmi:acquisitionInformation xlink:type="simple">\n",
+ " <gmi:MI_AcquisitionInformation>\n",
+ " <gmi:platform xlink:type="simple">\n",
+ " <eos:EOS_Platform>\n",
+ " <gmi:citation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>SMAP Handbook</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2014-07-01</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="publication">publication</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>JPL CL#14-2285, JPL 400-1567</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmi:citation>\n",
+ " <gmi:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>SMAP</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>http://smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmi:identifier>\n",
+ " <gmi:description>\n",
+ " <gco:CharacterString>The SMAP observatory houses an L-band radiometer that operates at 1.414 GHz and an L-band radar that operates at 1.225 GHz. The instruments share a rotating reflector antenna with a 6 meter aperture that scans over a 1000 km swath. The bus is a 3 axis stabilized spacecraft that provides momentum compensation for the rotating antenna.</gco:CharacterString>\n",
+ " </gmi:description>\n",
+ " <gmi:instrument xlink:type="simple">\n",
+ " <gmi:MI_Instrument>\n",
+ " <gmi:citation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>SMAP Handbook</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2014-07-01</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="publication">publication</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>JPL CL#14-2285, JPL 400-1567</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmi:citation>\n",
+ " <gmi:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>SMAP SAR</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmi:identifier>\n",
+ " <gmi:type>\n",
+ " <gco:CharacterString>L-Band Synthetic Aperture Radar</gco:CharacterString>\n",
+ " </gmi:type>\n",
+ " <gmi:description>\n",
+ " <gco:CharacterString>The SMAP 1.225 GHz L-Band Radar Instrument</gco:CharacterString>\n",
+ " </gmi:description>\n",
+ " </gmi:MI_Instrument>\n",
+ " </gmi:instrument>\n",
+ " <gmi:instrument xlink:type="simple">\n",
+ " <gmi:MI_Instrument>\n",
+ " <gmi:citation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>SMAP Handbook</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2014-07-01</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="publication">publication</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>JPL CL#14-2285, JPL 400-1567</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmi:citation>\n",
+ " <gmi:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>SMAP RAD</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmi:identifier>\n",
+ " <gmi:type>\n",
+ " <gco:CharacterString>L-Band Radiometer</gco:CharacterString>\n",
+ " </gmi:type>\n",
+ " <gmi:description>\n",
+ " <gco:CharacterString>The SMAP 1.414 GHz L-Band Radiometer</gco:CharacterString>\n",
+ " </gmi:description>\n",
+ " </gmi:MI_Instrument>\n",
+ " </gmi:instrument>\n",
+ " <eos:otherProperty xlink:type="simple">\n",
+ " <gco:Record xlink:type="simple" xsi:type="eos:EOS_AdditionalAttributes_PropertyType">\n",
+ " <eos:EOS_AdditionalAttributes>\n",
+ " <eos:additionalAttribute xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttribute>\n",
+ " <eos:reference xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttributeDescription>\n",
+ " <eos:type>\n",
+ " <eos:EOS_AdditionalAttributeTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/" codeListValue="processingInformation">processingInformation</eos:EOS_AdditionalAttributeTypeCode>\n",
+ " </eos:type>\n",
+ " <eos:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>uuid for stopRevNumber</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>http://smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " </gmd:MD_Identifier>\n",
+ " </eos:identifier>\n",
+ " <eos:name>\n",
+ " <gco:CharacterString>stopRevNumber</gco:CharacterString>\n",
+ " </eos:name>\n",
+ " <eos:dataType>\n",
+ " <eos:EOS_AdditionalAttributeDataTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/Codelists.xml#EOS_AdditionalAttributeDataTypeCode" codeListValue="int">int</eos:EOS_AdditionalAttributeDataTypeCode>\n",
+ " </eos:dataType>\n",
+ " </eos:EOS_AdditionalAttributeDescription>\n",
+ " </eos:reference>\n",
+ " <eos:value>\n",
+ " <gco:CharacterString>11121</gco:CharacterString>\n",
+ " </eos:value>\n",
+ " </eos:EOS_AdditionalAttribute>\n",
+ " </eos:additionalAttribute>\n",
+ " <eos:additionalAttribute xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttribute>\n",
+ " <eos:reference xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttributeDescription>\n",
+ " <eos:type>\n",
+ " <eos:EOS_AdditionalAttributeTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/" codeListValue="processingInformation">processingInformation</eos:EOS_AdditionalAttributeTypeCode>\n",
+ " </eos:type>\n",
+ " <eos:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>uuid for startRevNumber</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>http://smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " </gmd:MD_Identifier>\n",
+ " </eos:identifier>\n",
+ " <eos:name>\n",
+ " <gco:CharacterString>startRevNumber</gco:CharacterString>\n",
+ " </eos:name>\n",
+ " <eos:dataType>\n",
+ " <eos:EOS_AdditionalAttributeDataTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/Codelists.xml#EOS_AdditionalAttributeDataTypeCode" codeListValue="int">int</eos:EOS_AdditionalAttributeDataTypeCode>\n",
+ " </eos:dataType>\n",
+ " </eos:EOS_AdditionalAttributeDescription>\n",
+ " </eos:reference>\n",
+ " <eos:value>\n",
+ " <gco:CharacterString>11107</gco:CharacterString>\n",
+ " </eos:value>\n",
+ " </eos:EOS_AdditionalAttribute>\n",
+ " </eos:additionalAttribute>\n",
+ " <eos:additionalAttribute xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttribute>\n",
+ " <eos:reference xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttributeDescription>\n",
+ " <eos:type>\n",
+ " <eos:EOS_AdditionalAttributeTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/" codeListValue="processingInformation">processingInformation</eos:EOS_AdditionalAttributeTypeCode>\n",
+ " </eos:type>\n",
+ " <eos:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>uuid for AntennaRotationRate</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>http://smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " </gmd:MD_Identifier>\n",
+ " </eos:identifier>\n",
+ " <eos:name>\n",
+ " <gco:CharacterString>AntennaRotationRate</gco:CharacterString>\n",
+ " </eos:name>\n",
+ " <eos:dataType>\n",
+ " <eos:EOS_AdditionalAttributeDataTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/Codelists.xml#EOS_AdditionalAttributeDataTypeCode" codeListValue="float">float</eos:EOS_AdditionalAttributeDataTypeCode>\n",
+ " </eos:dataType>\n",
+ " </eos:EOS_AdditionalAttributeDescription>\n",
+ " </eos:reference>\n",
+ " <eos:value>\n",
+ " <gco:CharacterString>14.6</gco:CharacterString>\n",
+ " </eos:value>\n",
+ " </eos:EOS_AdditionalAttribute>\n",
+ " </eos:additionalAttribute>\n",
+ " </eos:EOS_AdditionalAttributes>\n",
+ " </gco:Record>\n",
+ " </eos:otherProperty>\n",
+ " </eos:EOS_Platform>\n",
+ " </gmi:platform>\n",
+ " </gmi:MI_AcquisitionInformation>\n",
+ " </gmi:acquisitionInformation>\n",
+ " </gmi:MI_Metadata>\n",
+ " </gmd:has>\n",
+ " </gmd:DS_DataSet>\n",
+ " </gmd:composedOf>\n",
+ "\n",
+ " <gmd:seriesMetadata gco:nilReason="missing" xlink:type="simple"/>\n",
+ "\n",
+ "</gmd:DS_Series>\n",
+ "
iso_19139_dataset_xml_md5 :
8575fcbb24fb9331cbb74df74abd5b15
iso_19139_series_xml :
<?xml version="1.0" encoding="UTF-8"?>\n",
+ "<gmd:DS_Series xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"\n",
+ " xsi:schemaLocation="http://www.isotc211.org/2005/gmi http://cdn.earthdata.nasa.gov/iso/schema/1.0/ISO19115-2_EOS.xsd"\n",
+ " xmlns:gco="http://www.isotc211.org/2005/gco"\n",
+ " xmlns:gmd="http://www.isotc211.org/2005/gmd"\n",
+ " xmlns:xlink="http://www.w3.org/1999/xlink"\n",
+ " xmlns:gml="http://www.opengis.net/gml/3.2"\n",
+ " xmlns:gsr="http://www.isotc211.org/2005/gsr"\n",
+ " xmlns:gss="http://www.isotc211.org/2005/gss"\n",
+ " xmlns:gts="http://www.isotc211.org/2005/gts"\n",
+ " xmlns:gmi="http://www.isotc211.org/2005/gmi"\n",
+ " xmlns:gmx="http://www.isotc211.org/2005/gmx">\n",
+ " <gmd:composedOf gco:nilReason="inapplicable"/>\n",
+ " <gmd:seriesMetadata>\n",
+ " <gmi:MI_Metadata>\n",
+ " <!-- With reference to file name here, do we need to use MD_Identification/CI_Citation to reference the file. -->\n",
+ " <gmd:fileIdentifier>\n",
+ " <gco:CharacterString>L3_SM_P</gco:CharacterString>\n",
+ " <!-- Assume that the file Identifier for series metadata would be the identifier that denotes that a file belongs to this series. -->\n",
+ " </gmd:fileIdentifier>\n",
+ " <gmd:language>\n",
+ " <gco:CharacterString>eng</gco:CharacterString>\n",
+ " </gmd:language>\n",
+ " <gmd:characterSet>\n",
+ " <gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode" codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>\n",
+ " </gmd:characterSet>\n",
+ " <gmd:hierarchyLevel>\n",
+ " <gmd:MD_ScopeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ScopeCode" codeListValue="series">series</gmd:MD_ScopeCode>\n",
+ " </gmd:hierarchyLevel>\n",
+ " <gmd:contact>\n",
+ " <gmd:CI_ResponsibleParty>\n",
+ " <gmd:organisationName>\n",
+ " <gco:CharacterString>NSIDC DAAC > National Snow and Ice Data Center DAAC</gco:CharacterString>\n",
+ " </gmd:organisationName>\n",
+ " <gmd:contactInfo>\n",
+ " <gmd:CI_Contact>\n",
+ " <gmd:address>\n",
+ " <gmd:CI_Address>\n",
+ " <gmd:electronicMailAddress>\n",
+ " <gco:CharacterString>nsidc@nsidc.org</gco:CharacterString>\n",
+ " </gmd:electronicMailAddress>\n",
+ " </gmd:CI_Address>\n",
+ " </gmd:address>\n",
+ " <gmd:onlineResource>\n",
+ " <gmd:CI_OnlineResource>\n",
+ " <gmd:linkage>\n",
+ " <gmd:URL>http://nsidc.org/daac/</gmd:URL>\n",
+ " </gmd:linkage>\n",
+ " </gmd:CI_OnlineResource>\n",
+ " </gmd:onlineResource>\n",
+ " </gmd:CI_Contact>\n",
+ " </gmd:contactInfo>\n",
+ " <gmd:role>\n",
+ " <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode" codeListValue="pointOfContact">pointOfContact</gmd:CI_RoleCode>\n",
+ " </gmd:role>\n",
+ " </gmd:CI_ResponsibleParty>\n",
+ " </gmd:contact>\n",
+ " <gmd:dateStamp>\n",
+ " <gco:Date>2019-04-15</gco:Date>\n",
+ " </gmd:dateStamp>\n",
+ " <gmd:metadataStandardName>\n",
+ " <gco:CharacterString>ISO 19115-2 Geographic information - Metadata - Part 2: Extensions for imagery and gridded data</gco:CharacterString>\n",
+ " </gmd:metadataStandardName>\n",
+ " <gmd:metadataStandardVersion>\n",
+ " <gco:CharacterString>ISO 19115-2:2009-02-15</gco:CharacterString>\n",
+ " </gmd:metadataStandardVersion>\n",
+ " <gmd:identificationInfo>\n",
+ " <gmd:MD_DataIdentification>\n",
+ " <gmd:citation>\n",
+ " <!-- If file name reference in MI_Metadata is sufficient, can use this CI_Citation to reference Product Specification Document. -->\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <!-- This field provides the product Long Name required by the ECS. -->\n",
+ " <gco:CharacterString>SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date>\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <!-- This field provides the date of a particular release or build. For the ECS, this is the RevisionDate, a required field. -->\n",
+ " <gco:Date>2023-08-31</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="revision">revision</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <!-- Specifies the SMAP Release ID -->\n",
+ " <gco:CharacterString>R19</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " <gmd:identifier>\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <!-- This field provides the product Short Name. This is the ECS Short Name rather than the SMAP Short Name. -->\n",
+ " <gco:CharacterString>SPL3SMP</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <!-- This field is intended to provide a namespace identifier for SMAP data product Short Names. Team should devise an identifier. -->\n",
+ " <gco:CharacterString>smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>The ECS Short Name</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " <gmd:identifier>\n",
+ " <gmd:MD_Identifier> <!-- This field provides the ECS Version ID. -->\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>009</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace> <!-- This field is intended to provide the namespace for ECS Version IDs for the SMAP mission. Team should devise an identifier.-->\n",
+ " <gco:CharacterString>gov.nasa.esdis</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>The ECS Version ID</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " <gmd:identifier>\n",
+ " <gmd:MD_Identifier> <!-- This field provides the Digital Object Identifier (DOI). -->\n",
+ " <gmd:code>\n",
+ " <gmx:Anchor xlink:actuate="onRequest" xlink:href="http://dx.doi.org/10.5067/4XXOGX0OOW1S" >doi:10.5067/4XXOGX0OOW1S</gmx:Anchor>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace> <!-- This field is intended to provide a namespace identifier for DOIs. What would be best specification?-->\n",
+ " <gco:CharacterString>gov.nasa.esdis</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>A Digital Object Identifier (DOI)</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " <gmd:citedResponsibleParty>\n",
+ " <gmd:CI_ResponsibleParty>\n",
+ " <gmd:organisationName>\n",
+ " <gco:CharacterString>National Aeronautics and Space Administration (NASA)</gco:CharacterString>\n",
+ " </gmd:organisationName>\n",
+ " <gmd:role>\n",
+ " <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode" codeListValue="resourceProvider">resourceProvider</gmd:CI_RoleCode>\n",
+ " </gmd:role>\n",
+ " </gmd:CI_ResponsibleParty>\n",
+ " </gmd:citedResponsibleParty>\n",
+ " <gmd:citedResponsibleParty>\n",
+ " <gmd:CI_ResponsibleParty>\n",
+ " <gmd:organisationName>\n",
+ " <!-- This field provides the ProcessingCenter, a required field for the ECS. The ECS will need to check the roleCode to ensure they're viewing the correct field.-->\n",
+ " <gco:CharacterString>Jet Propulsion Laboratory</gco:CharacterString>\n",
+ " </gmd:organisationName>\n",
+ " <gmd:role>\n",
+ " <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode" codeListValue="originator">originator</gmd:CI_RoleCode>\n",
+ " </gmd:role>\n",
+ " </gmd:CI_ResponsibleParty>\n",
+ " </gmd:citedResponsibleParty>\n",
+ " <gmd:presentationForm>\n",
+ " <gmd:CI_PresentationFormCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_PresentationFormCode" codeListValue="documentDigital">documentDigital</gmd:CI_PresentationFormCode>\n",
+ " </gmd:presentationForm>\n",
+ " <gmd:otherCitationDetails>\n",
+ " <gco:CharacterString>The Calibration and Validation Version 2 Release of the SMAP Level 3 Daily Global Composite Passive Soil Moisture Science Processing Software.</gco:CharacterString>\n",
+ " </gmd:otherCitationDetails>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:citation>\n",
+ " <gmd:abstract>\n",
+ " <!-- This field contains the CollectionDescription required by the ECS. -->\n",
+ " <gco:CharacterString>Daily global composite of up-to 30 half-orbit L2_SM_P soil moisture estimates based on radiometer brightness temperature measurements acquired by the SMAP radiometer during ascending and descending half-orbits at approximately 6 PM and 6 AM local solar time.</gco:CharacterString>\n",
+ " </gmd:abstract>\n",
+ " <gmd:purpose>\n",
+ " <gco:CharacterString>The SMAP L3_SM_P algorithm provides daily global composite of soil moistures based on radiometer data on a 36 km grid.</gco:CharacterString>\n",
+ " </gmd:purpose>\n",
+ " <gmd:credit>\n",
+ " <!-- This field can name individuals or organizations for credit. For now, it specifies NASA. -->\n",
+ " <gco:CharacterString>The software that generates the Level 3 Soil Moisture Passive product and the data system that automates its production were designed and implemented \n",
+ " at the Jet Propulsion Laboratory, California Institute of Technology in Pasadena, California.</gco:CharacterString>\n",
+ " </gmd:credit>\n",
+ " <gmd:status>\n",
+ " <gmd:MD_ProgressCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ProgressCode" codeListValue="onGoing">onGoing</gmd:MD_ProgressCode>\n",
+ " </gmd:status>\n",
+ " <gmd:pointOfContact>\n",
+ " <gmd:CI_ResponsibleParty>\n",
+ " <gmd:organisationName>\n",
+ " <!-- This field provides the ArchiveCenter, a required entry for the ECS. -->\n",
+ " <gco:CharacterString>National Snow and Ice Data Center</gco:CharacterString>\n",
+ " </gmd:organisationName>\n",
+ " <gmd:role>\n",
+ " <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode" codeListValue="distributor">distributor</gmd:CI_RoleCode>\n",
+ " </gmd:role>\n",
+ " </gmd:CI_ResponsibleParty>\n",
+ " </gmd:pointOfContact>\n",
+ " <gmd:resourceMaintenance>\n",
+ " <gmd:MD_MaintenanceInformation>\n",
+ " <gmd:maintenanceAndUpdateFrequency>\n",
+ " <gmd:MD_MaintenanceFrequencyCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_MaintenanceFrequencyCode" codeListValue="asNeeded">asNeeded</gmd:MD_MaintenanceFrequencyCode>\n",
+ " </gmd:maintenanceAndUpdateFrequency>\n",
+ " <gmd:dateOfNextUpdate>\n",
+ " <gco:Date>2017-04-01</gco:Date>\n",
+ " </gmd:dateOfNextUpdate>\n",
+ " <gmd:updateScope>\n",
+ " <gmd:MD_ScopeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ScopeCode" codeListValue="series">series</gmd:MD_ScopeCode>\n",
+ " </gmd:updateScope>\n",
+ " </gmd:MD_MaintenanceInformation>\n",
+ " </gmd:resourceMaintenance>\n",
+ " <gmd:resourceFormat>\n",
+ " <gmd:MD_Format>\n",
+ " <gmd:name>\n",
+ " <gco:CharacterString>HDF5</gco:CharacterString>\n",
+ " </gmd:name>\n",
+ " <gmd:version>\n",
+ " <gco:CharacterString>1.8.13</gco:CharacterString>\n",
+ " </gmd:version>\n",
+ " </gmd:MD_Format>\n",
+ " </gmd:resourceFormat>\n",
+ " <gmd:descriptiveKeywords>\n",
+ " <gmd:MD_Keywords>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > LAND SURFACE > SOILS > SOIL MOISTURE/WATER CONTENT</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > CLIMATE INDICATORS > LAND SURFACE/AGRICULTURE INDICATORS > SOIL MOISTURE</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > SPECTRAL/ENGINEERING > MICROWAVE > BRIGHTNESS TEMPERATURE</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SNOW/ICE > FREEZE/THAW</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > CRYOSPHERE > SNOW/ICE > FREEZE/THAW</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > BIOSPHERE > VEGETATION > PLANT CHARACTERISTICS > VEGETATION WATER CONTENT</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > LAND SURFACE > SURFACE RADIATIVE PROPERTIES > ALBEDO</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > SURFACE ROUGHNESS</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > LAND SURFACE > SURFACE RADIATIVE PROPERTIES > ALBEDO</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > TERRESTRIAL HYDROSPHERE> SNOW/ICE > FREEZE/THAW</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:type>\n",
+ " <gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode" codeListValue="theme">theme</gmd:MD_KeywordTypeCode>\n",
+ " </gmd:type>\n",
+ " <gmd:thesaurusName>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>NASA/GCMD Earth Science Keywords</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date gco:nilReason="unknown"/>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:thesaurusName>\n",
+ " </gmd:MD_Keywords>\n",
+ " </gmd:descriptiveKeywords>\n",
+ " <gmd:descriptiveKeywords>\n",
+ " <gmd:MD_Keywords>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>Earth Remote Sensing Instruments > Passive Remote Sensing > Spectrometers/Radiometers > Imaging Spectrometers/Radiometers > SMAP L-BAND RADIOMETER > SMAP L-Band Radiometer</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:type>\n",
+ " <gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode" codeListValue="theme">theme</gmd:MD_KeywordTypeCode>\n",
+ " </gmd:type>\n",
+ " <gmd:thesaurusName>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>NASA/GCMD Earth Science Keywords</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date gco:nilReason="unknown"/>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:thesaurusName>\n",
+ " </gmd:MD_Keywords>\n",
+ " </gmd:descriptiveKeywords>\n",
+ " <gmd:descriptiveKeywords>\n",
+ " <gmd:MD_Keywords>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>Earth Observation Satellites > NASA Decadal Survey > SMAP > Soil Moisture Active and Passive Observatory</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:type>\n",
+ " <gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode" codeListValue="theme">theme</gmd:MD_KeywordTypeCode>\n",
+ " </gmd:type>\n",
+ " <gmd:thesaurusName>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>NASA/GCMD Earth Science Keywords</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date gco:nilReason="unknown"/>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:thesaurusName>\n",
+ " </gmd:MD_Keywords>\n",
+ " </gmd:descriptiveKeywords>\n",
+ " <gmd:descriptiveKeywords>\n",
+ " <gmd:MD_Keywords>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>GEOGRAPHIC REGION > GLOBAL</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:type>\n",
+ " <gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode" codeListValue="theme">theme</gmd:MD_KeywordTypeCode>\n",
+ " </gmd:type>\n",
+ " <gmd:thesaurusName>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>NASA/GCMD Earth Science Keywords</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date gco:nilReason="unknown"/>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:thesaurusName>\n",
+ " </gmd:MD_Keywords>\n",
+ " </gmd:descriptiveKeywords> \n",
+ " <gmd:aggregationInfo>\n",
+ " <gmd:MD_AggregateInformation>\n",
+ " <gmd:aggregateDataSetIdentifier>\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>SMAP</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:aggregateDataSetIdentifier>\n",
+ " <gmd:associationType>\n",
+ " <gmd:DS_AssociationTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#DS_AssociationTypeCode" codeListValue="largerWorkCitation">largerWorkCitation</gmd:DS_AssociationTypeCode>\n",
+ " </gmd:associationType>\n",
+ " <gmd:initiativeType>\n",
+ " <gmd:DS_InitiativeTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#DS_AssociationTypeCode" codeListValue="mission">mission</gmd:DS_InitiativeTypeCode>\n",
+ " </gmd:initiativeType>\n",
+ " </gmd:MD_AggregateInformation>\n",
+ " </gmd:aggregationInfo>\n",
+ " <gmd:spatialRepresentationType>\n",
+ " <gmd:MD_SpatialRepresentationTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_SpatialRepresentationTypeCode" codeListValue="grid">grid</gmd:MD_SpatialRepresentationTypeCode>\n",
+ " </gmd:spatialRepresentationType>\n",
+ " <gmd:spatialResolution>\n",
+ " <gmd:MD_Resolution>\n",
+ " <gmd:distance>\n",
+ " <gco:Distance uom="km">36</gco:Distance>\n",
+ " </gmd:distance>\n",
+ " </gmd:MD_Resolution>\n",
+ " </gmd:spatialResolution>\n",
