From 635048c05f63290503767b39b31d56a4699581d0 Mon Sep 17 00:00:00 2001 From: GitHub Action Date: Fri, 20 Oct 2023 04:57:17 +0000 Subject: [PATCH] Updated datasets 2023-10-20 UTC --- gee_catalog.json | 120 +++++++++--------- gee_catalog.tsv | 120 +++++++++--------- nasa_cmr_catalog.json | 286 +++++++++++++++++++++--------------------- nasa_cmr_catalog.tsv | 22 ++-- 4 files changed, 274 insertions(+), 274 deletions(-) diff --git a/gee_catalog.json b/gee_catalog.json index ab2e931..555aa96 100644 --- a/gee_catalog.json +++ b/gee_catalog.json @@ -672,7 +672,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S1_GRD')", "provider": "European Union/ESA/Copernicus", "state_date": "2014-10-03", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "backscatter, copernicus, esa, eu, polarization, radar, sar, sentinel", @@ -690,7 +690,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2')", "provider": "European Union/ESA/Copernicus", "state_date": "2015-06-23", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -56, 180, 83", "deprecated": false, "keywords": "copernicus, esa, eu, msi, radiance, sentinel", @@ -708,7 +708,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2_CLOUD_PROBABILITY')", "provider": "European Union/ESA/Copernicus/SentinelHub", "state_date": "2015-06-23", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -56, 180, 83", "deprecated": false, "keywords": "cloud, copernicus, esa, eu, msi, radiance, sentinel, sentinelhub", @@ -726,7 +726,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2_HARMONIZED')", "provider": "European Union/ESA/Copernicus", "state_date": "2015-06-23", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -56, 180, 83", "deprecated": false, "keywords": "copernicus, esa, eu, msi, radiance, sentinel", @@ -744,7 +744,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2_SR')", "provider": "European Union/ESA/Copernicus", "state_date": "2017-03-28", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -56, 180, 83", "deprecated": false, "keywords": "copernicus, esa, eu, msi, reflectance, sentinel, sr", @@ -762,7 +762,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')", "provider": "European Union/ESA/Copernicus", "state_date": "2017-03-28", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -56, 180, 83", "deprecated": false, "keywords": "copernicus, esa, eu, msi, reflectance, sentinel, sr", @@ -780,7 +780,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S3/OLCI')", "provider": "European Union/ESA/Copernicus", "state_date": "2016-10-18", - "end_date": "2023-10-17", + "end_date": "2023-10-18", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "copernicus, esa, eu, olci, radiance, sentinel, toa", @@ -798,7 +798,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_AI')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai", @@ -816,7 +816,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_LH')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2023-10-17", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai", @@ -834,7 +834,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CLOUD')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-05", - "end_date": "2023-10-17", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi", @@ -852,7 +852,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CO')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-11-22", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi", @@ -870,7 +870,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_HCHO')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-10-02", - "end_date": "2023-10-17", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi", @@ -888,7 +888,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_NO2')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2023-10-17", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi", @@ -906,7 +906,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_O3')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2023-10-17", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi", @@ -924,7 +924,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_SO2')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2023-10-17", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi", @@ -942,7 +942,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_AER_AI')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-04", - "end_date": "2023-10-15", + "end_date": "2023-10-16", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai", @@ -960,7 +960,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_AER_LH')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-04", - "end_date": "2023-10-15", + "end_date": "2023-10-17", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai", @@ -978,7 +978,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CH4')", "provider": "European Union/ESA/Copernicus", "state_date": "2019-02-08", - "end_date": "2023-10-15", + "end_date": "2023-10-16", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, copernicus, esa, eu, knmi, methane, s5p, sentinel, sron, tropomi", @@ -996,7 +996,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CLOUD')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-04", - "end_date": "2023-10-15", + "end_date": "2023-10-17", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi", @@ -1014,7 +1014,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CO')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-06-28", - "end_date": "2023-10-15", + "end_date": "2023-10-16", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi", @@ -1032,7 +1032,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_HCHO')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-12-05", - "end_date": "2023-10-15", + "end_date": "2023-10-16", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi", @@ -1050,7 +1050,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_NO2')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-06-28", - "end_date": "2023-10-08", + "end_date": "2023-10-09", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi", @@ -1068,7 +1068,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-09-08", - "end_date": "2023-10-15", + "end_date": "2023-10-16", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi", @@ -1086,7 +1086,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3_TCL')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-04-30", - "end_date": "2023-10-02", + "end_date": "2023-10-03", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi", @@ -1104,7 +1104,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_SO2')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-12-05", - "end_date": "2023-10-15", + "end_date": "2023-10-16", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi", @@ -1500,7 +1500,7 @@ "snippet": "ee.ImageCollection('ECMWF/CAMS/NRT')", "provider": "European Centre for Medium-Range Weather Forecasts (ECMWF)", "state_date": "2016-06-22", - "end_date": "2023-10-16", + "end_date": "2023-10-18", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aerosol, atmosphere, climate, copernicus, ecmwf, forecast, particulate_matter", @@ -1554,7 +1554,7 @@ "snippet": "ee.ImageCollection('ECMWF/ERA5_LAND/DAILY_AGGR')", "provider": "Daily Aggregates: Google and Copernicus Climate Data Store", "state_date": "1950-01-02", - "end_date": "2023-10-09", + "end_date": "2023-10-10", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind", @@ -2166,7 +2166,7 @@ "snippet": "ee.ImageCollection('FIRMS')", "provider": "NASA / LANCE / EOSDIS", "state_date": "2000-11-01", - "end_date": "2023-10-16", + "end_date": "2023-10-17", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal", @@ -2418,7 +2418,7 @@ "snippet": "ee.ImageCollection('GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED')", "provider": "Google Earth Engine", "state_date": "2022-01-01", - "end_date": "2023-10-17", + "end_date": "2023-10-18", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "google, cloud, sentinel2_derived", @@ -2436,7 +2436,7 @@ "snippet": "ee.ImageCollection('GOOGLE/DYNAMICWORLD/V1')", "provider": "World Resources Institute", "state_date": "2015-06-23", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "global, google, landcover, landuse, nrt, sentinel2_derived", @@ -5442,7 +5442,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC09/C02/T1')", "provider": "USGS", "state_date": "2021-10-31", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, l9, landsat, lc9, oli_tirs, radiance, t1, tier1, usgs", @@ -5460,7 +5460,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC09/C02/T1_L2')", "provider": "USGS", "state_date": "2021-10-31", - "end_date": "2023-10-16", + "end_date": "2023-10-17", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "cfmask, cloud, fmask, global, l9sr, landsat, lasrc, lc09, lst, reflectance, sr, usgs", @@ -5478,7 +5478,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC09/C02/T1_TOA')", "provider": "USGS/Google", "state_date": "2021-10-31", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, landsat, toa, usgs", @@ -5496,7 +5496,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC09/C02/T2')", "provider": "USGS", "state_date": "2021-11-02", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, l9, landsat, lc9, oli_tirs, radiance, t2, tier2, usgs", @@ -5514,7 +5514,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC09/C02/T2_L2')", "provider": "USGS", "state_date": "2021-10-31", - "end_date": "2023-10-16", + "end_date": "2023-10-17", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "cfmask, cloud, fmask, global, l9sr, landsat, lasrc, lc09, lst, reflectance, sr, usgs", @@ -5532,7 +5532,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC09/C02/T2_TOA')", "provider": "USGS/Google", "state_date": "2021-11-02", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, l9, landsat, lc9, toa, usgs", @@ -6648,7 +6648,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LE07/C02/T1')", "provider": "USGS", "state_date": "1999-05-28", - "end_date": "2023-09-21", + "end_date": "2023-09-23", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, etm, global, l7, landsat, le7, radiance, t1, tier1, usgs", @@ -6666,7 +6666,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LE07/C02/T1_L2')", "provider": "USGS", "state_date": "1999-05-28", - "end_date": "2023-09-21", + "end_date": "2023-09-23", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "cfmask, cloud, etm, fmask, global, landsat, lasrc, le07, lst, reflectance, sr, usgs", @@ -6684,7 +6684,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LE07/C02/T1_RT')", "provider": "USGS", "state_date": "1999-05-28", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, etm, global, l7, landsat, le7, nrt, radiance, rt, t1, tier1, usgs", @@ -6702,7 +6702,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LE07/C02/T1_RT_TOA')", "provider": "USGS/Google", "state_date": "1999-05-28", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, landsat, toa, usgs", @@ -6720,7 +6720,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LE07/C02/T1_TOA')", "provider": "USGS/Google", "state_date": "1999-05-28", - "end_date": "2023-09-21", + "end_date": "2023-09-23", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, landsat, toa, usgs", @@ -6738,7 +6738,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LE07/C02/T2')", "provider": "USGS", "state_date": "1999-05-28", - "end_date": "2023-09-21", + "end_date": "2023-09-22", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, etm, global, l7, landsat, le7, radiance, t2, tier2, usgs", @@ -6756,7 +6756,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LE07/C02/T2_L2')", "provider": "USGS", "state_date": "1999-05-28", - "end_date": "2023-09-21", + "end_date": "2023-09-22", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "cfmask, cloud, etm, fmask, global, landsat, lasrc, le07, lst, reflectance, sr, usgs", @@ -6774,7 +6774,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LE07/C02/T2_TOA')", "provider": "USGS/Google", "state_date": "2003-12-01", - "end_date": "2023-09-21", + "end_date": "2023-09-22", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, landsat, toa, usgs", @@ -11562,7 +11562,7 @@ "snippet": "ee.ImageCollection('MODIS/061/MCD19A1_GRANULES')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-12-21", - "end_date": "2007-11-18", + "end_date": "2008-02-04", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aerosol, aod, aqua, daily, global, maiac, modis, nasa, terra, usgs", @@ -13902,7 +13902,7 @@ "snippet": "ee.ImageCollection('NASA/HLS/HLSL30/v002')", "provider": "USGS", "state_date": "2013-04-11", - "end_date": "2023-10-14", + "end_date": "2023-10-15", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "landsat, nasa, sentinel, usgs", @@ -14640,7 +14640,7 @@ "snippet": "ee.ImageCollection('NOAA/GFS0P25')", "provider": "NOAA/NCEP/EMC", "state_date": "2015-07-01", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, cloud, emc, flux, forecast, geophysical, gfs, humidity, ncep, noaa, precipitation, radiation, temperature, vapor, weather, wind", @@ -14658,7 +14658,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/FDCC')", "provider": "NOAA", "state_date": "2017-05-24", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-152.11, 14, -49.18, 56.77", "deprecated": false, "keywords": "abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire", @@ -14676,7 +14676,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/FDCF')", "provider": "NOAA", "state_date": "2017-05-24", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire", @@ -14694,7 +14694,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/MCMIPC')", "provider": "NOAA", "state_date": "2017-07-10", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-152.11, 14, -49.18, 56.77", "deprecated": false, "keywords": "abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather", @@ -14712,7 +14712,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/MCMIPF')", "provider": "NOAA", "state_date": "2017-07-10", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather", @@ -14730,7 +14730,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/MCMIPM')", "provider": "NOAA", "state_date": "2017-07-10", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather", @@ -14838,7 +14838,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/FDCC')", "provider": "NOAA", "state_date": "2022-10-13", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, 14.57, 180, 53.51", "deprecated": false, "keywords": "abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire", @@ -14856,7 +14856,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/FDCF')", "provider": "NOAA", "state_date": "2022-10-13", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire", @@ -14874,7 +14874,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/MCMIPC')", "provider": "NOAA", "state_date": "2018-12-04", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, 14.57, 180, 53.51", "deprecated": false, "keywords": "abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather", @@ -14892,7 +14892,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/MCMIPF')", "provider": "NOAA", "state_date": "2018-12-04", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather", @@ -14910,7 +14910,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/MCMIPM')", "provider": "NOAA", "state_date": "2018-12-04", - "end_date": "2023-10-18", + "end_date": "2023-10-19", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather", @@ -15180,7 +15180,7 @@ "snippet": "ee.ImageCollection('NOAA/VIIRS/001/VNP43IA1')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2012-01-17", - "end_date": "2023-10-08", + "end_date": "2023-10-09", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "land, nasa, noaa, surface, viirs", @@ -15198,7 +15198,7 @@ "snippet": "ee.ImageCollection('NOAA/VIIRS/001/VNP43IA2')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2012-01-17", - "end_date": "2023-10-08", + "end_date": "2023-10-09", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "land, nasa, noaa, surface, viirs", @@ -16476,7 +16476,7 @@ "snippet": "ee.ImageCollection('TOMS/MERGED')", "provider": "NASA / GES DISC", "state_date": "1978-11-01", - "end_date": "2023-10-15", + "end_date": "2023-10-16", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "atmosphere, aura, climate, geophysical, ges_disc, goddard, nasa, omi, ozone, toms", diff --git a/gee_catalog.tsv b/gee_catalog.tsv index 1ae720d..301efff 100644 --- a/gee_catalog.tsv +++ b/gee_catalog.tsv @@ -36,31 +36,31 @@ COPERNICUS/CORINE/V20/100m Copernicus CORINE Land Cover image_collection ee.Imag COPERNICUS/DEM/GLO30 Copernicus DEM GLO-30: Global 30m Digital Elevation Model image_collection ee.ImageCollection('COPERNICUS/DEM/GLO30') Copernicus 2010-12-01 2015-01-31 -180, -90, 180, 90 False copernicus, dem, elevation, geophysical https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_DEM_GLO30.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_DEM_GLO30 proprietary COPERNICUS/Landcover/100m/Proba-V-C3/Global Copernicus Global Land Cover Layers: CGLS-LC100 Collection 3 image_collection ee.ImageCollection('COPERNICUS/Landcover/100m/Proba-V-C3/Global') Copernicus 2015-01-01 2019-12-31 -180, -90, 180, 90 False copernicus, eea, esa, eu, landcover, proba, probav, vito https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_Landcover_100m_Proba-V-C3_Global.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global proprietary COPERNICUS/Landcover/100m/Proba-V/Global Copernicus Global Land Cover Layers: CGLS-LC100 Collection 2 [deprecated] image_collection ee.ImageCollection('COPERNICUS/Landcover/100m/Proba-V/Global') Copernicus 2015-01-01 2015-01-01 -180, -90, 180, 90 True copernicus, eea, esa, eu, landcover, proba, probav, vito https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_Landcover_100m_Proba-V_Global.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V_Global proprietary -COPERNICUS/S1_GRD Sentinel-1 SAR GRD: C-band Synthetic Aperture Radar Ground Range Detected, log scaling image_collection ee.ImageCollection('COPERNICUS/S1_GRD') European Union/ESA/Copernicus 2014-10-03 2023-10-18 -180, -90, 180, 90 False backscatter, copernicus, esa, eu, polarization, radar, sar, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S1_GRD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S1_GRD proprietary -COPERNICUS/S2 Sentinel-2 MSI: MultiSpectral Instrument, Level-1C image_collection ee.ImageCollection('COPERNICUS/S2') European Union/ESA/Copernicus 2015-06-23 2023-10-18 -180, -56, 180, 83 False copernicus, esa, eu, msi, radiance, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2 proprietary -COPERNICUS/S2_CLOUD_PROBABILITY Sentinel-2: Cloud Probability image_collection ee.ImageCollection('COPERNICUS/S2_CLOUD_PROBABILITY') European Union/ESA/Copernicus/SentinelHub 2015-06-23 2023-10-18 -180, -56, 180, 83 False cloud, copernicus, esa, eu, msi, radiance, sentinel, sentinelhub https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_CLOUD_PROBABILITY.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_CLOUD_PROBABILITY proprietary -COPERNICUS/S2_HARMONIZED Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-1C image_collection ee.ImageCollection('COPERNICUS/S2_HARMONIZED') European Union/ESA/Copernicus 2015-06-23 2023-10-18 -180, -56, 180, 83 False copernicus, esa, eu, msi, radiance, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_HARMONIZED proprietary -COPERNICUS/S2_SR Sentinel-2 MSI: MultiSpectral Instrument, Level-2A image_collection ee.ImageCollection('COPERNICUS/S2_SR') European Union/ESA/Copernicus 2017-03-28 2023-10-18 -180, -56, 180, 83 False copernicus, esa, eu, msi, reflectance, sentinel, sr https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_SR.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR proprietary -COPERNICUS/S2_SR_HARMONIZED Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-2A image_collection ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED') European Union/ESA/Copernicus 2017-03-28 2023-10-18 -180, -56, 180, 83 False copernicus, esa, eu, msi, reflectance, sentinel, sr https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_SR_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED proprietary -COPERNICUS/S3/OLCI Sentinel-3 OLCI EFR: Ocean and Land Color Instrument Earth Observation Full Resolution image_collection ee.ImageCollection('COPERNICUS/S3/OLCI') European Union/ESA/Copernicus 2016-10-18 2023-10-17 -180, -90, 180, 90 False copernicus, esa, eu, olci, radiance, sentinel, toa https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S3_OLCI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S3_OLCI proprietary -COPERNICUS/S5P/NRTI/L3_AER_AI Sentinel-5P NRTI AER AI: Near Real-Time UV Aerosol Index image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_AI') European Union/ESA/Copernicus 2018-07-10 2023-10-18 -180, -90, 180, 90 False aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_AER_AI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_AER_AI proprietary -COPERNICUS/S5P/NRTI/L3_AER_LH Sentinel-5P NRTI AER LH: Near Real-Time UV Aerosol Layer Height image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_LH') European Union/ESA/Copernicus 2018-07-10 2023-10-17 -180, -90, 180, 90 False aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_AER_LH.