+ " <gmd:language>\n",
+ " <gco:CharacterString>eng</gco:CharacterString>\n",
+ " </gmd:language>\n",
+ " <gmd:characterSet>\n",
+ " <gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode" codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>\n",
+ " </gmd:characterSet>\n",
+ " <gmd:topicCategory>\n",
+ " <gmd:MD_TopicCategoryCode>geoscientificInformation</gmd:MD_TopicCategoryCode>\n",
+ " </gmd:topicCategory>\n",
+ " <gmd:environmentDescription>\n",
+ " <gco:CharacterString>Data product generated by the SMAP mission in HDF5 format with metadata that conforms to the ISO 19115 model.</gco:CharacterString>\n",
+ " </gmd:environmentDescription>\n",
+ " <gmd:extent>\n",
+ " <gmd:EX_Extent>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>Soil moisture is\n",
+ "\t\t\t\tretrieved over land targets on the\n",
+ "\t\t\t\tdescending (AM) and ascending (PM) SMAP half-orbits, \n",
+ " while the SMAP instruments are operating in the nominal mode. Retrievals are performed but flagged as questionable \n",
+ " over urban areas, mountainous areas with high elevation variability, and areas with high ( > 5 kg/m**2) vegetation \n",
+ " water content; for retrievals using the high-resolution radar, cells in the nadir region are also flagged.\n",
+ " Retrievals are inhibited for permanent snow/ice, frozen ground, and excessive static or transient open water in the cell,\n",
+ " and for excessive RFI in the sensor data.</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " <gmd:geographicElement>\n",
+ " <!-- This defines the bounding box for all SMAP Level 3 Passive Soil Moisture data products. -->\n",
+ " <gmd:EX_GeographicBoundingBox>\n",
+ " <gmd:extentTypeCode>\n",
+ " <gco:Boolean>1</gco:Boolean>\n",
+ " </gmd:extentTypeCode>\n",
+ " <gmd:westBoundLongitude>\n",
+ " <gco:Decimal>-180.00</gco:Decimal>\n",
+ " </gmd:westBoundLongitude>\n",
+ " <gmd:eastBoundLongitude>\n",
+ " <gco:Decimal>180.00</gco:Decimal>\n",
+ " </gmd:eastBoundLongitude>\n",
+ " <gmd:southBoundLatitude>\n",
+ " <gco:Decimal>-85.0445</gco:Decimal>\n",
+ " </gmd:southBoundLatitude>\n",
+ " <gmd:northBoundLatitude>\n",
+ " <gco:Decimal>85.0445</gco:Decimal>\n",
+ " </gmd:northBoundLatitude>\n",
+ " </gmd:EX_GeographicBoundingBox>\n",
+ " </gmd:geographicElement>\n",
+ " <gmd:temporalElement>\n",
+ " <gmd:EX_TemporalExtent>\n",
+ " <!-- Mimics use in GHRSST. See no evidence of conformance to standard -->\n",
+ " <gmd:extent>\n",
+ " <gml:TimePeriod gml:id="swathTemporalExtent">\n",
+ " <!-- This defines the time period covered by all SMAP Level 3 Passive Soil Moisture data products. \n",
+ " ECS indicates that they will automatically extend the final time based on receipt of data products. -->\n",
+ " <gml:beginPosition>2015-03-31T00:00:00.000Z</gml:beginPosition>\n",
+ " <gml:endPosition>2020-12-31T00:00:00.000Z</gml:endPosition>\n",
+ " </gml:TimePeriod>\n",
+ " </gmd:extent>\n",
+ " </gmd:EX_TemporalExtent>\n",
+ " </gmd:temporalElement>\n",
+ " </gmd:EX_Extent>\n",
+ " </gmd:extent>\n",
+ " </gmd:MD_DataIdentification>\n",
+ " </gmd:identificationInfo>\n",
+ " <gmd:identificationInfo>\n",
+ " <!-- This field is used to reference the Product Specification Document. If and when the model moves to ISO 19115-1, move this reference to additionalDocumentation. -->\n",
+ " <gmd:MD_DataIdentification>\n",
+ " <gmd:citation>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>Product Specification Document for the SMAP Level 3 Passive Soil Moisture Product (L3_SM_P)</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date>\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2013-02-08</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="publication">publication</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>1.0</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " <gmd:identifier>\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>L3_SM_P</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <!-- This field is intended to provide a namespace identifier for SMAP data product Short Names. Team should devise an identifier. -->\n",
+ " <gco:CharacterString>smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>Short name used by the Soil Moisture Active Passive (SMAP) mission to identify the Level 3 Passive Soil Moisture product.</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " <gmd:presentationForm>\n",
+ " <gmd:CI_PresentationFormCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_PresentationFormCode" codeListValue="documentDigital">documentDigital</gmd:CI_PresentationFormCode>\n",
+ " </gmd:presentationForm>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:citation>\n",
+ " <gmd:abstract>\n",
+ " <gco:CharacterString>The Product Specification Document that fully describes the content and format of this data product.</gco:CharacterString>\n",
+ " </gmd:abstract>\n",
+ " <gmd:language>\n",
+ " <gco:CharacterString>eng</gco:CharacterString>\n",
+ " </gmd:language>\n",
+ " <gmd:characterSet>\n",
+ " <gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode" codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>\n",
+ " </gmd:characterSet>\n",
+ " </gmd:MD_DataIdentification>\n",
+ " </gmd:identificationInfo>\n",
+ " </gmi:MI_Metadata>\n",
+ " </gmd:seriesMetadata>\n",
+ "</gmd:DS_Series>\n",
+ "
The column index of the 36 km EASE grid cell that contains the associated data.
valid_max :
963
valid_min :
0
[391384 values with dtype=float32]
EASE_row_index
(y, x)
float32
...
long_name :
The row index of the 36 km EASE grid cell that contains the associated data.
valid_max :
405
valid_min :
0
[391384 values with dtype=float32]
albedo
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_dca
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scah
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-H within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scav
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-V within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
boresight_incidence
(y, x)
float32
...
long_name :
Representative angle between the antenna boresight vector and the normal to the Earth's surface for all footprints within the cell.
units :
degrees
valid_max :
90.0
valid_min :
0.0
[391384 values with dtype=float32]
bulk_density
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated bulk_density within the 36 km grid cell.
valid_max :
2.65
valid_min :
0.0
[391384 values with dtype=float32]
clay_fraction
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated clay fraction within the 36 km grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
freeze_thaw_fraction
(y, x)
float32
...
long_name :
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
grid_surface_status
(y, x)
float32
...
long_name :
Indicates if the grid point lies on land (0) or water (1).
valid_max :
1
valid_min :
0
[391384 values with dtype=float32]
landcover_class
(y, x, igbp_class)
float32
...
long_name :
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
[1174152 values with dtype=float32]
landcover_class_fraction
(y, x, igbp_class)
float32
...
long_name :
The fraction of the grid cell that contains the most common land cover in that area based on the IGBP landcover map.
valid_max :
1.0
valid_min :
0.0
[1174152 values with dtype=float32]
latitude
(y, x)
float32
...
long_name :
Latitude of the center of the Earth based grid cell.
units :
degrees_north
[391384 values with dtype=float32]
latitude_centroid
(y, x)
float32
...
long_name :
Weighted average of the latitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
longitude
(y, x)
float32
...
long_name :
Longitude of the center of the Earth based grid cell.
units :
degrees_east
[391384 values with dtype=float32]
longitude_centroid
(y, x)
float32
...
long_name :
Weighted average of the longitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
radar_water_body_fraction
(y, x)
float32
...
long_name :
The fraction of the area of the 36 km grid cell that is covered by water based on the radar detection algorithm.
Bit flags that represent the quality of the vertical polarization brightness temperature within each grid cell
[391384 values with dtype=float32]
tb_time_seconds
(y, x)
float64
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
units :
seconds
valid_max :
940000000.0
valid_min :
-999999.9
[391384 values with dtype=float64]
tb_time_utc
(y, x)
|S24
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in UTC.
[391384 values with dtype=|S24]
tb_v_corrected
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell adjusted for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
tb_v_uncorrected
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell before adjustment for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
vegetation_opacity
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_dca
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scah
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-H retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scav
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-V retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_water_content
(y, x)
float32
...
long_name :
Representative measure of water in the vegetation within the 36 km grid cell.
The column index of the 36 km EASE grid cell that contains the associated data.
valid_max :
963
valid_min :
0
[391384 values with dtype=float32]
EASE_row_index_pm
(y, x)
float32
...
long_name :
The row index of the 36 km EASE grid cell that contains the associated data.
valid_max :
405
valid_min :
0
[391384 values with dtype=float32]
albedo_dca_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scah_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-H retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scav_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-V retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
boresight_incidence_pm
(y, x)
float32
...
long_name :
Representative angle between the antenna boresight vector and the normal to the Earth's surface for all footprints within the cell.
units :
degrees
valid_max :
90.0
valid_min :
0.0
[391384 values with dtype=float32]
bulk_density_pm
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated bulk density within the 36 km grid cell.
valid_max :
2.65
valid_min :
0.0
[391384 values with dtype=float32]
clay_fraction_pm
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated clay fraction within the 36 km grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
freeze_thaw_fraction_pm
(y, x)
float32
...
long_name :
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
grid_surface_status_pm
(y, x)
float32
...
long_name :
Indicates if the grid point lies on land (0) or water (1).
valid_max :
1
valid_min :
0
[391384 values with dtype=float32]
landcover_class_fraction_pm
(y, x, igbp_class)
float32
...
long_name :
The fraction of the grid cell that contains the most common land cover in that area based on the IGBP landcover map.
valid_max :
1.0
valid_min :
0.0
[1174152 values with dtype=float32]
landcover_class_pm
(y, x, igbp_class)
float32
...
long_name :
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
[1174152 values with dtype=float32]
latitude_centroid_pm
(y, x)
float32
...
long_name :
Weighted average of the latitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
latitude_pm
(y, x)
float32
...
long_name :
Latitude of the center of the Earth based grid cell.
units :
degrees_north
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
longitude_centroid_pm
(y, x)
float32
...
long_name :
Weighted average of the longitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
longitude_pm
(y, x)
float32
...
long_name :
Longitude of the center of the Earth based grid cell.
units :
degrees_east
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
radar_water_body_fraction_pm
(y, x)
float32
...
long_name :
The fraction of the area of the 36 km grid cell that is covered by water based on the radar detection algorithm.
Bit flags that represent the quality of the vertical polarization brightness temperature within each grid cell
[391384 values with dtype=float32]
tb_time_seconds_pm
(y, x)
float64
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
units :
seconds
valid_max :
940000000.0
valid_min :
-999999.9
[391384 values with dtype=float64]
tb_time_utc_pm
(y, x)
|S24
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in UTC.
[391384 values with dtype=|S24]
tb_v_corrected_pm
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell adjusted for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
tb_v_uncorrected_pm
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell before adjustment for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
vegetation_opacity_dca_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in DCA retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in DCA retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scah_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in SCA-H retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scav_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in SCA-V retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_water_content_pm
(y, x)
float32
...
long_name :
Representative measure of water in the vegetation within the 36 km grid cell.
units :
kg/m**2
valid_max :
20.0
valid_min :
0.0
[391384 values with dtype=float32]
y: 406
x: 964
igbp_class: 3
EASE_column_index
(y, x)
float32
...
long_name :
The column index of the 36 km EASE grid cell that contains the associated data.
valid_max :
963
valid_min :
0
[391384 values with dtype=float32]
EASE_row_index
(y, x)
float32
...
long_name :
The row index of the 36 km EASE grid cell that contains the associated data.
valid_max :
405
valid_min :
0
[391384 values with dtype=float32]
albedo
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_dca
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scah
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-H within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scav
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-V within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
boresight_incidence
(y, x)
float32
...
long_name :
Representative angle between the antenna boresight vector and the normal to the Earth's surface for all footprints within the cell.
units :
degrees
valid_max :
90.0
valid_min :
0.0
[391384 values with dtype=float32]
bulk_density
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated bulk_density within the 36 km grid cell.
valid_max :
2.65
valid_min :
0.0
[391384 values with dtype=float32]
clay_fraction
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated clay fraction within the 36 km grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
freeze_thaw_fraction
(y, x)
float32
...
long_name :
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
grid_surface_status
(y, x)
float32
...
long_name :
Indicates if the grid point lies on land (0) or water (1).
valid_max :
1
valid_min :
0
[391384 values with dtype=float32]
landcover_class
(y, x, igbp_class)
float32
...
long_name :
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
[1174152 values with dtype=float32]
landcover_class_fraction
(y, x, igbp_class)
float32
...
long_name :
The fraction of the grid cell that contains the most common land cover in that area based on the IGBP landcover map.
valid_max :
1.0
valid_min :
0.0
[1174152 values with dtype=float32]
latitude
(y, x)
float32
...
long_name :
Latitude of the center of the Earth based grid cell.
units :
degrees_north
[391384 values with dtype=float32]
latitude_centroid
(y, x)
float32
...
long_name :
Weighted average of the latitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
longitude
(y, x)
float32
...
long_name :
Longitude of the center of the Earth based grid cell.
units :
degrees_east
[391384 values with dtype=float32]
longitude_centroid
(y, x)
float32
...
long_name :
Weighted average of the longitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
radar_water_body_fraction
(y, x)
float32
...
long_name :
The fraction of the area of the 36 km grid cell that is covered by water based on the radar detection algorithm.
Bit flags that represent the quality of the vertical polarization brightness temperature within each grid cell
[391384 values with dtype=float32]
tb_time_seconds
(y, x)
float64
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
units :
seconds
valid_max :
940000000.0
valid_min :
-999999.9
[391384 values with dtype=float64]
tb_time_utc
(y, x)
|S24
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in UTC.
[391384 values with dtype=|S24]
tb_v_corrected
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell adjusted for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
tb_v_uncorrected
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell before adjustment for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
vegetation_opacity
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_dca
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scah
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-H retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scav
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-V retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_water_content
(y, x)
float32
...
long_name :
Representative measure of water in the vegetation within the 36 km grid cell.
units :
kg/m**2
valid_max :
20.0
valid_min :
0.0
[391384 values with dtype=float32]
EASE_column_index_pm
(y, x)
float32
...
long_name :
The column index of the 36 km EASE grid cell that contains the associated data.
valid_max :
963
valid_min :
0
[391384 values with dtype=float32]
EASE_row_index_pm
(y, x)
float32
...
long_name :
The row index of the 36 km EASE grid cell that contains the associated data.
valid_max :
405
valid_min :
0
[391384 values with dtype=float32]
albedo_dca_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scah_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-H retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scav_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-V retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
boresight_incidence_pm
(y, x)
float32
...
long_name :
Representative angle between the antenna boresight vector and the normal to the Earth's surface for all footprints within the cell.
units :
degrees
valid_max :
90.0
valid_min :
0.0
[391384 values with dtype=float32]
bulk_density_pm
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated bulk density within the 36 km grid cell.
valid_max :
2.65
valid_min :
0.0
[391384 values with dtype=float32]
clay_fraction_pm
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated clay fraction within the 36 km grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
freeze_thaw_fraction_pm
(y, x)
float32
...
long_name :
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
grid_surface_status_pm
(y, x)
float32
...
long_name :
Indicates if the grid point lies on land (0) or water (1).
valid_max :
1
valid_min :
0
[391384 values with dtype=float32]
landcover_class_fraction_pm
(y, x, igbp_class)
float32
...
long_name :
The fraction of the grid cell that contains the most common land cover in that area based on the IGBP landcover map.
valid_max :
1.0
valid_min :
0.0
[1174152 values with dtype=float32]
landcover_class_pm
(y, x, igbp_class)
float32
...
long_name :
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
[1174152 values with dtype=float32]
latitude_centroid_pm
(y, x)
float32
...
long_name :
Weighted average of the latitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
latitude_pm
(y, x)
float32
...
long_name :
Latitude of the center of the Earth based grid cell.
units :
degrees_north
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
longitude_centroid_pm
(y, x)
float32
...
long_name :
Weighted average of the longitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
longitude_pm
(y, x)
float32
...
long_name :
Longitude of the center of the Earth based grid cell.
units :
degrees_east
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
radar_water_body_fraction_pm
(y, x)
float32
...
long_name :
The fraction of the area of the 36 km grid cell that is covered by water based on the radar detection algorithm.
Bit flags that represent the quality of the vertical polarization brightness temperature within each grid cell
[391384 values with dtype=float32]
tb_time_seconds_pm
(y, x)
float64
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
units :
seconds
valid_max :
940000000.0
valid_min :
-999999.9
[391384 values with dtype=float64]
tb_time_utc_pm
(y, x)
|S24
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in UTC.
[391384 values with dtype=|S24]
tb_v_corrected_pm
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell adjusted for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
tb_v_uncorrected_pm
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell before adjustment for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
vegetation_opacity_dca_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in DCA retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in DCA retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scah_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in SCA-H retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scav_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in SCA-V retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_water_content_pm
(y, x)
float32
...
long_name :
Representative measure of water in the vegetation within the 36 km grid cell.
The SMAP observatory houses an L-band radiometer that operates at 1.414 GHz and an L-band radar that operates at 1.225 GHz. The instruments share a rotating reflector antenna with a 6 meter aperture that scans over a 1000 km swath. The bus is a 3 axis stabilized spacecraft that provides momentum compensation for the rotating antenna.
Percentage of EASE2 grid cells that lack soil moisture retrieval values relative to the total number of grid cells where soil moisture retrieval was attempted.
Daily global composite of up-to 15 half-orbit L2_SM_P soil moisture estimates based on radiometer brightness temperature measurements acquired by the SMAP radiometer during descending half-orbits at approximately 6 AM local solar time.
characterSet :
utf8
creationDate :
2024-05-02
credit :
The software that generates the Level 3 SM_P product and the data system that automates its production were designed and implemented at the Jet Propulsion Laboratory, California Institute of Technology in Pasadena, California.
fileName :
SMAP_L3_SM_P_20170301_R19240_001.h5
format :
HDF5
formatVersion :
1.8.13
language :
eng
maintenanceAndUpdateFrequency :
asNeeded
maintenanceDate :
2016-05-01
originatorOrganizationName :
Jet Propulsion Laboratory
otherCitationDetails :
The Calibration and Validation Version 2 Release of the SMAP Level 3 Daily Global Composite Passive Soil Moisture Science Processing Software.
purpose :
The SMAP L3_SM_P effort provides soil moistures based on radiometer data on a 36 km grid.