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_AER_LH proprietary -COPERNICUS/S5P/NRTI/L3_CLOUD Sentinel-5P NRTI CLOUD: Near Real-Time Cloud image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CLOUD') European Union/ESA/Copernicus 2018-07-05 2023-10-17 -180, -90, 180, 90 False climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_CLOUD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_CLOUD proprietary -COPERNICUS/S5P/NRTI/L3_CO Sentinel-5P NRTI CO: Near Real-Time Carbon Monoxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CO') European Union/ESA/Copernicus 2018-11-22 2023-10-18 -180, -90, 180, 90 False air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_CO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_CO proprietary -COPERNICUS/S5P/NRTI/L3_HCHO Sentinel-5P NRTI HCHO: Near Real-Time Formaldehyde image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_HCHO') European Union/ESA/Copernicus 2018-10-02 2023-10-17 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_HCHO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_HCHO proprietary -COPERNICUS/S5P/NRTI/L3_NO2 Sentinel-5P NRTI NO2: Near Real-Time Nitrogen Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_NO2') European Union/ESA/Copernicus 2018-07-10 2023-10-17 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_NO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_NO2 proprietary -COPERNICUS/S5P/NRTI/L3_O3 Sentinel-5P NRTI O3: Near Real-Time Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_O3') European Union/ESA/Copernicus 2018-07-10 2023-10-17 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_O3.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_O3 proprietary -COPERNICUS/S5P/NRTI/L3_SO2 Sentinel-5P NRTI SO2: Near Real-Time Sulfur Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_SO2') European Union/ESA/Copernicus 2018-07-10 2023-10-17 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_SO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_SO2 proprietary -COPERNICUS/S5P/OFFL/L3_AER_AI Sentinel-5P OFFL AER AI: Offline UV Aerosol Index image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_AER_AI') European Union/ESA/Copernicus 2018-07-04 2023-10-15 -180, -90, 180, 90 False aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_AER_AI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_AER_AI proprietary -COPERNICUS/S5P/OFFL/L3_AER_LH Sentinel-5P OFFL AER LH: Offline UV Aerosol Layer Height image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_AER_LH') European Union/ESA/Copernicus 2018-07-04 2023-10-15 -180, -90, 180, 90 False aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_AER_LH.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_AER_LH proprietary -COPERNICUS/S5P/OFFL/L3_CH4 Sentinel-5P OFFL CH4: Offline Methane image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CH4') European Union/ESA/Copernicus 2019-02-08 2023-10-15 -180, -90, 180, 90 False climate, copernicus, esa, eu, knmi, methane, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CH4.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CH4 proprietary -COPERNICUS/S5P/OFFL/L3_CLOUD Sentinel-5P OFFL CLOUD: Near Real-Time Cloud image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CLOUD') European Union/ESA/Copernicus 2018-07-04 2023-10-15 -180, -90, 180, 90 False climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CLOUD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CLOUD proprietary -COPERNICUS/S5P/OFFL/L3_CO Sentinel-5P OFFL CO: Offline Carbon Monoxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CO') European Union/ESA/Copernicus 2018-06-28 2023-10-15 -180, -90, 180, 90 False air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CO proprietary -COPERNICUS/S5P/OFFL/L3_HCHO Sentinel-5P OFFL HCHO: Offline Formaldehyde image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_HCHO') European Union/ESA/Copernicus 2018-12-05 2023-10-15 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_HCHO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_HCHO proprietary -COPERNICUS/S5P/OFFL/L3_NO2 Sentinel-5P OFFL NO2: Offline Nitrogen Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_NO2') European Union/ESA/Copernicus 2018-06-28 2023-10-08 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_NO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_NO2 proprietary -COPERNICUS/S5P/OFFL/L3_O3 Sentinel-5P OFFL O3: Offline Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3') European Union/ESA/Copernicus 2018-09-08 2023-10-15 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_O3.