Soil moisture is retrieved over land targets on the descending (AM) SMAP half-orbits when the SMAP spacecraft is travelling from North to South, while the SMAP instruments are operating in the nominal mode. The L3_SM_P product represents soil moisture retrieved over the entre UTC day. Retrievals are performed but flagged as questionable over urban areas, mountainous areas with high elevation variability, and areas with high ( > 5 kg/m**2) vegetation water content; for retrievals using the high-resolution radar, cells in the nadir region are also flagged. Retrievals are inhibited for permanent snow/ice, frozen ground, and excessive static or transient open water in the cell, and for excessive RFI in the sensor data.
The Equal-Area Scalable Earth Grid (EASE-Grid 2.0) is used for gridding satellite data sets. The EASE-Grid 2.0 is defined on the WGS84 ellipsoid to allow users to import data into standard GIS software formats such as GeoTIFF without reprojection.
A configuration file that specifies the complete set of elements within the input Level 2 SM_P Product that the Radiometer Level 3_SM_P Science Processing Software (SPS) needs in order to function.
Passive soil moisture estimates onto a 36-km global Earth-fixed grid, based on radiometer measurements acquired when the SMAP spacecraft is travelling from North to South at approximately 6:00 AM local time.
A configuration file that specifies the source of the values for each of the data elements that comprise the metadata in the output Radiometer Level 3_SM_P product.
A configuration file generated automatically within the SMAP data system that specifies all of the conditions required for each individual run of the Radiometer Level 3 SM P Science Processing Software (SPS).
Algorithm Theoretical Basis Document: SMAP L2 and L3 Radiometer Soil Moisture (Passive) Data Products: L2_SM_P & L3_SM_P
ATBDVersion :
Version 1.1
SWVersionID :
026
algorithmDate :
2021-08-17
algorithmDescription :
Level 3 soil moisture product is formed by mosaicking Level 2 soil moisture granule data acquired over one day.
algorithmTitle :
Soil Moisture Active Passive (SMAP) Radiometer processing algorithm
algorithmVersionID :
023
documentDate :
2012-10-26
documentVersion :
Preliminary
documentation :
Algorithm Theoretical Basis Document: SMAP L2 and L3 Radiometer Soil Moisture (Passive) Data Products: L2_SM_P & L3_SM_P
epochJulianDate :
2451545.0
epochUTCDateTime :
2000-01-01T11:58:55.816Z
identifier :
L3_SM_P_SPS
parameterVersionID :
015
processDescription :
Soil moisture retrieved using default retrieval algorithm from brightness temperatures acquired by the SMAP radiometer during the spacecraft descending pass. Level 2 granule data are then mosaicked on a daily basis to form the Level 3 product.
processor :
Soil Moisture Active Passive Mission (SMAP) Science Data System (SDS) Operations Facility
An ASCII product that contains statistical information on data product results. These statistics enable data producers and users to assess the quality of the data in the data product granule.
Daily global composite of up-to 30 half-orbit L2_SM_P soil moisture estimates based on radiometer brightness temperature measurements acquired by the SMAP radiometer during ascending and descending half-orbits at approximately 6 PM and 6 AM local solar time.
characterSet :
utf8
credit :
The software that generates the Level 3 Soil Moisture Passive product and the data system that automates its production were designed and implemented \n",
+ " at the Jet Propulsion Laboratory, California Institute of Technology in Pasadena, California.
identifier_product_DOI :
doi:10.5067/4XXOGX0OOW1S
language :
eng
longName :
SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture
mission :
SMAP
otherCitationDetails :
The Calibration and Validation Version 2 Release of the SMAP Level 3 Daily Global Composite Passive Soil Moisture Science Processing Software.
pointOfContact :
National Snow and Ice Data Center
purpose :
The SMAP L3_SM_P algorithm provides daily global composite of soil moistures based on radiometer data on a 36 km grid.
resourceProviderOrganizationName :
National Aeronautics and Space Administration (NASA)
revisionDate :
2023-08-31
shortName :
SPL3SMP
spatialRepresentationType :
grid
status :
onGoing
topicCategory :
geoscientificInformation
y: 406
x: 964
igbp_class: 3
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+ " <gmi:resolution>\n",
+ " <gmi:LE_NominalResolution>\n",
+ " <gmi:groundResolution>\n",
+ " <gco:Distance uom="km">36</gco:Distance>\n",
+ " </gmi:groundResolution>\n",
+ " </gmi:LE_NominalResolution>\n",
+ " </gmi:resolution>\n",
+ " </gmi:LE_Source>\n",
+ " </gmd:source>\n",
+ " <gmd:source xlink:type="simple">\n",
+ " <gmi:LE_Source>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>Passive soil moisture estimates onto a 36-km global Earth-fixed grid, based on radiometer measurements acquired when the SMAP spacecraft is travelling from North to South at approximately 6:00 AM local time.</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " <gmd:sourceCitation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gmx:FileName>SMAP_L2_SM_P_11121_A_20170301T225047_R19240_001.h5</gmx:FileName>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2024-05-02</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="creation">creation</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gmx:Anchor xlink:type="simple">doi:10.5067/K7Y2D8QQVZ4L</gmx:Anchor>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>gov.nasa.esdis</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>A Digital Object Identifier (DOI) that provides a persistent interoperable means to locate the SMAP Level 2 SM P data product.</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " <gmd:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>L2_SM_P</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>http://smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>A short name used by the Soil Moisture Active Passive (SMAP) mission to identify the Level 2 SM_P product.</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:sourceCitation>\n",
+ " <gmi:processedLevel xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>SMAP Radiometer Level 2 SM P SPS</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmi:processedLevel>\n",
+ " <gmi:resolution>\n",
+ " <gmi:LE_NominalResolution>\n",
+ " <gmi:groundResolution>\n",
+ " <gco:Distance uom="km">36</gco:Distance>\n",
+ " </gmi:groundResolution>\n",
+ " </gmi:LE_NominalResolution>\n",
+ " </gmi:resolution>\n",
+ " </gmi:LE_Source>\n",
+ " </gmd:source>\n",
+ " <gmd:source xlink:type="simple">\n",
+ " <gmi:LE_Source>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>Passive soil moisture estimates onto a 36-km global Earth-fixed grid, based on radiometer measurements acquired when the SMAP spacecraft is travelling from North to South at approximately 6:00 AM local time.</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " <gmd:sourceCitation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gmx:FileName>SMAP_L2_SM_P_11121_D_20170301T234002_R19240_001.h5</gmx:FileName>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2024-05-02</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="creation">creation</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gmx:Anchor xlink:type="simple">doi:10.5067/K7Y2D8QQVZ4L</gmx:Anchor>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>gov.nasa.esdis</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>A Digital Object Identifier (DOI) that provides a persistent interoperable means to locate the SMAP Level 2 SM P data product.</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " <gmd:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>L2_SM_P</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>http://smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>A short name used by the Soil Moisture Active Passive (SMAP) mission to identify the Level 2 SM_P product.</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:sourceCitation>\n",
+ " <gmi:processedLevel xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>SMAP Radiometer Level 2 SM P SPS</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmi:processedLevel>\n",
+ " <gmi:resolution>\n",
+ " <gmi:LE_NominalResolution>\n",
+ " <gmi:groundResolution>\n",
+ " <gco:Distance uom="km">36</gco:Distance>\n",
+ " </gmi:groundResolution>\n",
+ " </gmi:LE_NominalResolution>\n",
+ " </gmi:resolution>\n",
+ " </gmi:LE_Source>\n",
+ " </gmd:source>\n",
+ " <gmd:source xlink:type="simple">\n",
+ " <gmi:LE_Source>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>A configuration file that lists the entire content of the output Radiometer Level 3_SM_P_ product.</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " <gmd:sourceCitation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gmx:FileName>SMAP_L3_SM_P_SPS_OutputConfig_L3_SM_P.xml</gmx:FileName>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2024-05-02</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="creation">creation</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>R19240</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " <gmd:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>OutputConfig</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:sourceCitation>\n",
+ " </gmi:LE_Source>\n",
+ " </gmd:source>\n",
+ " <gmd:source xlink:type="simple">\n",
+ " <gmi:LE_Source>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>A configuration file generated automatically within the SMAP data system that specifies all of the conditions required for each individual run of the Radiometer Level 3 SM P Science Processing Software (SPS).</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " <gmd:sourceCitation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gmx:FileName>SMAP_L3_SM_P_SPS_RunConfig_20240502T191336188.xml</gmx:FileName>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2024-05-02</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="creation">creation</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>R19240</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " <gmd:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>RunConfig</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:sourceCitation>\n",
+ " </gmi:LE_Source>\n",
+ " </gmd:source>\n",
+ " </gmd:LI_Lineage>\n",
+ " </gmd:lineage>\n",
+ " </gmd:DQ_DataQuality>\n",
+ " </gmd:dataQualityInfo>\n",
+ " <gmi:acquisitionInformation xlink:type="simple">\n",
+ " <gmi:MI_AcquisitionInformation>\n",
+ " <gmi:platform xlink:type="simple">\n",
+ " <eos:EOS_Platform>\n",
+ " <gmi:citation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>SMAP Handbook</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2014-07-01</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="publication">publication</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>JPL CL#14-2285, JPL 400-1567</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmi:citation>\n",
+ " <gmi:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>SMAP</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>http://smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmi:identifier>\n",
+ " <gmi:description>\n",
+ " <gco:CharacterString>The SMAP observatory houses an L-band radiometer that operates at 1.414 GHz and an L-band radar that operates at 1.225 GHz. The instruments share a rotating reflector antenna with a 6 meter aperture that scans over a 1000 km swath. The bus is a 3 axis stabilized spacecraft that provides momentum compensation for the rotating antenna.</gco:CharacterString>\n",
+ " </gmi:description>\n",
+ " <gmi:instrument xlink:type="simple">\n",
+ " <gmi:MI_Instrument>\n",
+ " <gmi:citation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>SMAP Handbook</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2014-07-01</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="publication">publication</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>JPL CL#14-2285, JPL 400-1567</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmi:citation>\n",
+ " <gmi:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>SMAP SAR</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmi:identifier>\n",
+ " <gmi:type>\n",
+ " <gco:CharacterString>L-Band Synthetic Aperture Radar</gco:CharacterString>\n",
+ " </gmi:type>\n",
+ " <gmi:description>\n",
+ " <gco:CharacterString>The SMAP 1.225 GHz L-Band Radar Instrument</gco:CharacterString>\n",
+ " </gmi:description>\n",
+ " </gmi:MI_Instrument>\n",
+ " </gmi:instrument>\n",
+ " <gmi:instrument xlink:type="simple">\n",
+ " <gmi:MI_Instrument>\n",
+ " <gmi:citation xlink:type="simple">\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>SMAP Handbook</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date xlink:type="simple">\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2014-07-01</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="publication">publication</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>JPL CL#14-2285, JPL 400-1567</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmi:citation>\n",
+ " <gmi:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>SMAP RAD</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmi:identifier>\n",
+ " <gmi:type>\n",
+ " <gco:CharacterString>L-Band Radiometer</gco:CharacterString>\n",
+ " </gmi:type>\n",
+ " <gmi:description>\n",
+ " <gco:CharacterString>The SMAP 1.414 GHz L-Band Radiometer</gco:CharacterString>\n",
+ " </gmi:description>\n",
+ " </gmi:MI_Instrument>\n",
+ " </gmi:instrument>\n",
+ " <eos:otherProperty xlink:type="simple">\n",
+ " <gco:Record xlink:type="simple" xsi:type="eos:EOS_AdditionalAttributes_PropertyType">\n",
+ " <eos:EOS_AdditionalAttributes>\n",
+ " <eos:additionalAttribute xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttribute>\n",
+ " <eos:reference xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttributeDescription>\n",
+ " <eos:type>\n",
+ " <eos:EOS_AdditionalAttributeTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/" codeListValue="processingInformation">processingInformation</eos:EOS_AdditionalAttributeTypeCode>\n",
+ " </eos:type>\n",
+ " <eos:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>uuid for stopRevNumber</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>http://smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " </gmd:MD_Identifier>\n",
+ " </eos:identifier>\n",
+ " <eos:name>\n",
+ " <gco:CharacterString>stopRevNumber</gco:CharacterString>\n",
+ " </eos:name>\n",
+ " <eos:dataType>\n",
+ " <eos:EOS_AdditionalAttributeDataTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/Codelists.xml#EOS_AdditionalAttributeDataTypeCode" codeListValue="int">int</eos:EOS_AdditionalAttributeDataTypeCode>\n",
+ " </eos:dataType>\n",
+ " </eos:EOS_AdditionalAttributeDescription>\n",
+ " </eos:reference>\n",
+ " <eos:value>\n",
+ " <gco:CharacterString>11121</gco:CharacterString>\n",
+ " </eos:value>\n",
+ " </eos:EOS_AdditionalAttribute>\n",
+ " </eos:additionalAttribute>\n",
+ " <eos:additionalAttribute xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttribute>\n",
+ " <eos:reference xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttributeDescription>\n",
+ " <eos:type>\n",
+ " <eos:EOS_AdditionalAttributeTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/" codeListValue="processingInformation">processingInformation</eos:EOS_AdditionalAttributeTypeCode>\n",
+ " </eos:type>\n",
+ " <eos:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>uuid for startRevNumber</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>http://smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " </gmd:MD_Identifier>\n",
+ " </eos:identifier>\n",
+ " <eos:name>\n",
+ " <gco:CharacterString>startRevNumber</gco:CharacterString>\n",
+ " </eos:name>\n",
+ " <eos:dataType>\n",
+ " <eos:EOS_AdditionalAttributeDataTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/Codelists.xml#EOS_AdditionalAttributeDataTypeCode" codeListValue="int">int</eos:EOS_AdditionalAttributeDataTypeCode>\n",
+ " </eos:dataType>\n",
+ " </eos:EOS_AdditionalAttributeDescription>\n",
+ " </eos:reference>\n",
+ " <eos:value>\n",
+ " <gco:CharacterString>11107</gco:CharacterString>\n",
+ " </eos:value>\n",
+ " </eos:EOS_AdditionalAttribute>\n",
+ " </eos:additionalAttribute>\n",
+ " <eos:additionalAttribute xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttribute>\n",
+ " <eos:reference xlink:type="simple">\n",
+ " <eos:EOS_AdditionalAttributeDescription>\n",
+ " <eos:type>\n",
+ " <eos:EOS_AdditionalAttributeTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/" codeListValue="processingInformation">processingInformation</eos:EOS_AdditionalAttributeTypeCode>\n",
+ " </eos:type>\n",
+ " <eos:identifier xlink:type="simple">\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>uuid for AntennaRotationRate</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <gco:CharacterString>http://smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " </gmd:MD_Identifier>\n",
+ " </eos:identifier>\n",
+ " <eos:name>\n",
+ " <gco:CharacterString>AntennaRotationRate</gco:CharacterString>\n",
+ " </eos:name>\n",
+ " <eos:dataType>\n",
+ " <eos:EOS_AdditionalAttributeDataTypeCode codeList="http://cdn.earthdata.nasa.gov/metadata/resources/Codelists.xml#EOS_AdditionalAttributeDataTypeCode" codeListValue="float">float</eos:EOS_AdditionalAttributeDataTypeCode>\n",
+ " </eos:dataType>\n",
+ " </eos:EOS_AdditionalAttributeDescription>\n",
+ " </eos:reference>\n",
+ " <eos:value>\n",
+ " <gco:CharacterString>14.6</gco:CharacterString>\n",
+ " </eos:value>\n",
+ " </eos:EOS_AdditionalAttribute>\n",
+ " </eos:additionalAttribute>\n",
+ " </eos:EOS_AdditionalAttributes>\n",
+ " </gco:Record>\n",
+ " </eos:otherProperty>\n",
+ " </eos:EOS_Platform>\n",
+ " </gmi:platform>\n",
+ " </gmi:MI_AcquisitionInformation>\n",
+ " </gmi:acquisitionInformation>\n",
+ " </gmi:MI_Metadata>\n",
+ " </gmd:has>\n",
+ " </gmd:DS_DataSet>\n",
+ " </gmd:composedOf>\n",
+ "\n",
+ " <gmd:seriesMetadata gco:nilReason="missing" xlink:type="simple"/>\n",
+ "\n",
+ "</gmd:DS_Series>\n",
+ "
iso_19139_dataset_xml_md5 :
8575fcbb24fb9331cbb74df74abd5b15
iso_19139_series_xml :
<?xml version="1.0" encoding="UTF-8"?>\n",
+ "<gmd:DS_Series xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"\n",
+ " xsi:schemaLocation="http://www.isotc211.org/2005/gmi http://cdn.earthdata.nasa.gov/iso/schema/1.0/ISO19115-2_EOS.xsd"\n",
+ " xmlns:gco="http://www.isotc211.org/2005/gco"\n",
+ " xmlns:gmd="http://www.isotc211.org/2005/gmd"\n",
+ " xmlns:xlink="http://www.w3.org/1999/xlink"\n",
+ " xmlns:gml="http://www.opengis.net/gml/3.2"\n",
+ " xmlns:gsr="http://www.isotc211.org/2005/gsr"\n",
+ " xmlns:gss="http://www.isotc211.org/2005/gss"\n",
+ " xmlns:gts="http://www.isotc211.org/2005/gts"\n",
+ " xmlns:gmi="http://www.isotc211.org/2005/gmi"\n",
+ " xmlns:gmx="http://www.isotc211.org/2005/gmx">\n",
+ " <gmd:composedOf gco:nilReason="inapplicable"/>\n",
+ " <gmd:seriesMetadata>\n",
+ " <gmi:MI_Metadata>\n",
+ " <!-- With reference to file name here, do we need to use MD_Identification/CI_Citation to reference the file. -->\n",
+ " <gmd:fileIdentifier>\n",
+ " <gco:CharacterString>L3_SM_P</gco:CharacterString>\n",
+ " <!-- Assume that the file Identifier for series metadata would be the identifier that denotes that a file belongs to this series. -->\n",
+ " </gmd:fileIdentifier>\n",
+ " <gmd:language>\n",
+ " <gco:CharacterString>eng</gco:CharacterString>\n",
+ " </gmd:language>\n",
+ " <gmd:characterSet>\n",
+ " <gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode" codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>\n",
+ " </gmd:characterSet>\n",
+ " <gmd:hierarchyLevel>\n",
+ " <gmd:MD_ScopeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ScopeCode" codeListValue="series">series</gmd:MD_ScopeCode>\n",
+ " </gmd:hierarchyLevel>\n",
+ " <gmd:contact>\n",
+ " <gmd:CI_ResponsibleParty>\n",
+ " <gmd:organisationName>\n",
+ " <gco:CharacterString>NSIDC DAAC > National Snow and Ice Data Center DAAC</gco:CharacterString>\n",
+ " </gmd:organisationName>\n",
+ " <gmd:contactInfo>\n",
+ " <gmd:CI_Contact>\n",
+ " <gmd:address>\n",
+ " <gmd:CI_Address>\n",
+ " <gmd:electronicMailAddress>\n",
+ " <gco:CharacterString>nsidc@nsidc.org</gco:CharacterString>\n",
+ " </gmd:electronicMailAddress>\n",
+ " </gmd:CI_Address>\n",
+ " </gmd:address>\n",
+ " <gmd:onlineResource>\n",
+ " <gmd:CI_OnlineResource>\n",
+ " <gmd:linkage>\n",
+ " <gmd:URL>http://nsidc.org/daac/</gmd:URL>\n",
+ " </gmd:linkage>\n",
+ " </gmd:CI_OnlineResource>\n",
+ " </gmd:onlineResource>\n",
+ " </gmd:CI_Contact>\n",
+ " </gmd:contactInfo>\n",
+ " <gmd:role>\n",
+ " <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode" codeListValue="pointOfContact">pointOfContact</gmd:CI_RoleCode>\n",
+ " </gmd:role>\n",
+ " </gmd:CI_ResponsibleParty>\n",
+ " </gmd:contact>\n",
+ " <gmd:dateStamp>\n",
+ " <gco:Date>2019-04-15</gco:Date>\n",
+ " </gmd:dateStamp>\n",
+ " <gmd:metadataStandardName>\n",
+ " <gco:CharacterString>ISO 19115-2 Geographic information - Metadata - Part 2: Extensions for imagery and gridded data</gco:CharacterString>\n",
+ " </gmd:metadataStandardName>\n",
+ " <gmd:metadataStandardVersion>\n",
+ " <gco:CharacterString>ISO 19115-2:2009-02-15</gco:CharacterString>\n",
+ " </gmd:metadataStandardVersion>\n",
+ " <gmd:identificationInfo>\n",
+ " <gmd:MD_DataIdentification>\n",
+ " <gmd:citation>\n",
+ " <!-- If file name reference in MI_Metadata is sufficient, can use this CI_Citation to reference Product Specification Document. -->\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <!-- This field provides the product Long Name required by the ECS. -->\n",
+ " <gco:CharacterString>SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date>\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <!-- This field provides the date of a particular release or build. For the ECS, this is the RevisionDate, a required field. -->\n",
+ " <gco:Date>2023-08-31</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="revision">revision</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <!-- Specifies the SMAP Release ID -->\n",
+ " <gco:CharacterString>R19</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " <gmd:identifier>\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <!-- This field provides the product Short Name. This is the ECS Short Name rather than the SMAP Short Name. -->\n",
+ " <gco:CharacterString>SPL3SMP</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <!-- This field is intended to provide a namespace identifier for SMAP data product Short Names. Team should devise an identifier. -->\n",
+ " <gco:CharacterString>smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>The ECS Short Name</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " <gmd:identifier>\n",
+ " <gmd:MD_Identifier> <!-- This field provides the ECS Version ID. -->\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>009</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace> <!-- This field is intended to provide the namespace for ECS Version IDs for the SMAP mission. Team should devise an identifier.-->\n",
+ " <gco:CharacterString>gov.nasa.esdis</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>The ECS Version ID</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " <gmd:identifier>\n",
+ " <gmd:MD_Identifier> <!-- This field provides the Digital Object Identifier (DOI). -->\n",
+ " <gmd:code>\n",
+ " <gmx:Anchor xlink:actuate="onRequest" xlink:href="http://dx.doi.org/10.5067/4XXOGX0OOW1S" >doi:10.5067/4XXOGX0OOW1S</gmx:Anchor>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace> <!-- This field is intended to provide a namespace identifier for DOIs. What would be best specification?-->\n",
+ " <gco:CharacterString>gov.nasa.esdis</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>A Digital Object Identifier (DOI)</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " <gmd:citedResponsibleParty>\n",
+ " <gmd:CI_ResponsibleParty>\n",
+ " <gmd:organisationName>\n",
+ " <gco:CharacterString>National Aeronautics and Space Administration (NASA)</gco:CharacterString>\n",
+ " </gmd:organisationName>\n",
+ " <gmd:role>\n",
+ " <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode" codeListValue="resourceProvider">resourceProvider</gmd:CI_RoleCode>\n",
+ " </gmd:role>\n",
+ " </gmd:CI_ResponsibleParty>\n",
+ " </gmd:citedResponsibleParty>\n",
+ " <gmd:citedResponsibleParty>\n",
+ " <gmd:CI_ResponsibleParty>\n",
+ " <gmd:organisationName>\n",
+ " <!-- This field provides the ProcessingCenter, a required field for the ECS. The ECS will need to check the roleCode to ensure they're viewing the correct field.-->\n",
+ " <gco:CharacterString>Jet Propulsion Laboratory</gco:CharacterString>\n",
+ " </gmd:organisationName>\n",
+ " <gmd:role>\n",
+ " <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode" codeListValue="originator">originator</gmd:CI_RoleCode>\n",
+ " </gmd:role>\n",
+ " </gmd:CI_ResponsibleParty>\n",
+ " </gmd:citedResponsibleParty>\n",
+ " <gmd:presentationForm>\n",
+ " <gmd:CI_PresentationFormCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_PresentationFormCode" codeListValue="documentDigital">documentDigital</gmd:CI_PresentationFormCode>\n",
+ " </gmd:presentationForm>\n",
+ " <gmd:otherCitationDetails>\n",
+ " <gco:CharacterString>The Calibration and Validation Version 2 Release of the SMAP Level 3 Daily Global Composite Passive Soil Moisture Science Processing Software.</gco:CharacterString>\n",
+ " </gmd:otherCitationDetails>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:citation>\n",
+ " <gmd:abstract>\n",
+ " <!-- This field contains the CollectionDescription required by the ECS. -->\n",
+ " <gco:CharacterString>Daily global composite of up-to 30 half-orbit L2_SM_P soil moisture estimates based on radiometer brightness temperature measurements acquired by the SMAP radiometer during ascending and descending half-orbits at approximately 6 PM and 6 AM local solar time.</gco:CharacterString>\n",
+ " </gmd:abstract>\n",
+ " <gmd:purpose>\n",
+ " <gco:CharacterString>The SMAP L3_SM_P algorithm provides daily global composite of soil moistures based on radiometer data on a 36 km grid.</gco:CharacterString>\n",
+ " </gmd:purpose>\n",
+ " <gmd:credit>\n",
+ " <!-- This field can name individuals or organizations for credit. For now, it specifies NASA. -->\n",
+ " <gco:CharacterString>The software that generates the Level 3 Soil Moisture Passive product and the data system that automates its production were designed and implemented \n",
+ " at the Jet Propulsion Laboratory, California Institute of Technology in Pasadena, California.</gco:CharacterString>\n",
+ " </gmd:credit>\n",
+ " <gmd:status>\n",
+ " <gmd:MD_ProgressCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ProgressCode" codeListValue="onGoing">onGoing</gmd:MD_ProgressCode>\n",
+ " </gmd:status>\n",
+ " <gmd:pointOfContact>\n",
+ " <gmd:CI_ResponsibleParty>\n",
+ " <gmd:organisationName>\n",
+ " <!-- This field provides the ArchiveCenter, a required entry for the ECS. -->\n",
+ " <gco:CharacterString>National Snow and Ice Data Center</gco:CharacterString>\n",
+ " </gmd:organisationName>\n",
+ " <gmd:role>\n",
+ " <gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode" codeListValue="distributor">distributor</gmd:CI_RoleCode>\n",
+ " </gmd:role>\n",
+ " </gmd:CI_ResponsibleParty>\n",
+ " </gmd:pointOfContact>\n",
+ " <gmd:resourceMaintenance>\n",
+ " <gmd:MD_MaintenanceInformation>\n",
+ " <gmd:maintenanceAndUpdateFrequency>\n",
+ " <gmd:MD_MaintenanceFrequencyCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_MaintenanceFrequencyCode" codeListValue="asNeeded">asNeeded</gmd:MD_MaintenanceFrequencyCode>\n",
+ " </gmd:maintenanceAndUpdateFrequency>\n",
+ " <gmd:dateOfNextUpdate>\n",
+ " <gco:Date>2017-04-01</gco:Date>\n",
+ " </gmd:dateOfNextUpdate>\n",
+ " <gmd:updateScope>\n",
+ " <gmd:MD_ScopeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ScopeCode" codeListValue="series">series</gmd:MD_ScopeCode>\n",
+ " </gmd:updateScope>\n",
+ " </gmd:MD_MaintenanceInformation>\n",
+ " </gmd:resourceMaintenance>\n",
+ " <gmd:resourceFormat>\n",
+ " <gmd:MD_Format>\n",
+ " <gmd:name>\n",
+ " <gco:CharacterString>HDF5</gco:CharacterString>\n",
+ " </gmd:name>\n",
+ " <gmd:version>\n",
+ " <gco:CharacterString>1.8.13</gco:CharacterString>\n",
+ " </gmd:version>\n",
+ " </gmd:MD_Format>\n",
+ " </gmd:resourceFormat>\n",
+ " <gmd:descriptiveKeywords>\n",
+ " <gmd:MD_Keywords>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > LAND SURFACE > SOILS > SOIL MOISTURE/WATER CONTENT</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > CLIMATE INDICATORS > LAND SURFACE/AGRICULTURE INDICATORS > SOIL MOISTURE</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > SPECTRAL/ENGINEERING > MICROWAVE > BRIGHTNESS TEMPERATURE</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SNOW/ICE > FREEZE/THAW</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > CRYOSPHERE > SNOW/ICE > FREEZE/THAW</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > BIOSPHERE > VEGETATION > PLANT CHARACTERISTICS > VEGETATION WATER CONTENT</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > LAND SURFACE > SURFACE RADIATIVE PROPERTIES > ALBEDO</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > SURFACE ROUGHNESS</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > LAND SURFACE > SURFACE RADIATIVE PROPERTIES > ALBEDO</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>EARTH SCIENCE > TERRESTRIAL HYDROSPHERE> SNOW/ICE > FREEZE/THAW</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:type>\n",
+ " <gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode" codeListValue="theme">theme</gmd:MD_KeywordTypeCode>\n",
+ " </gmd:type>\n",
+ " <gmd:thesaurusName>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>NASA/GCMD Earth Science Keywords</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date gco:nilReason="unknown"/>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:thesaurusName>\n",
+ " </gmd:MD_Keywords>\n",
+ " </gmd:descriptiveKeywords>\n",
+ " <gmd:descriptiveKeywords>\n",
+ " <gmd:MD_Keywords>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>Earth Remote Sensing Instruments > Passive Remote Sensing > Spectrometers/Radiometers > Imaging Spectrometers/Radiometers > SMAP L-BAND RADIOMETER > SMAP L-Band Radiometer</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:type>\n",
+ " <gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode" codeListValue="theme">theme</gmd:MD_KeywordTypeCode>\n",
+ " </gmd:type>\n",
+ " <gmd:thesaurusName>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>NASA/GCMD Earth Science Keywords</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date gco:nilReason="unknown"/>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:thesaurusName>\n",
+ " </gmd:MD_Keywords>\n",
+ " </gmd:descriptiveKeywords>\n",
+ " <gmd:descriptiveKeywords>\n",
+ " <gmd:MD_Keywords>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>Earth Observation Satellites > NASA Decadal Survey > SMAP > Soil Moisture Active and Passive Observatory</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:type>\n",
+ " <gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode" codeListValue="theme">theme</gmd:MD_KeywordTypeCode>\n",
+ " </gmd:type>\n",
+ " <gmd:thesaurusName>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>NASA/GCMD Earth Science Keywords</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date gco:nilReason="unknown"/>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:thesaurusName>\n",
+ " </gmd:MD_Keywords>\n",
+ " </gmd:descriptiveKeywords>\n",
+ " <gmd:descriptiveKeywords>\n",
+ " <gmd:MD_Keywords>\n",
+ " <gmd:keyword>\n",
+ " <gco:CharacterString>GEOGRAPHIC REGION > GLOBAL</gco:CharacterString>\n",
+ " </gmd:keyword>\n",
+ " <gmd:type>\n",
+ " <gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode" codeListValue="theme">theme</gmd:MD_KeywordTypeCode>\n",
+ " </gmd:type>\n",
+ " <gmd:thesaurusName>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>NASA/GCMD Earth Science Keywords</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date gco:nilReason="unknown"/>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:thesaurusName>\n",
+ " </gmd:MD_Keywords>\n",
+ " </gmd:descriptiveKeywords> \n",
+ " <gmd:aggregationInfo>\n",
+ " <gmd:MD_AggregateInformation>\n",
+ " <gmd:aggregateDataSetIdentifier>\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>SMAP</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:aggregateDataSetIdentifier>\n",
+ " <gmd:associationType>\n",
+ " <gmd:DS_AssociationTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#DS_AssociationTypeCode" codeListValue="largerWorkCitation">largerWorkCitation</gmd:DS_AssociationTypeCode>\n",
+ " </gmd:associationType>\n",
+ " <gmd:initiativeType>\n",
+ " <gmd:DS_InitiativeTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#DS_AssociationTypeCode" codeListValue="mission">mission</gmd:DS_InitiativeTypeCode>\n",
+ " </gmd:initiativeType>\n",
+ " </gmd:MD_AggregateInformation>\n",
+ " </gmd:aggregationInfo>\n",
+ " <gmd:spatialRepresentationType>\n",
+ " <gmd:MD_SpatialRepresentationTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_SpatialRepresentationTypeCode" codeListValue="grid">grid</gmd:MD_SpatialRepresentationTypeCode>\n",
+ " </gmd:spatialRepresentationType>\n",
+ " <gmd:spatialResolution>\n",
+ " <gmd:MD_Resolution>\n",
+ " <gmd:distance>\n",
+ " <gco:Distance uom="km">36</gco:Distance>\n",
+ " </gmd:distance>\n",
+ " </gmd:MD_Resolution>\n",
+ " </gmd:spatialResolution>\n",
+ " <gmd:language>\n",
+ " <gco:CharacterString>eng</gco:CharacterString>\n",
+ " </gmd:language>\n",
+ " <gmd:characterSet>\n",
+ " <gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode" codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>\n",
+ " </gmd:characterSet>\n",
+ " <gmd:topicCategory>\n",
+ " <gmd:MD_TopicCategoryCode>geoscientificInformation</gmd:MD_TopicCategoryCode>\n",
+ " </gmd:topicCategory>\n",
+ " <gmd:environmentDescription>\n",
+ " <gco:CharacterString>Data product generated by the SMAP mission in HDF5 format with metadata that conforms to the ISO 19115 model.</gco:CharacterString>\n",
+ " </gmd:environmentDescription>\n",
+ " <gmd:extent>\n",
+ " <gmd:EX_Extent>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>Soil moisture is\n",
+ "\t\t\t\tretrieved over land targets on the\n",
+ "\t\t\t\tdescending (AM) and ascending (PM) SMAP half-orbits, \n",
+ " while the SMAP instruments are operating in the nominal mode. Retrievals are performed but flagged as questionable \n",
+ " over urban areas, mountainous areas with high elevation variability, and areas with high ( > 5 kg/m**2) vegetation \n",
+ " water content; for retrievals using the high-resolution radar, cells in the nadir region are also flagged.\n",
+ " Retrievals are inhibited for permanent snow/ice, frozen ground, and excessive static or transient open water in the cell,\n",
+ " and for excessive RFI in the sensor data.</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " <gmd:geographicElement>\n",
+ " <!-- This defines the bounding box for all SMAP Level 3 Passive Soil Moisture data products. -->\n",
+ " <gmd:EX_GeographicBoundingBox>\n",
+ " <gmd:extentTypeCode>\n",
+ " <gco:Boolean>1</gco:Boolean>\n",
+ " </gmd:extentTypeCode>\n",
+ " <gmd:westBoundLongitude>\n",
+ " <gco:Decimal>-180.00</gco:Decimal>\n",
+ " </gmd:westBoundLongitude>\n",
+ " <gmd:eastBoundLongitude>\n",
+ " <gco:Decimal>180.00</gco:Decimal>\n",
+ " </gmd:eastBoundLongitude>\n",
+ " <gmd:southBoundLatitude>\n",
+ " <gco:Decimal>-85.0445</gco:Decimal>\n",
+ " </gmd:southBoundLatitude>\n",
+ " <gmd:northBoundLatitude>\n",
+ " <gco:Decimal>85.0445</gco:Decimal>\n",
+ " </gmd:northBoundLatitude>\n",
+ " </gmd:EX_GeographicBoundingBox>\n",
+ " </gmd:geographicElement>\n",
+ " <gmd:temporalElement>\n",
+ " <gmd:EX_TemporalExtent>\n",
+ " <!-- Mimics use in GHRSST. See no evidence of conformance to standard -->\n",
+ " <gmd:extent>\n",
+ " <gml:TimePeriod gml:id="swathTemporalExtent">\n",
+ " <!-- This defines the time period covered by all SMAP Level 3 Passive Soil Moisture data products. \n",
+ " ECS indicates that they will automatically extend the final time based on receipt of data products. -->\n",
+ " <gml:beginPosition>2015-03-31T00:00:00.000Z</gml:beginPosition>\n",
+ " <gml:endPosition>2020-12-31T00:00:00.000Z</gml:endPosition>\n",
+ " </gml:TimePeriod>\n",
+ " </gmd:extent>\n",
+ " </gmd:EX_TemporalExtent>\n",
+ " </gmd:temporalElement>\n",
+ " </gmd:EX_Extent>\n",
+ " </gmd:extent>\n",
+ " </gmd:MD_DataIdentification>\n",
+ " </gmd:identificationInfo>\n",
+ " <gmd:identificationInfo>\n",
+ " <!-- This field is used to reference the Product Specification Document. If and when the model moves to ISO 19115-1, move this reference to additionalDocumentation. -->\n",
+ " <gmd:MD_DataIdentification>\n",
+ " <gmd:citation>\n",
+ " <gmd:CI_Citation>\n",
+ " <gmd:title>\n",
+ " <gco:CharacterString>Product Specification Document for the SMAP Level 3 Passive Soil Moisture Product (L3_SM_P)</gco:CharacterString>\n",
+ " </gmd:title>\n",
+ " <gmd:date>\n",
+ " <gmd:CI_Date>\n",
+ " <gmd:date>\n",
+ " <gco:Date>2013-02-08</gco:Date>\n",
+ " </gmd:date>\n",
+ " <gmd:dateType>\n",
+ " <gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode" codeListValue="publication">publication</gmd:CI_DateTypeCode>\n",
+ " </gmd:dateType>\n",
+ " </gmd:CI_Date>\n",
+ " </gmd:date>\n",
+ " <gmd:edition>\n",
+ " <gco:CharacterString>1.0</gco:CharacterString>\n",
+ " </gmd:edition>\n",
+ " <gmd:identifier>\n",
+ " <gmd:MD_Identifier>\n",
+ " <gmd:code>\n",
+ " <gco:CharacterString>L3_SM_P</gco:CharacterString>\n",
+ " </gmd:code>\n",
+ " <gmd:codeSpace>\n",
+ " <!-- This field is intended to provide a namespace identifier for SMAP data product Short Names. Team should devise an identifier. -->\n",
+ " <gco:CharacterString>smap.jpl.nasa.gov</gco:CharacterString>\n",
+ " </gmd:codeSpace>\n",
+ " <gmd:description>\n",
+ " <gco:CharacterString>Short name used by the Soil Moisture Active Passive (SMAP) mission to identify the Level 3 Passive Soil Moisture product.</gco:CharacterString>\n",
+ " </gmd:description>\n",
+ " </gmd:MD_Identifier>\n",
+ " </gmd:identifier>\n",
+ " <gmd:presentationForm>\n",
+ " <gmd:CI_PresentationFormCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_PresentationFormCode" codeListValue="documentDigital">documentDigital</gmd:CI_PresentationFormCode>\n",
+ " </gmd:presentationForm>\n",
+ " </gmd:CI_Citation>\n",
+ " </gmd:citation>\n",
+ " <gmd:abstract>\n",
+ " <gco:CharacterString>The Product Specification Document that fully describes the content and format of this data product.</gco:CharacterString>\n",
+ " </gmd:abstract>\n",
+ " <gmd:language>\n",
+ " <gco:CharacterString>eng</gco:CharacterString>\n",
+ " </gmd:language>\n",
+ " <gmd:characterSet>\n",
+ " <gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode" codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>\n",
+ " </gmd:characterSet>\n",
+ " </gmd:MD_DataIdentification>\n",
+ " </gmd:identificationInfo>\n",
+ " </gmi:MI_Metadata>\n",
+ " </gmd:seriesMetadata>\n",
+ "</gmd:DS_Series>\n",
+ "
The column index of the 36 km EASE grid cell that contains the associated data.
valid_max :
963
valid_min :
0
[391384 values with dtype=float32]
EASE_row_index
(y, x)
float32
...
long_name :
The row index of the 36 km EASE grid cell that contains the associated data.
valid_max :
405
valid_min :
0
[391384 values with dtype=float32]
albedo
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_dca
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scah
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-H within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scav
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-V within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
boresight_incidence
(y, x)
float32
...
long_name :
Representative angle between the antenna boresight vector and the normal to the Earth's surface for all footprints within the cell.
units :
degrees
valid_max :
90.0
valid_min :
0.0
[391384 values with dtype=float32]
bulk_density
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated bulk_density within the 36 km grid cell.
valid_max :
2.65
valid_min :
0.0
[391384 values with dtype=float32]
clay_fraction
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated clay fraction within the 36 km grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
freeze_thaw_fraction
(y, x)
float32
...
long_name :
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
grid_surface_status
(y, x)
float32
...
long_name :
Indicates if the grid point lies on land (0) or water (1).
valid_max :
1
valid_min :
0
[391384 values with dtype=float32]
landcover_class
(y, x, igbp_class)
float32
...
long_name :
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
[1174152 values with dtype=float32]
landcover_class_fraction
(y, x, igbp_class)
float32
...
long_name :
The fraction of the grid cell that contains the most common land cover in that area based on the IGBP landcover map.
valid_max :
1.0
valid_min :
0.0
[1174152 values with dtype=float32]
latitude
(y, x)
float32
...
long_name :
Latitude of the center of the Earth based grid cell.
units :
degrees_north
[391384 values with dtype=float32]
latitude_centroid
(y, x)
float32
...
long_name :
Weighted average of the latitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
longitude
(y, x)
float32
...
long_name :
Longitude of the center of the Earth based grid cell.
units :
degrees_east
[391384 values with dtype=float32]
longitude_centroid
(y, x)
float32
...
long_name :
Weighted average of the longitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
radar_water_body_fraction
(y, x)
float32
...
long_name :
The fraction of the area of the 36 km grid cell that is covered by water based on the radar detection algorithm.