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_O3 proprietary -COPERNICUS/S5P/OFFL/L3_O3_TCL Sentinel-5P OFFL O3 TCL: Offline Tropospheric Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3_TCL') European Union/ESA/Copernicus 2018-04-30 2023-10-02 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_O3_TCL.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_O3_TCL proprietary -COPERNICUS/S5P/OFFL/L3_SO2 Sentinel-5P OFFL SO2: Offline Sulfur Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_SO2') European Union/ESA/Copernicus 2018-12-05 2023-10-15 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_SO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_SO2 proprietary +COPERNICUS/S1_GRD Sentinel-1 SAR GRD: C-band Synthetic Aperture Radar Ground Range Detected, log scaling image_collection ee.ImageCollection('COPERNICUS/S1_GRD') European Union/ESA/Copernicus 2014-10-03 2023-10-19 -180, -90, 180, 90 False backscatter, copernicus, esa, eu, polarization, radar, sar, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S1_GRD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S1_GRD proprietary +COPERNICUS/S2 Sentinel-2 MSI: MultiSpectral Instrument, Level-1C image_collection ee.ImageCollection('COPERNICUS/S2') European Union/ESA/Copernicus 2015-06-23 2023-10-19 -180, -56, 180, 83 False copernicus, esa, eu, msi, radiance, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2 proprietary +COPERNICUS/S2_CLOUD_PROBABILITY Sentinel-2: Cloud Probability image_collection ee.ImageCollection('COPERNICUS/S2_CLOUD_PROBABILITY') European Union/ESA/Copernicus/SentinelHub 2015-06-23 2023-10-19 -180, -56, 180, 83 False cloud, copernicus, esa, eu, msi, radiance, sentinel, sentinelhub https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_CLOUD_PROBABILITY.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_CLOUD_PROBABILITY proprietary +COPERNICUS/S2_HARMONIZED Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-1C image_collection ee.ImageCollection('COPERNICUS/S2_HARMONIZED') European Union/ESA/Copernicus 2015-06-23 2023-10-19 -180, -56, 180, 83 False copernicus, esa, eu, msi, radiance, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_HARMONIZED proprietary +COPERNICUS/S2_SR Sentinel-2 MSI: MultiSpectral Instrument, Level-2A image_collection ee.ImageCollection('COPERNICUS/S2_SR') European Union/ESA/Copernicus 2017-03-28 2023-10-19 -180, -56, 180, 83 False copernicus, esa, eu, msi, reflectance, sentinel, sr https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_SR.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR proprietary +COPERNICUS/S2_SR_HARMONIZED Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-2A image_collection ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED') European Union/ESA/Copernicus 2017-03-28 2023-10-19 -180, -56, 180, 83 False copernicus, esa, eu, msi, reflectance, sentinel, sr https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_SR_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED proprietary +COPERNICUS/S3/OLCI Sentinel-3 OLCI EFR: Ocean and Land Color Instrument Earth Observation Full Resolution image_collection ee.ImageCollection('COPERNICUS/S3/OLCI') European Union/ESA/Copernicus 2016-10-18 2023-10-18 -180, -90, 180, 90 False copernicus, esa, eu, olci, radiance, sentinel, toa https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S3_OLCI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S3_OLCI proprietary +COPERNICUS/S5P/NRTI/L3_AER_AI Sentinel-5P NRTI AER AI: Near Real-Time UV Aerosol Index image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_AI') European Union/ESA/Copernicus 2018-07-10 2023-10-19 -180, -90, 180, 90 False aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_AER_AI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_AER_AI proprietary +COPERNICUS/S5P/NRTI/L3_AER_LH Sentinel-5P NRTI AER LH: Near Real-Time UV Aerosol Layer Height image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_LH') European Union/ESA/Copernicus 2018-07-10 2023-10-19 -180, -90, 180, 90 False aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_AER_LH.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_AER_LH proprietary +COPERNICUS/S5P/NRTI/L3_CLOUD Sentinel-5P NRTI CLOUD: Near Real-Time Cloud image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CLOUD') European Union/ESA/Copernicus 2018-07-05 2023-10-19 -180, -90, 180, 90 False climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_CLOUD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_CLOUD proprietary +COPERNICUS/S5P/NRTI/L3_CO Sentinel-5P NRTI CO: Near Real-Time Carbon Monoxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CO') European Union/ESA/Copernicus 2018-11-22 2023-10-19 -180, -90, 180, 90 False air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_CO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_CO proprietary +COPERNICUS/S5P/NRTI/L3_HCHO Sentinel-5P NRTI HCHO: Near Real-Time Formaldehyde image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_HCHO') European Union/ESA/Copernicus 2018-10-02 2023-10-19 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_HCHO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_HCHO proprietary +COPERNICUS/S5P/NRTI/L3_NO2 Sentinel-5P NRTI NO2: Near Real-Time Nitrogen Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_NO2') European Union/ESA/Copernicus 2018-07-10 2023-10-19 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_NO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_NO2 proprietary +COPERNICUS/S5P/NRTI/L3_O3 Sentinel-5P NRTI O3: Near Real-Time Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_O3') European Union/ESA/Copernicus 2018-07-10 2023-10-19 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_O3.