Bit flags that represent the quality of the vertical polarization brightness temperature within each grid cell
[391384 values with dtype=float32]
tb_time_seconds
(y, x)
float64
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
units :
seconds
valid_max :
940000000.0
valid_min :
-999999.9
[391384 values with dtype=float64]
tb_time_utc
(y, x)
|S24
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in UTC.
[391384 values with dtype=|S24]
tb_v_corrected
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell adjusted for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
tb_v_uncorrected
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell before adjustment for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
vegetation_opacity
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_dca
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scah
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-H retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scav
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-V retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_water_content
(y, x)
float32
...
long_name :
Representative measure of water in the vegetation within the 36 km grid cell.
The column index of the 36 km EASE grid cell that contains the associated data.
valid_max :
963
valid_min :
0
[391384 values with dtype=float32]
EASE_row_index_pm
(y, x)
float32
...
long_name :
The row index of the 36 km EASE grid cell that contains the associated data.
valid_max :
405
valid_min :
0
[391384 values with dtype=float32]
albedo_dca_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scah_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-H retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scav_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-V retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
boresight_incidence_pm
(y, x)
float32
...
long_name :
Representative angle between the antenna boresight vector and the normal to the Earth's surface for all footprints within the cell.
units :
degrees
valid_max :
90.0
valid_min :
0.0
[391384 values with dtype=float32]
bulk_density_pm
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated bulk density within the 36 km grid cell.
valid_max :
2.65
valid_min :
0.0
[391384 values with dtype=float32]
clay_fraction_pm
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated clay fraction within the 36 km grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
freeze_thaw_fraction_pm
(y, x)
float32
...
long_name :
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
grid_surface_status_pm
(y, x)
float32
...
long_name :
Indicates if the grid point lies on land (0) or water (1).
valid_max :
1
valid_min :
0
[391384 values with dtype=float32]
landcover_class_fraction_pm
(y, x, igbp_class)
float32
...
long_name :
The fraction of the grid cell that contains the most common land cover in that area based on the IGBP landcover map.
valid_max :
1.0
valid_min :
0.0
[1174152 values with dtype=float32]
landcover_class_pm
(y, x, igbp_class)
float32
...
long_name :
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
[1174152 values with dtype=float32]
latitude_centroid_pm
(y, x)
float32
...
long_name :
Weighted average of the latitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
latitude_pm
(y, x)
float32
...
long_name :
Latitude of the center of the Earth based grid cell.
units :
degrees_north
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
longitude_centroid_pm
(y, x)
float32
...
long_name :
Weighted average of the longitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
longitude_pm
(y, x)
float32
...
long_name :
Longitude of the center of the Earth based grid cell.
units :
degrees_east
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
radar_water_body_fraction_pm
(y, x)
float32
...
long_name :
The fraction of the area of the 36 km grid cell that is covered by water based on the radar detection algorithm.
Bit flags that represent the quality of the vertical polarization brightness temperature within each grid cell
[391384 values with dtype=float32]
tb_time_seconds_pm
(y, x)
float64
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
units :
seconds
valid_max :
940000000.0
valid_min :
-999999.9
[391384 values with dtype=float64]
tb_time_utc_pm
(y, x)
|S24
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in UTC.
[391384 values with dtype=|S24]
tb_v_corrected_pm
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell adjusted for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
tb_v_uncorrected_pm
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell before adjustment for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
vegetation_opacity_dca_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in DCA retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in DCA retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scah_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in SCA-H retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scav_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in SCA-V retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_water_content_pm
(y, x)
float32
...
long_name :
Representative measure of water in the vegetation within the 36 km grid cell.
The column index of the 36 km EASE grid cell that contains the associated data.
valid_max :
963
valid_min :
0
[391384 values with dtype=float32]
EASE_row_index
(y, x)
float32
...
long_name :
The row index of the 36 km EASE grid cell that contains the associated data.
valid_max :
405
valid_min :
0
[391384 values with dtype=float32]
albedo
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_dca
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scah
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-H within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scav
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-V within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
boresight_incidence
(y, x)
float32
...
long_name :
Representative angle between the antenna boresight vector and the normal to the Earth's surface for all footprints within the cell.
units :
degrees
valid_max :
90.0
valid_min :
0.0
[391384 values with dtype=float32]
bulk_density
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated bulk_density within the 36 km grid cell.
valid_max :
2.65
valid_min :
0.0
[391384 values with dtype=float32]
clay_fraction
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated clay fraction within the 36 km grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
freeze_thaw_fraction
(y, x)
float32
...
long_name :
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
grid_surface_status
(y, x)
float32
...
long_name :
Indicates if the grid point lies on land (0) or water (1).
valid_max :
1
valid_min :
0
[391384 values with dtype=float32]
landcover_class
(y, x, igbp_class)
float32
...
long_name :
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
[1174152 values with dtype=float32]
landcover_class_fraction
(y, x, igbp_class)
float32
...
long_name :
The fraction of the grid cell that contains the most common land cover in that area based on the IGBP landcover map.
valid_max :
1.0
valid_min :
0.0
[1174152 values with dtype=float32]
latitude
(y, x)
float32
...
long_name :
Latitude of the center of the Earth based grid cell.
units :
degrees_north
[391384 values with dtype=float32]
latitude_centroid
(y, x)
float32
...
long_name :
Weighted average of the latitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
longitude
(y, x)
float32
...
long_name :
Longitude of the center of the Earth based grid cell.
units :
degrees_east
[391384 values with dtype=float32]
longitude_centroid
(y, x)
float32
...
long_name :
Weighted average of the longitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
radar_water_body_fraction
(y, x)
float32
...
long_name :
The fraction of the area of the 36 km grid cell that is covered by water based on the radar detection algorithm.
Bit flags that represent the quality of the vertical polarization brightness temperature within each grid cell
[391384 values with dtype=float32]
tb_time_seconds
(y, x)
float64
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
units :
seconds
valid_max :
940000000.0
valid_min :
-999999.9
[391384 values with dtype=float64]
tb_time_utc
(y, x)
|S24
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in UTC.
[391384 values with dtype=|S24]
tb_v_corrected
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell adjusted for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
tb_v_uncorrected
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell before adjustment for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
vegetation_opacity
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_dca
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scah
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-H retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scav
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-V retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_water_content
(y, x)
float32
...
long_name :
Representative measure of water in the vegetation within the 36 km grid cell.
units :
kg/m**2
valid_max :
20.0
valid_min :
0.0
[391384 values with dtype=float32]
EASE_column_index_pm
(y, x)
float32
...
long_name :
The column index of the 36 km EASE grid cell that contains the associated data.
valid_max :
963
valid_min :
0
[391384 values with dtype=float32]
EASE_row_index_pm
(y, x)
float32
...
long_name :
The row index of the 36 km EASE grid cell that contains the associated data.
valid_max :
405
valid_min :
0
[391384 values with dtype=float32]
albedo_dca_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scah_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-H retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scav_pm
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-V retrievals within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
boresight_incidence_pm
(y, x)
float32
...
long_name :
Representative angle between the antenna boresight vector and the normal to the Earth's surface for all footprints within the cell.
units :
degrees
valid_max :
90.0
valid_min :
0.0
[391384 values with dtype=float32]
bulk_density_pm
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated bulk density within the 36 km grid cell.
valid_max :
2.65
valid_min :
0.0
[391384 values with dtype=float32]
clay_fraction_pm
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated clay fraction within the 36 km grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
freeze_thaw_fraction_pm
(y, x)
float32
...
long_name :
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
grid_surface_status_pm
(y, x)
float32
...
long_name :
Indicates if the grid point lies on land (0) or water (1).
valid_max :
1
valid_min :
0
[391384 values with dtype=float32]
landcover_class_fraction_pm
(y, x, igbp_class)
float32
...
long_name :
The fraction of the grid cell that contains the most common land cover in that area based on the IGBP landcover map.
valid_max :
1.0
valid_min :
0.0
[1174152 values with dtype=float32]
landcover_class_pm
(y, x, igbp_class)
float32
...
long_name :
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
[1174152 values with dtype=float32]
latitude_centroid_pm
(y, x)
float32
...
long_name :
Weighted average of the latitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
latitude_pm
(y, x)
float32
...
long_name :
Latitude of the center of the Earth based grid cell.
units :
degrees_north
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
longitude_centroid_pm
(y, x)
float32
...
long_name :
Weighted average of the longitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
longitude_pm
(y, x)
float32
...
long_name :
Longitude of the center of the Earth based grid cell.
units :
degrees_east
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
radar_water_body_fraction_pm
(y, x)
float32
...
long_name :
The fraction of the area of the 36 km grid cell that is covered by water based on the radar detection algorithm.
Bit flags that represent the quality of the vertical polarization brightness temperature within each grid cell
[391384 values with dtype=float32]
tb_time_seconds_pm
(y, x)
float64
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
units :
seconds
valid_max :
940000000.0
valid_min :
-999999.9
[391384 values with dtype=float64]
tb_time_utc_pm
(y, x)
|S24
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in UTC.
[391384 values with dtype=|S24]
tb_v_corrected_pm
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell adjusted for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
tb_v_uncorrected_pm
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell before adjustment for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
vegetation_opacity_dca_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in DCA retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in DCA retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scah_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in SCA-H retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scav_pm
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in SCA-V retrievals in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_water_content_pm
(y, x)
float32
...
long_name :
Representative measure of water in the vegetation within the 36 km grid cell.
units :
kg/m**2
valid_max :
20.0
valid_min :
0.0
[391384 values with dtype=float32]
"
+ ],
+ "text/plain": [
+ "\n",
+ "Group: /\n",
+ "│ Dimensions: (y: 406, x: 964, igbp_class: 3)\n",
+ "│ Coordinates:\n",
+ "│ * x (x) float64 8kB -1.735e+07 ... 1.735e+07\n",
+ "│ * y (y) float64 3kB 7.297e+06 ... -7.297e+06\n",
+ "│ * igbp_class (igbp_class) int64 24B 0 1 2\n",
+ "│ Data variables: (12/106)\n",
+ "│ EASE_column_index (y, x) float32 2MB ...\n",
+ "│ EASE_row_index (y, x) float32 2MB ...\n",
+ "│ albedo (y, x) float32 2MB ...\n",
+ "│ albedo_dca (y, x) float32 2MB ...\n",
+ "│ albedo_scah (y, x) float32 2MB ...\n",
+ "│ albedo_scav (y, x) float32 2MB ...\n",
+ "│ ... ...\n",
+ "│ tb_v_uncorrected_pm (y, x) float32 2MB ...\n",
+ "│ vegetation_opacity_dca_pm (y, x) float32 2MB ...\n",
+ "│ vegetation_opacity_pm (y, x) float32 2MB ...\n",
+ "│ vegetation_opacity_scah_pm (y, x) float32 2MB ...\n",
+ "│ vegetation_opacity_scav_pm (y, x) float32 2MB ...\n",
+ "│ vegetation_water_content_pm (y, x) float32 2MB ...\n",
+ "├── Group: /Metadata\n",
+ "│ │ Attributes:\n",
+ "│ │ iso_19139_dataset_xml: \\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "EASEGrid2 = ccrs.epsg(CRS.from_epsg(6933).to_epsg())\n",
+ "\n",
+ "p = dt[\"Soil_Moisture_Retrieval_Data_AM\"].soil_moisture.plot(\n",
+ " subplot_kws=dict(projection=EASEGrid2, facecolor=\"0.9\"),\n",
+ " transform=EASEGrid2,\n",
+ " cbar_kwargs=dict(shrink=0.5),\n",
+ " figsize=(12,7),\n",
+ ")\n",
+ "p.axes.coastlines()\n",
+ "p.axes.set_title('Soil Moisture');"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "5982dbc5-7e0f-48b5-8f0b-4435c880f200",
+ "metadata": {},
+ "source": [
+ "### Analyze a time-series of soil moisture\n",
+ "\n",
+ "Now that we know how to open one file as a `xarray.DataTree` lets open multiple open multiple files to create a time series for March 2017. We will plot the time mean for March and also plot a time series of spatially averaged soil moisture for a region in Colorado."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "345cd9da-fbaf-43af-aab5-5a9a1995b67c",
+ "metadata": {},
+ "source": [
+ "#### Read multiple files as a time series\n",
+ "\n",
+ "Currently, `xarray.open_datatree` can only open a single file as a `xarray.DataTree` object, so we have to use a different strategy to open a time series of files. Ideally, the alternative strategy would be to use `xarray.open_mfdataset` which is designed to load data from multiple files into a single dataset. However, we need a coordinate variable to concatenate on. For a time series, this is a time. The SMAP files do not have a time dimension. The time is in the filename instead.\n",
+ "\n",
+ "Our data access strategy is to open each file individually using a function `preprocess_file` and then concatenate all the `xarray.Dataset` from this preprocessing step into a single large `Dataset`. `preprocess_file` gets the timestamp for the data from the filename, opens the file, renames the dimensions as we did above, and adds `x`, `y`, and `time` coordinates. the `xarray.concat` function is used to concatenate the files along the time dimension.\n",
+ "\n",
+ "```{note}\n",
+ "If you creating your own NetCDF4 or HDF5 files, it is good practice to add a time dimension, even if data are for a singe timestep. This allows tools such as `xarray` to create time series of data efficiently.\n",
+ "```"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "33aba49f-371b-4cb3-9283-a3d91541a685",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
\n",
+ "
<xarray.Dataset> Size: 3GB\n",
+ "Dimensions: (time: 31, y: 406, x: 964, igbp_class: 3)\n",
+ "Coordinates:\n",
+ " * x (x) float64 8kB -1.735e+07 ... 1.735e+07\n",
+ " * y (y) float64 3kB 7.297e+06 ... -7.297e+06\n",
+ " * time (time) datetime64[ns] 248B 2017-03-01 ... 20...\n",
+ "Dimensions without coordinates: igbp_class\n",
+ "Data variables: (12/53)\n",
+ " EASE_column_index (time, y, x) float32 49MB 0.0 1.0 ... 963.0\n",
+ " EASE_row_index (time, y, x) float32 49MB 0.0 0.0 ... 405.0\n",
+ " albedo (time, y, x) float32 49MB nan nan ... 0.0 0.03\n",
+ " albedo_dca (time, y, x) float32 49MB nan nan ... 0.0 0.03\n",
+ " albedo_scah (time, y, x) float32 49MB nan nan ... 0.0 0.025\n",
+ " albedo_scav (time, y, x) float32 49MB nan nan ... 0.0 0.025\n",
+ " ... ...\n",
+ " tb_v_uncorrected (time, y, x) float32 49MB 251.9 251.7 ... 225.3\n",
+ " vegetation_opacity (time, y, x) float32 49MB nan nan ... nan nan\n",
+ " vegetation_opacity_dca (time, y, x) float32 49MB nan nan ... nan nan\n",
+ " vegetation_opacity_scah (time, y, x) float32 49MB nan nan ... nan nan\n",
+ " vegetation_opacity_scav (time, y, x) float32 49MB nan nan ... nan nan\n",
+ " vegetation_water_content (time, y, x) float32 49MB nan nan ... nan nan
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
"
+ ],
+ "text/plain": [
+ " Size: 3GB\n",
+ "Dimensions: (time: 31, y: 406, x: 964, igbp_class: 3)\n",
+ "Coordinates:\n",
+ " * x (x) float64 8kB -1.735e+07 ... 1.735e+07\n",
+ " * y (y) float64 3kB 7.297e+06 ... -7.297e+06\n",
+ " * time (time) datetime64[ns] 248B 2017-03-01 ... 20...\n",
+ "Dimensions without coordinates: igbp_class\n",
+ "Data variables: (12/53)\n",
+ " EASE_column_index (time, y, x) float32 49MB 0.0 1.0 ... 963.0\n",
+ " EASE_row_index (time, y, x) float32 49MB 0.0 0.0 ... 405.0\n",
+ " albedo (time, y, x) float32 49MB nan nan ... 0.0 0.03\n",
+ " albedo_dca (time, y, x) float32 49MB nan nan ... 0.0 0.03\n",
+ " albedo_scah (time, y, x) float32 49MB nan nan ... 0.0 0.025\n",
+ " albedo_scav (time, y, x) float32 49MB nan nan ... 0.0 0.025\n",
+ " ... ...\n",
+ " tb_v_uncorrected (time, y, x) float32 49MB 251.9 251.7 ... 225.3\n",
+ " vegetation_opacity (time, y, x) float32 49MB nan nan ... nan nan\n",
+ " vegetation_opacity_dca (time, y, x) float32 49MB nan nan ... nan nan\n",
+ " vegetation_opacity_scah (time, y, x) float32 49MB nan nan ... nan nan\n",
+ " vegetation_opacity_scav (time, y, x) float32 49MB nan nan ... nan nan\n",
+ " vegetation_water_content (time, y, x) float32 49MB nan nan ... nan nan"
+ ]
+ },
+ "execution_count": 9,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "def preprocess_file(f, x, y):\n",
+ "\n",
+ " time_string = f.stem.split(\"_\")[4] # Get date string from filename\n",
+ " time = datetime.datetime.strptime(time_string, \"%Y%m%d\") # Create datetime object\n",
+ " \n",
+ " ds = xr.open_dataset(f, \n",
+ " group=\"Soil_Moisture_Retrieval_Data_AM\", \n",
+ " phony_dims=\"sort\",\n",
+ " decode_timedelta=False)\n",
+ " \n",
+ " ds = ds.rename_dims({\n",
+ " 'phony_dim_0': 'y', \n",
+ " 'phony_dim_1': 'x', \n",
+ " 'phony_dim_2': 'igbp_class'\n",
+ " })\n",
+ "\n",
+ " # add coordinates\n",
+ " ds[\"x\"] = x\n",
+ " ds[\"y\"] = y\n",
+ " ds[\"time\"] = [time]\n",
+ " \n",
+ " return ds\n",
+ " \n",
+ "datasets = [preprocess_file(f, x, y) for f in filelist] # Use x and y from earlier calculations\n",
+ "\n",
+ "ds = xr.concat(datasets, dim=\"time\")\n",
+ "\n",
+ "ds"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "cfccdc72-3889-4e9e-beec-014e6a61ec0c",
+ "metadata": {},
+ "source": [
+ "#### Plot mean monthly soil moisture for March 2017\n",
+ "\n",
+ "We can now use `xarray` to calculate the mean soil moisture for March 2017 and plot the data on a map."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "e3632e36-555b-4554-908a-3afcad89bb7b",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 10,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "cbar_label = \" \".join(ds.soil_moisture.name.split(\"_\")).title() + f\" ({ds.soil_moisture.attrs['units']})\"\n",
+ "\n",
+ "p = ds.soil_moisture.mean(dim=[\"time\"]).plot(\n",
+ " subplot_kws=dict(projection=EASEGrid2, facecolor=\"0.9\"),\n",
+ " transform=EASEGrid2,\n",
+ " cbar_kwargs=dict(shrink=0.5, label=cbar_label),\n",
+ " figsize=(10,7)\n",
+ ")\n",
+ "p.axes.coastlines()\n",
+ "\n",
+ "p.axes.scatter(-113.5, 37.5, transform=ccrs.PlateCarree())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "8b2fb93b-10ad-4af4-a709-c457bab891f8",
+ "metadata": {},
+ "source": [
+ "#### Calculate and Plot a Time series for Four Corners Region\n",
+ "\n",
+ "We can use the time series of SMAP data to generate a plot of mean soil moisture from SMAP for the Four Corners of the western USA. The region of interest is defined by the latitude and longitudes in the code-cell below. These need to be transformed to grid coordinates in the EASE Grid 2.0 Global coordinate reference system (CRS).\n",
+ "\n",
+ "There are several tools that can be used to do this. Here we use the `transform_point` method of the `cartopy.crs`, `EASEGrid2`, we defined for creating the maps above. This takes a longitude and a latitude for each corner of the region of interest, along with the CRS for the latitude and longitude coordinate system."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "53b7f6e2-424f-40f1-9748-5db4c5d1aee9",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(np.float64(-10951192.808476754),\n",
+ " np.float64(-10613490.827598616),\n",
+ " np.float64(4457063.374682719),\n",
+ " np.float64(3986270.2078663567))"
+ ]
+ },
+ "execution_count": 11,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "N_lat = 37.5\n",
+ "S_lat = 33.0\n",
+ "W_lon = -113.5\n",
+ "E_lon = -110.0\n",
+ "\n",
+ "x1, y1 = EASEGrid2.transform_point(E_lon, S_lat, src_crs=ccrs.Geodetic())\n",
+ "x0, y0 = EASEGrid2.transform_point(W_lon, N_lat, src_crs=ccrs.Geodetic())\n",
+ "\n",
+ "x0, x1, y0, y1"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "d1e9f690-28cb-4e6f-ab82-b740347e25f5",
+ "metadata": {},
+ "source": [