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_O3 proprietary +COPERNICUS/S5P/NRTI/L3_SO2 Sentinel-5P NRTI SO2: Near Real-Time Sulfur Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_SO2') European Union/ESA/Copernicus 2018-07-10 2023-10-19 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_SO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_SO2 proprietary +COPERNICUS/S5P/OFFL/L3_AER_AI Sentinel-5P OFFL AER AI: Offline UV Aerosol Index image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_AER_AI') European Union/ESA/Copernicus 2018-07-04 2023-10-16 -180, -90, 180, 90 False aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_AER_AI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_AER_AI proprietary +COPERNICUS/S5P/OFFL/L3_AER_LH Sentinel-5P OFFL AER LH: Offline UV Aerosol Layer Height image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_AER_LH') European Union/ESA/Copernicus 2018-07-04 2023-10-17 -180, -90, 180, 90 False aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_AER_LH.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_AER_LH proprietary +COPERNICUS/S5P/OFFL/L3_CH4 Sentinel-5P OFFL CH4: Offline Methane image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CH4') European Union/ESA/Copernicus 2019-02-08 2023-10-16 -180, -90, 180, 90 False climate, copernicus, esa, eu, knmi, methane, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CH4.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CH4 proprietary +COPERNICUS/S5P/OFFL/L3_CLOUD Sentinel-5P OFFL CLOUD: Near Real-Time Cloud image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CLOUD') European Union/ESA/Copernicus 2018-07-04 2023-10-17 -180, -90, 180, 90 False climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CLOUD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CLOUD proprietary +COPERNICUS/S5P/OFFL/L3_CO Sentinel-5P OFFL CO: Offline Carbon Monoxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CO') European Union/ESA/Copernicus 2018-06-28 2023-10-16 -180, -90, 180, 90 False air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CO proprietary +COPERNICUS/S5P/OFFL/L3_HCHO Sentinel-5P OFFL HCHO: Offline Formaldehyde image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_HCHO') European Union/ESA/Copernicus 2018-12-05 2023-10-16 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_HCHO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_HCHO proprietary +COPERNICUS/S5P/OFFL/L3_NO2 Sentinel-5P OFFL NO2: Offline Nitrogen Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_NO2') European Union/ESA/Copernicus 2018-06-28 2023-10-09 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_NO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_NO2 proprietary +COPERNICUS/S5P/OFFL/L3_O3 Sentinel-5P OFFL O3: Offline Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3') European Union/ESA/Copernicus 2018-09-08 2023-10-16 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_O3.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_O3 proprietary +COPERNICUS/S5P/OFFL/L3_O3_TCL Sentinel-5P OFFL O3 TCL: Offline Tropospheric Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3_TCL') European Union/ESA/Copernicus 2018-04-30 2023-10-03 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_O3_TCL.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_O3_TCL proprietary +COPERNICUS/S5P/OFFL/L3_SO2 Sentinel-5P OFFL SO2: Offline Sulfur Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_SO2') European Union/ESA/Copernicus 2018-12-05 2023-10-16 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_SO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_SO2 proprietary CPOM/CryoSat2/ANTARCTICA_DEM CryoSat-2 Antarctica 1km DEM image ee.Image('CPOM/CryoSat2/ANTARCTICA_DEM') CPOM 2010-07-01 2016-07-01 -180, -88, 180, -60 False antarctica, cpom, cryosat_2, dem, elevation, polar https://storage.googleapis.com/earthengine-stac/catalog/CPOM/CPOM_CryoSat2_ANTARCTICA_DEM.json https://developers.google.com/earth-engine/datasets/catalog/CPOM_CryoSat2_ANTARCTICA_DEM proprietary CSIC/SPEI/2_8 SPEIbase: Standardised Precipitation-Evapotranspiration Index database, Version 2.8 image_collection ee.ImageCollection('CSIC/SPEI/2_8') Spanish National Research Council (CSIC) 1901-01-01 2021-01-01 -180, -90, 180, 90 False climate, climate_change, drought, evapotranspiration, global, monthly, palmer, precipitation, temperature https://storage.googleapis.com/earthengine-stac/catalog/CSIC/CSIC_SPEI_2_8.json https://developers.google.com/earth-engine/datasets/catalog/CSIC_SPEI_2_8 CC-BY-4.0 CSIRO/SLGA SLGA: Soil and Landscape Grid of Australia (Soil Attributes) image_collection ee.ImageCollection('CSIRO/SLGA') CSIRO/SLGA 1950-01-01 2013-12-31 113, -44.15, 154, -9.97 False australia, csiro, digital_soil_mapping, globalsoilmap, slga, soil, soil_depth, tern