+ "We can now subset the `soil_moisture` grids along the `x` and `y` dimensions using the `.sel` method. We then calculate a mean over these dimensions and plot the result, all within `xarray`. The EASE Grid 2.0 CRS is an equal area projection, so grid cells do not need to be weighted before averaging them."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "id": "1637358c-5161-4da2-954b-9f06f68ac15e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "p = ds.soil_moisture.sel(x=slice(x0,x1), y=slice(y0,y1)).mean(dim=[\"x\",\"y\"]).plot(\n",
+ " ls='', marker='.', ylim=(0,0.25), \n",
+ ")\n",
+ "p[0].axes.set_ylabel(f\"${ds.soil_moisture.attrs['units'].replace('**','^')}$\");\n",
+ "p[0].axes.set_title(\"Soil Moisture over Four Corners Region\");"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a5758aac-a13b-49f8-80b5-f3eebbbd6dae",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.14"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/SMAP/smap_issues_and_solutions.ipynb b/notebooks/SMAP/smap_issues_and_solutions.ipynb
new file mode 100644
index 0000000..ce50771
--- /dev/null
+++ b/notebooks/SMAP/smap_issues_and_solutions.ipynb
@@ -0,0 +1,960 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "91ebd94c-fb02-42a7-9cfe-b02a0da5967a",
+ "metadata": {},
+ "source": [
+ "# Read and plot SMAP data\n",
+ "\n",
+ "## Overview\n",
+ "\n",
+ "This has become an overly long notebook. It was started to demonstrate some more _pythonistic_ streamlined workflows than we show in the SMAP tutorials for accessing, loading and plotting SMAP L3 data. However, what should have been a short and simple demonstration of workflows became an exploration of the shortcomings of the L3 SMAP HDF5 files and workarounds to deal with them. What follows is a hybrid of a tutorial, critique and suggested improvements. I summarize the problems with the data set in this overview section. Please see the code and plots below for examples.\n",
+ "\n",
+ "The tutorials use the SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture, Version 8 (SPL3SMP, DOI:10.5067/OMHVSRGFX38O).\n",
+ "\n",
+ "[Data set landing page](https://nsidc.org/data/spl3smp/versions/8) \n",
+ "[User Guide](https://nsidc.org/sites/default/files/spl3smp-v008-userguide.pdf)\n",
+ "\n",
+ "### Problems with the L3 SMAP Data\n",
+ "\n",
+ "This list is not exhaustive. It is informed by trying to describe workflows to open, read and plot the data contained in the files using current, standard tools in the geospatial python stack. I suspect that the same problems and frustrations would be encountered if other software tools and programming languages were used.\n",
+ "\n",
+ "The critique is also inspired by the belief that self-desribing file formats, conventions such as CF and COARDS, along with software tools designed to take advantage of these file formats and conventions, are there to make the working with data simple, allow scientists to start analysis sooner. Ad-hoc file structures and incomplete (or inaccurate) metadata _\"break\"_ these tools, workflows. Often the _forensic investigations_ required to track down the necessary information to \"fix\" problems introduced by non-conforming files is time consuming. The following quote from the CF Conventions makes this point well.\n",
+ "\n",
+ ">The purpose of the CF conventions is to require conforming datasets to contain sufficient metadata that they are self-describing in the sense that each variable in the file has an associated description of what it represents, including physical units if appropriate, and that each value can be located in space (relative to earth-based coordinates) and time.\n",
+ ">\n",
+ ">An important benefit of a convention is that it enables software tools to display data and perform operations on specified subsets of the data with minimal user intervention. It is possible to provide the metadata describing how a field is located in time and space in many different ways that a human would immediately recognize as equivalent. The purpose in restricting how the metadata is represented is to make it practical to write software that allows a machine to parse that metadata and to automatically associate each data value with its location in time and space. It is equally important that the metadata be easy for human users to write and to understand.\n",
+ "\n",
+ "1. **The HDF5 files do not contain sufficient information for the data to be geolocatable**. The data are in a projected coordinate reference system (CRS) - EASE-Grid 2.0 - on a 406 x 964 grid with a 36 km grid cell height and width. Although `latitude` and `longitude` 2D grids are included as Datasets, these grids are masked, so that coordinates are not available for all grid cells. Coordinate grids **should not** have missing values. Furthermore, standard tools in the Geoscience stack, such as `xarray`, do not allow coordinate variables to have missing data in accordance with conventions such as CF and COARDS.\n",
+ "2. The data have a projected CRS, the projected coordinates should be included in the file. These would be vectors containing `x` and `y` in meters.\n",
+ "3. There are no named dimensions. Standard tools (and humans) have no way to associate dimension variables (dimension scales in HDF5 terms) with data variables.\n",
+ "4. There is no information about the CRS contained in the file. It may be in the xml but modern tools expect to find it as a variable. It should be included at least as a WKT string and an EPSG code.\n",
+ "5. The names of Datasets have an inconsistent naming convention. Datasets in the `Soil_Moisture_Retrieval_Data_PM` Group have the suffix `_pm`. Datasets in the `Soil_Moisture_Retrieval_Data_AM` group do not. This makes programmatic workflows more complicated because users have to \"code around\" the differences in file names. For example: `if spass == 'PM': filename = f\"{variable}_{spass.lower()} \\\\ else: filename = variable` instead of `filename = f\"{variable}_{spass.lower()}\"`.\n",
+ "6. Some of the attribute data is incorrect. See the `landcover_class` for an example. The `long_name` attribute is used to describe the dimensions. This is the wrong place to describe this. `long_name` should be reserved for the name of the variables. If named dimensions had been created there would be no need to describe the dimensions. Moreover, dimensions are listed as longitude, latitude and IGBP land cover type. Longitude and latitude cannot be dimensions. The data arrays are in projected coordinates. Longitude and latitude are 2D arrays and, therefore, it is impossible to assign them as dimensions, which by definition, are 1D vectors. The dimensions should be x and y or easting and northing. \n",
+ " \n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "b35a4034-033a-419c-97a1-fb3a4234e799",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from pathlib import Path\n",
+ "\n",
+ "import earthaccess\n",
+ "import h5py\n",
+ "import rioxarray\n",
+ "import xarray as xr\n",
+ "import numpy as np\n",
+ "\n",
+ "from affine import Affine\n",
+ "from pyproj import CRS\n",
+ "\n",
+ "import matplotlib.pyplot as plt\n",
+ "import cartopy.crs as ccrs\n",
+ "import cartopy.feature as cfeature\n",
+ "\n",
+ "from pprint import pprint"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "58a65b4d-42a7-49b7-807f-150daf3928e5",
+ "metadata": {},
+ "source": [
+ "## Search for SMAP data\n",
+ "\n",
+ "We will use `earthaccess` to search for SMAP Level 3 files for March 2017. The first step is to authenticate using `earthaccess.login`. We can then use `search_data` to search for data."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "04c73ccc-c8dc-4dcb-84bf-962f8b0e6c84",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "auth = earthaccess.login()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "1b04c8b8-fe00-4452-9989-8a32012ed338",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "results = earthaccess.search_data(\n",
+ " short_name = 'SPL3SMP',\n",
+ " version = '009',\n",
+ " cloud_hosted = False,\n",
+ " temporal = ('2017-03-01','2017-03-31')\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "dd8b84a6-6085-40a1-bebf-792ad2605549",
+ "metadata": {},
+ "source": [
+ "## Download files\n",
+ "\n",
+ "If you haven't already, we'll download the files to a local directory. This is defined in the `DOWNLOAD_PATH` constant. In this example, we'll use the `Path` object from the [`pathlib`](https://docs.python.org/3/library/pathlib.html) package to build a path to a directory `smap_data` under the current working directory. `Path` objects have methods to return the current working directory `.cwd()`, make directories `.mkdir()`, and search using globbing `.glob()`.\n",
+ "\n",
+ "
\n",
+ "Tip: If you want to download files to a different directory change the cell below to \n",
+ "\n",
+ "```\n",
+ "DOWNLOAD_PATH = Path(\"path-to-download-directory\")\n",
+ "```\n",
+ "
\n",
+ "\n",
+ "`earthaccess.download` checks if the files already exist in the local download directory."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "b9f11521-54ff-4dd0-8823-cea9d8bba6d3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#rm smap_data/*.h5"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "4d7cb4e8-0854-4dfa-b2a0-28fffca94305",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "DOWNLOAD_PATH = Path.cwd() / \"smap_data\"\n",
+ "DOWNLOAD_PATH.mkdir(parents=True, exist_ok=True) # creates parents if they don't exist and fails silently if path exists\n",
+ "\n",
+ "smap_files = earthaccess.download(results, str(DOWNLOAD_PATH))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "2696e5a4-92be-4860-a84b-7ea387ea25bf",
+ "metadata": {},
+ "source": [
+ "I then use `.glob('*.h5')` to get a list of SMAP files in the `DOWNLOAD_PATH`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a474c513-0473-43eb-b2d1-f386c52272b5",
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [],
+ "source": [
+ "smap_files = list(DOWNLOAD_PATH.glob('*.h5')) # .glob() returns a generator list() turn it into a list \n",
+ "smap_files"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "4f49af27-5890-4b0e-807c-d7394594d008",
+ "metadata": {},
+ "source": [
+ "## Read data from HDF5 file using `h5py`\n",
+ "\n",
+ "HDF5 files are hierarchical data structures that consist of _Groups_ and _Datasets_. Groups contain sub-groups and Datasets. Datasets are equivalent to Variables in NetCDF files. Both Groups and Datasets can have attributes. Datasets are multidimensional arrays similar to numpy arrays and have `shape`, `ndim`, `dtype` attributes the same as numpy arrays.\n",
+ "\n",
+ "The best way to explore an HDF5 file is to use a \"viewer\". [MyHDF5](https://myhdf5.hdfgroup.org/) is one such tool. You can upload a file from your local machine or point to a URL for a file."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "83ea9670-0d39-4ab2-bc10-bcfb2d05fa46",
+ "metadata": {},
+ "source": [
+ "We open an HDF5 file using `h5py.File`, which returns a file object. This file object is also the _root_ group for the file. "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "2113e065-5aa3-4a9f-a537-170cd92e69ec",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "root = h5py.File(smap_files[0], 'r')\n",
+ "root"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "f16419b2-304b-4d38-978c-e47ba23d9c31",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "root.keys()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "ce4f263a-0233-42e4-a904-658c94a7cb07",
+ "metadata": {},
+ "source": [
+ "_Add examples of accessing Groups by path, accessing attributes and data arrays, as well as dimensions_\n",
+ "\n",
+ "A HDF5 `Dataset` can be accessed using a similar syntax to how you would access a file on your hard drive. For example we can access the `soil_moisture` data set for the AM pass with the following command. "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "bf41372e-df90-4a42-adf4-ebab4b210909",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "root['Soil_Moisture_Retrieval_Data_AM/soil_moisture']"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "8a4b57b9-593e-4634-9c85-91fd150e4c72",
+ "metadata": {},
+ "source": [
+ "We can see that this is a data array with shape 406 x 964 containing 32 bit floating point numbers (`\n",
+ "Tip: The non-numerical data attributes are byte strings, these can be converted to strings using `decode`\n",
+ ""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "adc57f9e-6f08-460f-b15b-eadfde6d3d74",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "for key, value in root['Soil_Moisture_Retrieval_Data_AM/soil_moisture'].attrs.items():\n",
+ " print(f\"{key}: {value}\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1c6b8ff0-e329-4505-a8e1-3e607a9887ea",
+ "metadata": {},
+ "source": [
+ "## _Optional_: An alternative way to access Groups and Datasets\n",
+ "\n",
+ "An alternative way to list `Groups` and `Datasets` in the file is to use the `visit` and `visititems` methods. Both these methods iterate over the objects in a file. They take a function name as an argument. `visit` takes a function with the form:\n",
+ "\n",
+ "```\n",
+ "myfunc()\n",
+ "```\n",
+ "\n",
+ "This function can be used to return a list of all Groups and Datasets in the file. In the example below we create an empty list and then pass the `list.append` method, which is a function, to visit."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "91d27b73-0d8b-4ebe-baed-c3c5324836ec",
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [],
+ "source": [
+ "with h5py.File(smap_files[0], 'r') as root:\n",
+ " list_of_names = []\n",
+ " root.visit(list_of_names.append)\n",
+ "list_of_names"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "5e44f69e-1dd6-44eb-9aaf-744aeb888f76",
+ "metadata": {},
+ "source": [
+ "We can also write a function to look for members with albedo in the name. "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "147e1bd7-07ee-4609-9943-cec5ca527a93",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "with h5py.File(smap_files[0], 'r') as root:\n",
+ " soil_moisture = root['Soil_Moisture_Retrieval_Data_AM/soil_moisture'][:]\n",
+ "soil_moisture"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "06263ffa-d2fb-4e12-86d3-e2cfff25677e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "list_of_names = []\n",
+ "def get_albedo(name):\n",
+ " if 'albedo' in name.lower():\n",
+ " list_of_names.append(name)\n",
+ "\n",
+ "root.visit(get_albedo)\n",
+ "list_of_names"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "17dc5739-e32f-42e0-af28-55e66bf6eebe",
+ "metadata": {},
+ "source": [
+ "`visititems` not only takes a function with the member name but also the actual Group or Dataset object.\n",
+ "\n",
+ "```\n",
+ "myfunc(name, obj)\n",
+ "```\n",
+ "\n",
+ "we can use this to get particular variables or do some form of processing based on whether the object is a Group or a Dataset.\n",
+ "\n",
+ "In the example below, we will extract the data arrays for albedo variables for the AM pass. I first look for `AM` in the name and then check if the name contains `albedo` as in the `visit` example above. I only want `Datasets`. `Groups` do not contain data arrays. To do this, I use the `isinstance` function that is part of the standard library. `isinstance` take `obj` as an argument and checks to see if it is of the type `h5py.Dataset`.\n",
+ "\n",
+ "If all three of these conditions are `True`, I then want to write the variables to a dictionary. I want to use the name of the `Dataset` as the key for each data array. I can split the `name` string on the `/` character and take the last element of the list that is returned. To assign the data array and not the `Dataset` object, I use the `[:]` syntax. "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "c17e3b4f-5283-4d1d-96e1-965a623e361c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "dict_of_vars = {}\n",
+ "def get_vars(name, obj):\n",
+ " if ('AM' in name) & ('albedo' in name) & isinstance(obj, h5py.Dataset):\n",
+ " dict_of_vars[name.split('/')[-1]] = obj[:]\n",
+ "\n",
+ "root.visititems(get_vars)\n",
+ "dict_of_vars"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "084a4e87-ad0b-4379-af68-bfd8faf5f9bc",
+ "metadata": {},
+ "source": [
+ "The `h5py.File` opens the file. The file needs to be closed, otherwise it remains in memory. If you are reading multiple files, this could lead to memory problems."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "ded43124-14cc-4be6-b690-be4f7f3bcceb",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "root.close()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1304aa23-5196-4c6b-b92d-d2ed050f3fe0",
+ "metadata": {},
+ "source": [
+ "## Creating a georeferenced `xarray.Dataset` for a subset of variables from an HDF5 SMAP file\n",
+ "\n",
+ "Fully georeferenced data sets are required for Earth science analysis workflows. This may be as simple as plotting a map. You may want to transform the data so it can be used with another data set, or you may want to perform some geospatial subsetting.\n",
+ "\n",
+ "Unfortunately, the SMAP HDF5 files do not contain sufficient information to geolocate data on the Earth surface. This is is the case both for using the data with software tools to display or manipulate the data, and for humans trying to understand the data. The following example shows:\n",
+ "\n",
+ "1. how to read a subset of `Datasets` (variables) from the HDF5 file and create a geospatially aware `xarray.Dataset`;\n",
+ "2. how to mask missing data;\n",
+ "3. how to add coordinate information to the dataset;\n",
+ "4. how to add a coordinate reference system information the dataset."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "aa714ea3-2dd2-4831-b482-a0421e0979f9",
+ "metadata": {},
+ "source": [
+ "`xarray` can read a group from an HDF5 file. In the following example, we read the `Soil_Moisture_Retrieval_Data_AM` group."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "759e1df8-eb4f-472d-8175-69e634c30503",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "gds = xr.open_dataset(smap_files[0], group='Soil_Moisture_Retrieval_Data_AM') #, decode_coords='all', decode_cf=True)\n",
+ "gds"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "05d558e4-448d-4c7a-a188-ea5cf27dc124",
+ "metadata": {},
+ "source": [
+ "53 variables are loaded from `Soil_Moisture_Retrieval_Data_AM`. However, we can immediately see some issues. The dimensions are named `phony_dim_0`, `phony_dim_1`, and `phony_dim_2`, which is not much help. This is because no dimensions are assigned to Datasets so `xarray` has to generate some dummy variables. The same problem arises if the Python binding for HDF5 library, `h5py`, were used.\n",
+ " \n",
+ "Let's change the names of the dimensions to something useful and meaningful. The first thing is to figure out what the dimensions are. This is more diffcult than is should be. Some of the metadata is wrong. Some is confusing. The description of the `landcover_class` offers some information, albeit misleading, but it is a clue.\n",
+ "\n",
+ "> An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)\n",
+ "\n",
+ "This description states that the dimensions of the landcover_class array are longitude, latitude and IGBP land cover class. The data are in projected coordinates (EASE Grid 2.0) **so longitude and latitude cannot be dimensions**. Longitude and latitude must be 2D arrays for a projected dataset. However, x and y or easting and northing are likely candidates. However, the 3rd dimension appears to be land cover class. Plotting the `soil_moisture` variable also shows that `phony_dim_1` is the x-dimension and `phony_dim_0` is the y-dimension in cartesian coordinates. So we'll rename the coordinates:\n",
+ "\n",
+ " - `phony_dim_0 --> y`\n",
+ " - `phony_dim_1 --> x`\n",
+ " - `phony_dim_2 --> igbp_class`\n",
+ "\n",
+ "We can do this using `rename_dims`, which takes a dictionary as an argument, where keys are the old dimension name and values are the new dimension name."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a445433e-d160-4ca2-9a58-a0b74ccf348b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "gds = gds.rename_dims({'phony_dim_0': 'y', 'phony_dim_1': 'x', 'phony_dim_2': 'igbp_class'})\n",
+ "gds"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "de673df1-483f-47b0-9e9a-c1aadd711629",
+ "metadata": {},
+ "source": [
+ "Another issue is that there are no coordinate variables, again because the HDF5 file was not created with any. Inspecting the variables, we see that there are two possible candidate coordinate variables: `latitude` and `longitude`. So let's plot them."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "96f26e1e-2c6d-4f57-bf51-72653e2c76d9",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "gds.latitude.plot()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "fe9bc187-b64d-414d-9074-5bc5e33c3774",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "print(gds.latitude.min(), gds.latitude.max())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "ba404a65-2dd2-4f1b-a538-40861dfcd199",
+ "metadata": {},
+ "source": [
+ "If we plot both latitude and soil_moisture, we can see that latitude values have been masked with -9999. where there are no valid data values. **This is not a good or sensible approach because latitude and longitude are coordinates. As long as latitude and longitude values are between -90 and 90, and -180 and 180 (or 0 and 360), they are valid coordinates. Under NetCDF and CF conventions, coordinate values should not have missing values. We also need coordinates for all grid cells for plotting and other operations.** "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "18d8326c-fea7-4fb5-a7bc-e38f4bbfdd05",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "fig, ax = plt.subplots(2, 1)\n",
+ "gds.latitude.plot(ax=ax[0]);\n",
+ "gds.soil_moisture.plot(ax=ax[1])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "43d5222c-82ba-4c58-83b5-0b13c1919ec2",
+ "metadata": {},
+ "source": [
+ "Neither the plot of latitude nor the minimum and maximum values look as we would expect. We expect latitude to be in the range of -90 to +90. The maximum is actually in this range but the minimum is -9999., which is suspiciously like a `_FillData` or missing data value. We would also expect the image to show a smooth field that only varies in the vertical direction, e.g. from -90. to 90. or some similar range. Instead it shows a set of lozenges.\n",
+ "\n",
+ "Let's set the `_FillValue` attribute for latitude to `-9999`. In `xarray`, we have to use `where` to apply a mask everywhere a condition is not `True`. Here we set the condition to be _not equal to -9999._ To save time and errors later, we also set the `encoding` entry for `fillvalue` to -9999.\n",
+ "\n",
+ "
\n",
+ "`encoding` is a dictionary of parameters that defines how data are \"encoded\" in the file. It includes information about how data are compressed, chunked, the _FillValue, and data type. Saving the `encoding` is not strictly necessary unless you want to write the data to a new file. We'll follow these steps here to demonstrate how to preserve the encoding data. \n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "c65618de-eb3d-4f07-804c-81f0199a3ed4",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "print(gds.latitude.encoding)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "efc06b5a-fe82-4732-8753-f589485bb3f5",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "fillvalue = -9999.\n",
+ "\n",
+ "# `where` does not preserve encoding, so we have to copy first\n",
+ "encoding = gds.latitude.encoding\n",
+ "# Apply fillvalue mask\n",
+ "gds['latitude'] = gds.latitude.where(gds.latitude != fillvalue)\n",
+ "# we copy the encoding back to DataArray\n",
+ "gds.latitude.encoding = encoding\n",
+ "# ...and update encoding to include fillvalue\n",
+ "gds.latitude.encoding['fillvalue'] = fillvalue"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "511b2d12-c6ce-4fc4-b924-d5b3e4b13cf9",
+ "metadata": {},
+ "source": [
+ "Now when we check the range of the latitude values, we see that the range is between -83.63... and 83.63... as we expect."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "ec868a8e-bf13-4967-bde6-02cc2b07738e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "print(gds.latitude.min(), gds.latitude.max())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "5acf9bca-d60d-4d34-9618-7d33e7236772",
+ "metadata": {},
+ "source": [
+ "Plotting the data again, we see that latitude values are within the expected range but that hasn't solved the missing data problem."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "c7d6df08-b03f-465a-bb21-d6a68665fde2",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "fig, ax = plt.subplots(2, 1)\n",
+ "gds.latitude.plot(ax=ax[0]);\n",
+ "gds.soil_moisture.plot(ax=ax[1])"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "id": "efc6edf9-0555-4256-86c7-c6527c9746c7",
+ "metadata": {},
+ "source": [
+ "#### Adding coordinates\n",
+ "\n",
+ "There are no useful coordinate values. If we plotted `longitude` we would see the same problem, and beside we need both latitude and longitude. As noted above, the files do not include complete information about the coordinate reference system or the grid definition. So we need to do some data sleuthing.\n",
+ "\n",
+ "Tables 4 and 5 in the [User Guide](https://nsidc.org/sites/default/files/spl3smp-v008-userguide.pdf) provide geospatial information. Further information on EASE Grids can be found on [A Guide to EASE Grids page](https://nsidc.org/data/user-resources/help-center/guide-ease-grids).\n",
+ "\n",
+ "
\n",
+ "Note: The ATBD for the L3 SMP data gives the data array dimensions as 406 x 963.\n",
+ "
\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "3d642bf9-c8fb-431d-8467-7720a3378081",
+ "metadata": {},
+ "source": [
+ "The CRS and grid definition are independent. The CRS defines how projected coordinates, usually in meters, relate to geographic latitude and longitude. The grid definition relates how image coordinates (columns and rows) map to the projected coordinates. The Guide to EASE Grids has 8 grid definitions, ranging from 1 km to 36 km cell sizes, for the Global EASE-Grid 2.0 CRS (EPSG:9633). We could define many more grid definitions. For more information on CRS, map projections and grids see [_Link to be added_]().\n",
+ "\n",
+ "In the [table](https://nsidc.org/data/user-resources/help-center/guide-ease-grids#anchor-10) for the 36 km Global EASE-Grid 2.0 we are given the height and width of each grid cell, and the x and y coordinates of the upper-left corner of the upper-left grid cell. We can see that the 36 km grid cell size is not exact. In fact the value the table gives is not exact. The actual value runs to 9 decimal places. This is because the grid cell height and width of the global grid were defined so that an exact number of cells span the equator {@brodzik_ease}. This is not necessary for polar grids.\n",
+ "\n",
+ "
\n",
+ "Tip: Exact definitions of CRS, projection and grid parameters can be found in the Grid Parameter Definition (gpd) files in the [`mapxmaps` GitHub repository](https://github.com/nsidc/mapxmaps). These gpd files have a somewhat esoteric format, so might take a little bit to understand. It is important that the grid definition is exact because we cannot merge datasets if the coordinates do not match, even to the 9th decimal place.\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "78dc5886-d10a-4ca7-b2df-e10ac1de0c8d",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "grid_cell_width = 36032.220840584\n",
+ "grid_cell_height = -36032.220840584\n",
+ "x_upper_left_corner = -17367530.4451615\n",
+ "y_upper_left_corner = 7314540.8306386"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "927e8b99-28d0-46d0-9c0e-8f9fd6223861",
+ "metadata": {},
+ "source": [
+ "The projected coordinates of a grid cell can be found using the following formulas:\n",
+ "\n",
+ "$$\n",
+ "x = (grid\\_cell\\_width \\times row) + x\\_upper\\_left\\_corner\n",
+ "$$\n",
+ "$$\n",
+ "y = (grid\\_cell\\_height \\times column) + y\\_upper\\_left\\_corner)\n",
+ "$$\n",
+ "\n",
+ "This equations assumes that the origin of the image coordinates start at row=0. and column=0. in the upper-left corner of the upper-left grid cell. So the center of the upper-left grid cell is row=0.5 and column=0.5. Adding 0.5 to row and column indices solves this problem.\n",
+ "\n",
+ "We could write a function to return (x, y) coordinates for (column, row) image coordinates using the equations above. Or we can use the `Affine` class from the `affine` package to define an affine matrix. This is what we'll do below. "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "feed97dc-b521-4240-9446-8811c8694aeb",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "transform = Affine(grid_cell_width, 0.0, x_upper_left_corner, \n",
+ " 0.0, grid_cell_height, y_upper_left_corner)\n",
+ "transform"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "08669cb5-4848-41e7-a08b-0b3e71d21f40",
+ "metadata": {},
+ "source": [
+ "This then allows us to calculate x and y coordinates from column and row indices using matrix multiplication."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "98bd706e-78fc-4cc5-a11a-ff0cb22ca93c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "transform * (964, 406)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "549fc024-b032-406a-acdc-f7a76dea9e49",
+ "metadata": {},
+ "source": [
+ "We'll define vectors for the row and column indices of the grid cell centers, and then use the `transform` matrix to get x and y coordinates. These only need to be vectors as well because each column will have the same row indices and each row will have the same column indices. We'll use the `numpy.arange` function to do and start the range at 0.5 to offset the row and column indices for grid cell centers by 0.5."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "4a314543-1a0c-482d-86d3-5905b6b11b2b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "nrows, ncolumns, nclass = gds.dims['y'], gds.dims['x'], gds.dims['igbp_class'] #data_vars['soil_moisture'][1].shape\n",
+ "row = np.arange(0.5, nrows)\n",
+ "column = np.arange(0.5, ncolumns)\n",
+ "\n",
+ "x, _ = transform * (column, 0.5)\n",
+ "_, y = transform * (0.5, row)\n",
+ "igbp_class = np.arange(nclass) # Add attributes"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "85c7ee2c-05e7-4f00-a30c-e8697c91499e",
+ "metadata": {},
+ "source": [
+ "We need to assign `x`, `y`, and `igbp_class` as coordinates. This should be sufficient for plotting. However, if we want to reproject the data we should define the CRS and spatial coordinates, and transform. We do this using `rioxarray` accessors."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "4fda308a-6433-4174-b14e-b162a71ae729",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "gds = gds.assign_coords(x=x, y=y, igbp_class=igbp_class)\n",
+ "\n",
+ "gds.rio.write_crs(6933, grid_mapping_name='wgs84_easegrid2_global', inplace=True)\n",
+ "gds.rio.set_spatial_dims(x_dim='x', y_dim='y', inplace=True)\n",
+ "gds.rio.write_coordinate_system(inplace=True)\n",
+ "gds.rio.write_transform(transform)\n",
+ "gds.rio.write_grid_mapping('wgs84_easegrid2_global', inplace=True)\n",
+ "gds"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "29cb574a-7f44-4924-b275-0fce25606569",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "print(gds.latitude.rio.grid_mapping)\n",
+ "print(gds.rio.bounds())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "70f54aaa-a1fc-46a2-826d-737bd71aa386",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "EASEGrid2 = ccrs.epsg(gds.rio.crs.to_epsg())\n",
+ "\n",
+ "fig = plt.figure(figsize=(12,7))\n",
+ "ax = fig.add_subplot(projection=EASEGrid2)\n",
+ "\n",
+ "ax.coastlines()\n",
+ "gds.soil_moisture.plot(ax=ax,)\n",
+ "ax.set_title('Soil Moisture');"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "ae67f0aa-b858-4ee1-aa29-3961df9c54cc",
+ "metadata": {},
+ "source": [
+ "## Extra Stuff to be refined"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "1d00eaa2-7b6e-477a-b71c-6d90d09aa0a2",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "grid_mapping_name = \"WGS84_NSIDC_EASEGrid_2.0_Global\"\n",
+ "datasets = ['Soil_Moisture_Retrieval_Data_AM/soil_moisture', 'Soil_Moisture_Retrieval_Data_AM/retrieval_qual_flag']\n",
+ "data_vars = {}\n",
+ "dims = ['y', 'x']\n",
+ "with h5py.File(smap_files[0]) as root:\n",
+ " for dataset in datasets:\n",
+ " ds = root[dataset]\n",
+ " path = ds.name\n",
+ " name = path.split('/')[-1]\n",
+ " attrs = {k: (v.decode('UTF-8') if hasattr(v, 'decode') else v) for k, v in dict(ds.attrs).items()}\n",
+ " attrs['grid_mapping'] = grid_mapping_name # Add so that dataset is CF-compliant and geoferenced\n",
+ " data_vars[name] = (dims, ds[:], attrs)\n",
+ "\n",
+ "data_vars\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "39afd220-8f13-4993-a25a-5ec0513476be",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "plt.imshow(data_vars['soil_moisture'][1])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "1d7878b4-eec8-4214-8479-df2a8aab1016",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data_vars['soil_moisture'][1].shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "5329fb83-8b95-42db-8ac1-7efe555a0c4f",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "plt.pcolormesh(x, y, data_vars['soil_moisture'][1])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "083d7efa-0fb3-418b-93b6-04132a0375fe",
+ "metadata": {},
+ "source": [
+ "We also need to define the CRS. We know that the CRS has the EPSG code 6933. We can use `pyproj` to get the CRS definition."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "fcbd0150-c72c-453b-8045-489f702b8349",
+ "metadata": {},
+ "source": [
+ "Base on [CF-Conventions](http://cfconventions.org/cf-conventions/cf-conventions.html#grid-mappings-and-projections), we add the CRS as a variable with the same name as we used for the `grid_mapping` attribute of each data variable. We define this variable as an integer. The grid mapping information is then copied as attributes for that variable. We use the `to_cf()` method of the `pyproj.CRS` object to do this."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "037dc012-8f52-4144-b929-fb3169dcebeb",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds = xr.Dataset(data_vars, coords={'x': x, 'y': y})\n",
+ "ds"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "667dbefd-1a3e-4b9f-94a7-dfc0cb314961",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds.rio.write_crs(6933, inplace=True)\n",
+ "\n",
+ "#ds[grid_mapping_name].attrs = crs.to_cf()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "58167732-336b-49a1-b915-2b3683336226",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds =xr.decode_cf(ds)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "f479de98-57b8-401d-8ae6-f5372c835dc1",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds.soil_moisture.plot()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "c98fef70-b2eb-4e17-90f1-58d8e93c2f56",
+ "metadata": {},
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.14"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/SMAP/smap_rasterio_issues.ipynb b/notebooks/SMAP/smap_rasterio_issues.ipynb
new file mode 100644
index 0000000..8f35355
--- /dev/null
+++ b/notebooks/SMAP/smap_rasterio_issues.ipynb
@@ -0,0 +1,266 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "12d41e1b-020f-431d-8916-44b79b9bab33",
+ "metadata": {},
+ "source": [
+ "# Issues reading SMAP with different xarray backends\n",
+ "\n",
+ "This notebook explores [Issue 650](https://github.com/corteva/rioxarray/issues/650) for rioxarray. The user finds that the y-axis is flipped when they use `xarray` with `rioxarray` to read SMAP L4 data but not when they use the `netcdf4` backend.\n",
+ "\n",
+ "They use https://n5eil01u.ecs.nsidc.org/SMAP/SPL4SMGP.007/2015.03.31/SMAP_L4_SM_gph_20150331T013000_Vv7032_001.h5 as an example."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "e157b689-ed9b-49dc-83cf-ed046f57d5ef",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from pathlib import Path\n",
+ "import warnings\n",
+ "\n",
+ "import xarray as xr\n",
+ "import rioxarray\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "print(xr.__version__)\n",
+ "print(rioxarray.__version__)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "ad25ca3c-9aa4-4123-8af0-5a09ccf5bf46",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "filepath = Path(\"smap_data/SMAP_L4_SM_gph_20150331T013000_Vv7032_001.h5\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "f31063b9-0b3a-4a3c-b34f-86a3ce59c898",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "engine = \"netcdf4\"\n",
+ "ds = xr.merge([\n",
+ " xr.open_dataset(filepath, engine=engine),\n",
+ " xr.open_dataset(filepath, group='Geophysical_Data', engine=engine)['precipitation_total_surface_flux'],\n",
+ " ])\n",
+ "ds"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "2fe7bdca-12de-4674-b1c3-e55ac24e7627",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds.precipitation_total_surface_flux.plot()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "7cd943e4-7c2e-41c6-9ed1-ea45c90ff015",
+ "metadata": {},
+ "source": [
+ "With `h5netcdf`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "fd8a2568-0893-4375-8b34-0b2e8b816ac2",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "engine=\"h5netcdf\"\n",
+ "ds = xr.merge([\n",
+ " xr.open_dataset(filepath, engine=engine, phony_dims=\"sort\"),\n",
+ " xr.open_dataset(filepath, group='Geophysical_Data', engine=engine, phony_dims=\"sort\")['precipitation_total_surface_flux'],\n",
+ " ])\n",
+ "print(ds)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "105606bc-6c6b-4ffd-8bbc-23e40db3f065",
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [],
+ "source": [
+ "%%capture \n",
+ "# Avoid a string of NotGeoreferencedWarnings\n",
+ "# /home/apbarret/mambaforge/envs/nsidc-tutorials/lib/python3.9/site-packages/rasterio/__init__.py:304: NotGeoreferencedWarning: \n",
+ "# Dataset has no geotransform, gcps, or rpcs. The identity matrix will be returned.\n",
+ "# dataset = DatasetReader(path, driver=driver, sharing=sharing, **kwargs)\n",
+ "engine = \"rasterio\"\n",
+ "ds_rasterio = xr.open_dataset(filepath, engine=engine)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "fe9df3a8-b6f9-459f-b74c-44c6b1495fcb",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "print(ds_rasterio.x, ds_rasterio.y)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "ca842d36-9d4e-4ce7-8005-94cdf96875af",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds_rasterio.cell_lat.plot()\n",
+ "plt.savefig('smap_h5_cell_lat.png')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "66ea978b-26ae-496a-9bdf-e94843dfd035",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds_rasterio.cell_lat.squeeze().plot.imshow(origin=\"upper\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "f2d01026-e6dc-49a2-963f-6143157eabca",
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [],
+ "source": [
+ "!h5dump -d x {filepath}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "0b5c0ea7-5693-4745-ae37-152b354504d5",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds_rioxarray = xr.merge([\n",
+ " xr.open_dataset(filepath, decode_coords=\"all\"),\n",
+ " xr.open_dataset(filepath, group='Geophysical_Data', decode_coords=\"all\")['precipitation_total_surface_flux'],\n",
+ "])\n",
+ "\n",
+ "print(ds_rioxarray)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a70d9fbf-9087-49c5-8e14-c978fba84b26",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds_rioxarray.precipitation_total_surface_flux.plot(vmax=0.001)\n",
+ "plt.savefig('smap_h5_precipitation.png')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "1119929c-2e50-4053-bb84-e5cf441c2526",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds_rioxarray.rio.crs"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a44c287c-c490-4e91-a7a9-c6643c01897f",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds_rioxarray.rio.transform()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "4056a4fe-3f45-4617-a73e-bc8ba52a8dc2",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds_rioxarray.rio.reproject?"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "7b855823-9181-4100-ba58-6b8fad7a7dd1",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds.cell_row.plot()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "02710743-1835-495f-8d40-a8750ab029b7",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds.precipitation_total_surface_flux.plot.imshow()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "2074ce5c-7ef5-4458-a52d-d7211ed2231f",
+ "metadata": {},
+ "source": [
+ "Try writing a dummy geotiff and then read it back in"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "f79ff594-0a8f-44cf-9eb8-731d2e714eec",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.14"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/SMAP/working_with_smap_in_xarray.ipynb b/notebooks/SMAP/working_with_smap_in_xarray.ipynb
index d67b2ec..669860d 100644
--- a/notebooks/SMAP/working_with_smap_in_xarray.ipynb
+++ b/notebooks/SMAP/working_with_smap_in_xarray.ipynb
@@ -11,15 +11,11 @@
"\n",
"### Introduction\n",
"\n",
- "This notebook demonstrates searching for, downloading, reading and plotting SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture data using `earthaccess`, `xarray` and `cartopy`. `earthaccess` makes searching for and downloading NASA Earth science data easy. `xarray` is a commonly used, high-level package for working with n-dimensional gridded data. It makes reading HDF5 data easy and simplifies common Earth and atmospheric science workflows. `cartopy` provides a simple plotting interface to display geospatial data and create maps complete with country, state and outher topographic features. Finally, we demonstrate how to transform and resample the data using `rioxarray`, an add-on for `xarray` that brings many of the geospatial functions from `rasterio` to n-dimensional data.\n",
+ "This notebook demonstrates searching for, downloading, reading and plotting SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture data using `earthaccess`, `xarray` and `cartopy`. `earthaccess` makes searching for and downloading NASA Earth science data easy. `xarray` is a commonly used, high-level package for working with n-dimensional gridded data. It makes reading HDF5 data easy and simplifies common Earth and atmospheric science workflows. `cartopy` provides a simple plotting interface to display geospatial data and create maps complete with coastlines, country and state boundaries, and other topographic features. Finally, we demonstrate how to transform and resample the data using `rioxarray`, an add-on for `xarray` that brings many of the geospatial functions from `rasterio` to n-dimensional data.\n",
"\n",
- "To enable any of these functions `xarray.Datasets`, one of the two data structures used in `xarray`, `rioxarray.Datasets` expect to have information about the coordinate reference system (CRS), also known as the spatial reference system (SRS), and the coordinate system of the grid. Many datasets that conform to CF-Conventions already contain this information. Unfortunately, the SMAP data files do not contain this information. The tutorial shows how to add this information. It also shows how to fix some other issues with the data.\n",
+ "To use `xarray` and `rioxarray`, we need information about the coordinate reference system (CRS), also known as the spatial reference system (SRS), and the coordinate system of the grid. Many datasets that conform to CF-Conventions already contain this information within the file so that `rioxarray` can read it. Unfortunately, the SMAP data files do not contain this information. The tutorial shows how to add this information and add additional information that makes working with N-dimensional data much easier.\n",
"\n",
- "These issues are common to many datasets. These sections of the tutorial can be thought of as a guide to working with and fixing datasets with missing or inadequate metadata.\n",
- "\n",
- ">The purpose of the CF conventions is to require conforming datasets to contain sufficient metadata that they are self-describing in the sense that each variable in the file has an associated description of what it represents, including physical units if appropriate, and that each value can be located in space (relative to earth-based coordinates) and time.\n",
- ">\n",
- ">An important benefit of a convention is that it enables software tools to display data and perform operations on specified subsets of the data with minimal user intervention. It is possible to provide the metadata describing how a field is located in time and space in many different ways that a human would immediately recognize as equivalent. The purpose in restricting how the metadata is represented is to make it practical to write software that allows a machine to parse that metadata and to automatically associate each data value with its location in time and space. It is equally important that the metadata be easy for human users to write and to understand.\n",
+ "These issues are common to many datasets. These sections of the tutorial can be thought of as a guide to working with and \"fixing\" datasets with missing or inadequate metadata. You can also think of it as a guide to producing CF-compliant data.\n",
"\n",
"The tutorials use the SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture, Version 8 (SPL3SMP, DOI:10.5067/OMHVSRGFX38O).\n",
"\n",
@@ -32,7 +28,7 @@
"By the end of this tutorial you will know how to:\n",
"1. open the SMAP data with `xarray`;\n",
"2. add CRS and coordinate system information;\n",
- "3. fix metadata issues with dataset;\n",
+ "3. add dataset metadata;\n",
"4. plot the data on a map;\n",
"5. transform and resample the data to a new CRS.\n",
"\n",
@@ -55,9 +51,7 @@
"id": "433b3975-71ab-4189-9453-1d38a250b842",
"metadata": {},
"source": [
- "### Import libraries\n",
- "\n",
- "We'll be using tools from the following libraries."
+ "### Import libraries"
]
},
{
@@ -83,11 +77,11 @@
"import earthaccess\n",
"\n",
"# For reading and working with the data\n",
- "import rioxarray\n",
+ "# import rioxarray\n",
"import xarray as xr\n",
"import numpy as np\n",
"\n",
- "# For defining CRS and coordinate system\n",
+ "# For defining CRS and image coordinate system\n",
"from affine import Affine\n",
"from pyproj import CRS\n",
"\n",
@@ -119,23 +113,15 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 6,
"id": "1b04c8b8-fe00-4452-9989-8a32012ed338",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Granules found: 31\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"results = earthaccess.search_data(\n",
" short_name = 'SPL3SMP',\n",
" version = '008',\n",
- " cloud_hosted = False,\n",
+ " cloud_hosted = True,\n",
" temporal = ('2017-03-01','2017-03-31')\n",
")"
]
@@ -162,24 +148,17 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 8,
"id": "4d7cb4e8-0854-4dfa-b2a0-28fffca94305",
"metadata": {},
"outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " Getting 31 granules, approx download size: 0.93 GB\n"
- ]
- },
{
"name": "stderr",
"output_type": "stream",
"text": [
- "QUEUEING TASKS | : 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 31/31 [00:00<00:00, 6426.30it/s]\n",
- "PROCESSING TASKS | : 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 31/31 [01:28<00:00, 2.85s/it]\n",
- "COLLECTING RESULTS | : 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 31/31 [00:00<00:00, 174997.88it/s]\n"
+ "QUEUEING TASKS | : 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 31/31 [00:00<00:00, 7531.04it/s]\n",
+ "PROCESSING TASKS | : 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 31/31 [00:00<00:00, 161519.78it/s]\n",
+ "COLLECTING RESULTS | : 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 31/31 [00:00<00:00, 370437.11it/s]\n"
]
}
],
@@ -195,12 +174,12 @@
"id": "2696e5a4-92be-4860-a84b-7ea387ea25bf",
"metadata": {},
"source": [
- "We can use `.glob('*.h5')` to get a list of SMAP files in the `DOWNLOAD_PATH`. `glob` returns a python generator object. If we want to see the filepaths we can pass this object to the `list()` method, which converts the generator to a list."
+ "The paths to the downloaded files are written to `smap_files`."
]
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 9,
"id": "a474c513-0473-43eb-b2d1-f386c52272b5",
"metadata": {
"scrolled": true
@@ -209,46 +188,45 @@
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]
},
- "execution_count": 6,
+ "execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "smap_files = list(DOWNLOAD_PATH.glob('*.h5'))\n",
"smap_files"
]
},
@@ -259,12 +237,14 @@
"source": [
"## Create a georeferenced `xarray.Dataset` for a subset of variables from an HDF5 SMAP file\n",
"\n",
- "Georeferenced data sets are required for Earth science analysis workflows. This may be as simple as plotting a map. You may want to transform the data so it can be used with another data set, or you may want to perform some spatial subsetting. Each of these tasks requires that the coordinate system of the dataset is known and that there is sufficient information to relate the coordinate system to an actual location on the Earth. The coordinate system may be spherical (_latitude_ and _longitude_) or cartesian (_x_ and _y_), and it may include a _height_ component (sometimes _z_ or atmospheric _level_). _latitude_, _longitude_ and _height_, and _x_, _y_, and _z_ represent the dimensions of the dataset. Other non-geospatial dimensions may also be included. The relationship between the coordinate system and a location on the Earth is defined by the coordinate reference system (CRS), sometimes called a spatial reference system (SRS). This includes a reference ellipsoid and datum, and, if the data are in a projected coordinate system, information about the projection method and projection parameters. Ideally, this information is included in the data file so that software tools can use this information directly to plot and manipulate the data. Including this information in files also makes it very easy for users to undertsand the data.\n",
+ "Georeferenced data sets are required for Earth science analysis workflows. This may be as simple as plotting a map. You may want to transform the data so it can be used with another data set, or you may want to perform some spatial subsetting. Each of these tasks requires that the coordinate system of the dataset is known and that there is sufficient information to relate the coordinate system to an actual location on the Earth. The coordinate system may be spherical (_latitude_ and _longitude_) or cartesian (_x_ and _y_), and it may include a _height_ component (sometimes _z_ or atmospheric _level_). _latitude_, _longitude_ and _height_, and _x_, _y_, and _z_ represent the dimensions of the dataset. Other non-geospatial dimensions may also be included. \n",
"\n",
- "The SMAP HDF5 data files do not contain sufficient information to geolocate data on the Earth surface. We need to add this information so that we can work with the data in `xarray`. We also need to make some changes to how missing data is represented, as well as change some of the attribute values. In the following sections we will:\n",
+ "The relationship between the coordinate system and a location on the Earth is defined by the coordinate reference system (CRS), sometimes called a spatial reference system (SRS). This includes a reference ellipsoid and datum, and, if the data are in a projected coordinate system, information about the projection method and projection parameters. Ideally, this information is included in the data file so that software tools can use this information directly to plot and manipulate the data. Including this information in files also makes it very easy for users to undertsand the data.\n",
+ "\n",
+ "The SMAP HDF5 data files do not contain sufficient information to geolocate data on the Earth surface. We need to add this information so that we can work with the data in `xarray` or other geospatial-aware tools. We will also make some changes to how missing data is represented, as well as change some of the attribute values to make the data CF-Compliant. In the following sections we will:\n",
"\n",
"1. read a subset of `Datasets` (variables) from the HDF5 file;\n",
- "2. add meaning dimension names;\n",
+ "2. add meaningful dimension names;\n",
"3. mask missing data;\n",
"4. add coordinate information to the dataset;\n",
"5. add a coordinate reference system information the dataset."
@@ -292,12 +272,12 @@
"\n",
"`xarray` can only read one group at a time from an HDF5 file. Multiple groups can be read with multiple reads and then concatenate the `xarray.Datasets`. See xarray tricks for HDF5 data [To be added]. Or you can use the [`xarray-datatree`](https://xarray-datatree.readthedocs.io/en/stable/) package.\n",
"\n",
- "In the following example, we read only the `Soil_Moisture_Retrieval_Data_AM` group. This is done by passing the group name using the `group` keyword. If you wanted data for a subgroup or a dataset one or more levels down, the argument passed to `group` would look like a filepath; for example `\"group/subgroup/dataset\"`."
+ "In the following example, we read the `Soil_Moisture_Retrieval_Data_AM` group. This is done by passing the group name using the `group` keyword. If you wanted data for a subgroup or a dataset one or more levels down, the argument passed to `group` would look like a filepath; for example `\"group/subgroup/dataset\"`."
]
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 10,
"id": "759e1df8-eb4f-472d-8175-69e634c30503",
"metadata": {},
"outputs": [
@@ -334,13 +314,14 @@
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
- "html[theme=dark],\n",
- "body[data-theme=dark],\n",
+ "html[theme=\"dark\"],\n",
+ "html[data-theme=\"dark\"],\n",
+ "body[data-theme=\"dark\"],\n",
"body.vscode-dark {\n",
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
- " --xr-border-color: #1F1F1F;\n",
+ " --xr-border-color: #1f1f1f;\n",
" --xr-disabled-color: #515151;\n",
" --xr-background-color: #111111;\n",
" --xr-background-color-row-even: #111111;\n",
@@ -385,7 +366,7 @@
".xr-sections {\n",
" padding-left: 0 !important;\n",
" display: grid;\n",
- " grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+ " grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
"}\n",
"\n",
".xr-section-item {\n",
@@ -393,7 +374,9 @@
"}\n",
"\n",
".xr-section-item input {\n",
- " display: none;\n",
+ " display: inline-block;\n",
+ " opacity: 0;\n",
+ " height: 0;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
@@ -405,6 +388,10 @@
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
+ ".xr-section-item input:focus + label {\n",
+ " border: 2px solid var(--xr-font-color0);\n",
+ "}\n",
+ "\n",
".xr-section-item input:enabled + label:hover {\n",
" color: var(--xr-font-color0);\n",
"}\n",
@@ -426,7 +413,7 @@
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
- " content: '►';\n",
+ " content: \"►\";\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
@@ -437,7 +424,7 @@
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
- " content: '▼';\n",
+ " content: \"▼\";\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
@@ -509,15 +496,15 @@
"}\n",
"\n",
".xr-dim-list:before {\n",
- " content: '(';\n",
+ " content: \"(\";\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
- " content: ')';\n",
+ " content: \")\";\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
- " content: ',';\n",
+ " content: \",\";\n",
" padding-right: 5px;\n",
"}\n",
"\n",
@@ -667,56 +654,75 @@
" stroke: currentColor;\n",
" fill: currentColor;\n",
"}\n",
- "
The column index of the 36 km EASE grid cell that contains the associated data.
valid_max :
963
valid_min :
0
[391384 values with dtype=float32]
EASE_row_index
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The row index of the 36 km EASE grid cell that contains the associated data.
valid_max :
405
valid_min :
0
[391384 values with dtype=float32]
albedo
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_dca
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scah
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-H within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scav
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-V within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
boresight_incidence
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Representative angle between the antenna boresight vector and the normal to the Earth's surface for all footprints within the cell.
units :
degrees
valid_max :
90.0
valid_min :
0.0
[391384 values with dtype=float32]
bulk_density
(phony_dim_0, phony_dim_1)
float32
...
long_name :
A unitless value that is indicative of aggregated bulk_density within the 36 km grid cell.
valid_max :
2.65
valid_min :
0.0
[391384 values with dtype=float32]
clay_fraction
(phony_dim_0, phony_dim_1)
float32
...
long_name :
A unitless value that is indicative of aggregated clay fraction within the 36 km grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
freeze_thaw_fraction
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
grid_surface_status
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Indicates if the grid point lies on land (0) or water (1).
valid_max :
1
valid_min :
0
[391384 values with dtype=float32]
landcover_class
(phony_dim_0, phony_dim_1, phony_dim_2)
float32
...
long_name :
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
[1174152 values with dtype=float32]
landcover_class_fraction
(phony_dim_0, phony_dim_1, phony_dim_2)
float32
...
long_name :
The fraction of the grid cell that contains the most common land cover in that area based on the IGBP landcover map.
valid_max :
1.0
valid_min :
0.0
[1174152 values with dtype=float32]
latitude
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Latitude of the center of the Earth based grid cell.
units :
degrees_north
[391384 values with dtype=float32]
latitude_centroid
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Weighted average of the latitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
longitude
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Longitude of the center of the Earth based grid cell.
units :
degrees_east
[391384 values with dtype=float32]
longitude_centroid
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Weighted average of the longitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
radar_water_body_fraction
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The fraction of the area of the 36 km grid cell that is covered by water based on the radar detection algorithm.
Bit flags that represent the quality of the vertical polarization brightness temperature within each grid cell
[391384 values with dtype=float32]
tb_time_seconds
(phony_dim_0, phony_dim_1)
timedelta64[ns]
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
valid_max :
940000000.0
valid_min :
-999999.9
[391384 values with dtype=timedelta64[ns]]
tb_time_utc
(phony_dim_0, phony_dim_1)
|S24
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in UTC.
[391384 values with dtype=|S24]
tb_v_corrected
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell adjusted for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
tb_v_uncorrected
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell before adjustment for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
vegetation_opacity
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_dca
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scah
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-H retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scav
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-V retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_water_content
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Representative measure of water in the vegetation within the 36 km grid cell.
The column index of the 36 km EASE grid cell that contains the associated data.
valid_max :
963
valid_min :
0
[391384 values with dtype=float32]
EASE_row_index
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The row index of the 36 km EASE grid cell that contains the associated data.
valid_max :
405
valid_min :
0
[391384 values with dtype=float32]
albedo
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_dca
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scah
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-H within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scav
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-V within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
boresight_incidence
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Representative angle between the antenna boresight vector and the normal to the Earth's surface for all footprints within the cell.
units :
degrees
valid_max :
90.0
valid_min :
0.0
[391384 values with dtype=float32]
bulk_density
(phony_dim_0, phony_dim_1)
float32
...
long_name :
A unitless value that is indicative of aggregated bulk_density within the 36 km grid cell.
valid_max :
2.65
valid_min :
0.0
[391384 values with dtype=float32]
clay_fraction
(phony_dim_0, phony_dim_1)
float32
...
long_name :
A unitless value that is indicative of aggregated clay fraction within the 36 km grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
freeze_thaw_fraction
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
grid_surface_status
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Indicates if the grid point lies on land (0) or water (1).
valid_max :
1
valid_min :
0
[391384 values with dtype=float32]
landcover_class
(phony_dim_0, phony_dim_1, phony_dim_2)
float32
...
long_name :
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
[1174152 values with dtype=float32]
landcover_class_fraction
(phony_dim_0, phony_dim_1, phony_dim_2)
float32
...
long_name :
The fraction of the grid cell that contains the most common land cover in that area based on the IGBP landcover map.
valid_max :
1.0
valid_min :
0.0
[1174152 values with dtype=float32]
latitude
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Latitude of the center of the Earth based grid cell.
units :
degrees_north
[391384 values with dtype=float32]
latitude_centroid
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Weighted average of the latitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
longitude
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Longitude of the center of the Earth based grid cell.
units :
degrees_east
[391384 values with dtype=float32]
longitude_centroid
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Weighted average of the longitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
radar_water_body_fraction
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The fraction of the area of the 36 km grid cell that is covered by water based on the radar detection algorithm.
Bit flags that represent the quality of the vertical polarization brightness temperature within each grid cell
[391384 values with dtype=float32]
tb_time_seconds
(phony_dim_0, phony_dim_1)
timedelta64[ns]
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
valid_max :
940000000.0
valid_min :
-999999.9
[391384 values with dtype=timedelta64[ns]]
tb_time_utc
(phony_dim_0, phony_dim_1)
|S24
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in UTC.
[391384 values with dtype=|S24]
tb_v_corrected
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell adjusted for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
tb_v_uncorrected
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell before adjustment for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
vegetation_opacity
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_dca
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scah
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-H retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scav
(phony_dim_0, phony_dim_1)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-V retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_water_content
(phony_dim_0, phony_dim_1)
float32
...
long_name :
Representative measure of water in the vegetation within the 36 km grid cell.
The column index of the 36 km EASE grid cell that contains the associated data.
valid_max :
963
valid_min :
0
[391384 values with dtype=float32]
EASE_row_index
(y, x)
float32
...
long_name :
The row index of the 36 km EASE grid cell that contains the associated data.
valid_max :
405
valid_min :
0
[391384 values with dtype=float32]
albedo
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_dca
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scah
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-H within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scav
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-V within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
boresight_incidence
(y, x)
float32
...
long_name :
Representative angle between the antenna boresight vector and the normal to the Earth's surface for all footprints within the cell.
units :
degrees
valid_max :
90.0
valid_min :
0.0
[391384 values with dtype=float32]
bulk_density
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated bulk_density within the 36 km grid cell.
valid_max :
2.65
valid_min :
0.0
[391384 values with dtype=float32]
clay_fraction
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated clay fraction within the 36 km grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
freeze_thaw_fraction
(y, x)
float32
...
long_name :
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
grid_surface_status
(y, x)
float32
...
long_name :
Indicates if the grid point lies on land (0) or water (1).
valid_max :
1
valid_min :
0
[391384 values with dtype=float32]
landcover_class
(y, x, igbp_class)
float32
...
long_name :
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
[1174152 values with dtype=float32]
landcover_class_fraction
(y, x, igbp_class)
float32
...
long_name :
The fraction of the grid cell that contains the most common land cover in that area based on the IGBP landcover map.
valid_max :
1.0
valid_min :
0.0
[1174152 values with dtype=float32]
latitude
(y, x)
float32
...
long_name :
Latitude of the center of the Earth based grid cell.
units :
degrees_north
[391384 values with dtype=float32]
latitude_centroid
(y, x)
float32
...
long_name :
Weighted average of the latitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
90.0
valid_min :
-90.0
[391384 values with dtype=float32]
longitude
(y, x)
float32
...
long_name :
Longitude of the center of the Earth based grid cell.
units :
degrees_east
[391384 values with dtype=float32]
longitude_centroid
(y, x)
float32
...
long_name :
Weighted average of the longitude of the center of the brightness temperature footprints that fall within the EASE grid cell.
units :
degrees
valid_max :
179.999
valid_min :
-180.0
[391384 values with dtype=float32]
radar_water_body_fraction
(y, x)
float32
...
long_name :
The fraction of the area of the 36 km grid cell that is covered by water based on the radar detection algorithm.
Bit flags that represent the quality of the vertical polarization brightness temperature within each grid cell
[391384 values with dtype=float32]
tb_time_seconds
(y, x)
timedelta64[ns]
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
valid_max :
940000000.0
valid_min :
-999999.9
[391384 values with dtype=timedelta64[ns]]
tb_time_utc
(y, x)
|S24
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in UTC.
[391384 values with dtype=|S24]
tb_v_corrected
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell adjusted for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
tb_v_uncorrected
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell before adjustment for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
vegetation_opacity
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_dca
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scah
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-H retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scav
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-V retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_water_content
(y, x)
float32
...
long_name :
Representative measure of water in the vegetation within the 36 km grid cell.
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
The column index of the 36 km EASE grid cell that contains the associated data.
valid_max :
963
valid_min :
0
[391384 values with dtype=float32]
EASE_row_index
(y, x)
float32
...
long_name :
The row index of the 36 km EASE grid cell that contains the associated data.
valid_max :
405
valid_min :
0
[391384 values with dtype=float32]
albedo
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_dca
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in DCA within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scah
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-H within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
albedo_scav
(y, x)
float32
...
long_name :
Diffuse reflecting power of the Earth's surface used in SCA-V within the grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
boresight_incidence
(y, x)
float32
...
long_name :
Representative angle between the antenna boresight vector and the normal to the Earth's surface for all footprints within the cell.
units :
degrees
valid_max :
90.0
valid_min :
0.0
[391384 values with dtype=float32]
bulk_density
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated bulk_density within the 36 km grid cell.
valid_max :
2.65
valid_min :
0.0
[391384 values with dtype=float32]
clay_fraction
(y, x)
float32
...
long_name :
A unitless value that is indicative of aggregated clay fraction within the 36 km grid cell.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
freeze_thaw_fraction
(y, x)
float32
...
long_name :
Fraction of the 36 km grid cell that is denoted as frozen. Based on binary flag that specifies freeze thaw conditions in each of the component 3 km grid cells.
valid_max :
1.0
valid_min :
0.0
[391384 values with dtype=float32]
grid_surface_status
(y, x)
float32
...
long_name :
Indicates if the grid point lies on land (0) or water (1).
valid_max :
1
valid_min :
0
[391384 values with dtype=float32]
landcover_class
(y, x, igbp_class)
float32
...
long_name :
An enumerated type that specifies the most common landcover class in the grid cell based on the IGBP landcover map. The array order is longitude (ascending), followed by latitude (descending), and followed by IGBP land cover type descending dominance (only the first three types are listed)
[1174152 values with dtype=float32]
landcover_class_fraction
(y, x, igbp_class)
float32
...
long_name :
The fraction of the grid cell that contains the most common land cover in that area based on the IGBP landcover map.
valid_max :
1.0
valid_min :
0.0
[1174152 values with dtype=float32]
latitude
(y, x)
float32
83.63 83.63 83.63 ... -83.63 -83.63
long_name :
Latitude of the center of the Earth based grid cell.
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
Bit flags that represent the quality of the vertical polarization brightness temperature within each grid cell
[391384 values with dtype=float32]
tb_time_seconds
(y, x)
timedelta64[ns]
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in seconds since noon on January 1, 2000 UTC.
valid_max :
940000000.0
valid_min :
-999999.9
[391384 values with dtype=timedelta64[ns]]
tb_time_utc
(y, x)
|S24
...
long_name :
Arithmetic average of the acquisition time of all of the brightness temperature footprints with a center that falls within the EASE grid cell in UTC.
[391384 values with dtype=|S24]
tb_v_corrected
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell adjusted for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
tb_v_uncorrected
(y, x)
float32
...
long_name :
Vertical polarization brightness temperature in 36 km Earth grid cell before adjustment for the presence of water bodies.
units :
Kelvin
valid_max :
330.0
valid_min :
0.0
[391384 values with dtype=float32]
vegetation_opacity
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_dca
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the DCA retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scah
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-H retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_opacity_scav
(y, x)
float32
...
long_name :
The measured opacity of the vegetation used in the SCA-V retrieval in the grid cell.
valid_max :
999999.9
valid_min :
-999999.9
[391384 values with dtype=float32]
vegetation_water_content
(y, x)
float32
...
long_name :
Representative measure of water in the vegetation within the 36 km grid cell.
\n",
+ "\n",
+ "# 2.0 Read and Plot SMAP data using `xarray.DataTree`\n",
+ "\n",
+ "