https://storage.googleapis.com/earthengine-stac/catalog/CSIRO/CSIRO_SLGA.json https://developers.google.com/earth-engine/datasets/catalog/CSIRO_SLGA CC-BY-4.0 @@ -82,10 +82,10 @@ CSP/ERGo/1_0/US/topoDiversity US NED Topographic Diversity image ee.Image('CSP/E CSP/HM/GlobalHumanModification CSP gHM: Global Human Modification image_collection ee.ImageCollection('CSP/HM/GlobalHumanModification') Conservation Science Partners 2016-01-01 2016-12-31 -180, -90, 180, 90 False csp, fragmentation, human_modification, landcover, landscape_gradient, stressors, tnc https://storage.googleapis.com/earthengine-stac/catalog/CSP/CSP_HM_GlobalHumanModification.json https://developers.google.com/earth-engine/datasets/catalog/CSP_HM_GlobalHumanModification CC-BY-NC-SA-4.0 DLR/WSF/WSF2015/v1 World Settlement Footprint 2015 image ee.Image('DLR/WSF/WSF2015/v1') Deutsches Zentrum für Luft- und Raumfahrt (DLR) 2015-01-01 2016-01-01 -180, -90, 180, 90 False landcover, landsat_derived, sentinel1_derived, settlement, urban https://storage.googleapis.com/earthengine-stac/catalog/DLR/DLR_WSF_WSF2015_v1.json https://developers.google.com/earth-engine/datasets/catalog/DLR_WSF_WSF2015_v1 CC0-1.0 DOE/ORNL/LandScan_HD/Ukraine_202201 LandScan High Definition Data for Ukraine, January 2022 image ee.Image('DOE/ORNL/LandScan_HD/Ukraine_202201') Oak Ridge National Laboratory 2022-01-01 2022-02-01 22.125, 44.175, 40.225, 52.4 False landscan, population, ukraine https://storage.googleapis.com/earthengine-stac/catalog/DOE/DOE_ORNL_LandScan_HD_Ukraine_202201.json https://developers.google.com/earth-engine/datasets/catalog/DOE_ORNL_LandScan_HD_Ukraine_202201 CC-BY-4.0 -ECMWF/CAMS/NRT Copernicus Atmosphere Monitoring Service (CAMS) Global Near-Real-Time image_collection ee.ImageCollection('ECMWF/CAMS/NRT') European Centre for Medium-Range Weather Forecasts (ECMWF) 2016-06-22 2023-10-16 -180, -90, 180, 90 False aerosol, atmosphere, climate, copernicus, ecmwf, forecast, particulate_matter https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_CAMS_NRT.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_CAMS_NRT proprietary +ECMWF/CAMS/NRT Copernicus Atmosphere Monitoring Service (CAMS) Global Near-Real-Time image_collection ee.ImageCollection('ECMWF/CAMS/NRT') European Centre for Medium-Range Weather Forecasts (ECMWF) 2016-06-22 2023-10-18 -180, -90, 180, 90 False aerosol, atmosphere, climate, copernicus, ecmwf, forecast, particulate_matter https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_CAMS_NRT.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_CAMS_NRT proprietary ECMWF/ERA5/DAILY ERA5 Daily Aggregates - Latest Climate Reanalysis Produced by ECMWF / Copernicus Climate Change Service image_collection ee.ImageCollection('ECMWF/ERA5/DAILY') ECMWF / Copernicus Climate Change Service 1979-01-02 2020-07-09 -180, -90, 180, 90 False climate, copernicus, dewpoint, ecmwf, era5, precipitation, pressure, reanalysis, surface, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_DAILY.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_DAILY proprietary ECMWF/ERA5/MONTHLY ERA5 Monthly Aggregates - Latest Climate Reanalysis Produced by ECMWF / Copernicus Climate Change Service image_collection ee.ImageCollection('ECMWF/ERA5/MONTHLY') ECMWF / Copernicus Climate Change Service 1979-01-01 2020-06-01 -180, -90, 180, 90 False climate, copernicus, dewpoint, ecmwf, era5, precipitation, pressure, reanalysis, surface, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_MONTHLY.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_MONTHLY proprietary -ECMWF/ERA5_LAND/DAILY_AGGR ERA5-Land Daily Aggregated - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/DAILY_AGGR') Daily Aggregates: Google and Copernicus Climate Data Store 1950-01-02 2023-10-09 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_DAILY_AGGR.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_DAILY_AGGR proprietary +ECMWF/ERA5_LAND/DAILY_AGGR ERA5-Land Daily Aggregated - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/DAILY_AGGR') Daily Aggregates: Google and Copernicus Climate Data Store 1950-01-02 2023-10-10 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_DAILY_AGGR.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_DAILY_AGGR proprietary ECMWF/ERA5_LAND/HOURLY ERA5-Land Hourly - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/HOURLY') Copernicus Climate Data Store 1950-01-01 2023-10-11 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_HOURLY.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_HOURLY proprietary ECMWF/ERA5_LAND/MONTHLY ERA5-Land Monthly Averaged - ECMWF Climate Reanalysis [deprecated] image_collection ee.ImageCollection('ECMWF/ERA5_LAND/MONTHLY') Copernicus Climate Data Store 1950-02-01 2023-04-01 -180, -90, 180, 90 True cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_MONTHLY.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_MONTHLY proprietary ECMWF/ERA5_LAND/MONTHLY_AGGR ERA5-Land Monthly Aggregated - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/MONTHLY_AGGR') Monthly Aggregates: Google and Copernicus Climate Data Store 1950-02-01 2023-09-01 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_MONTHLY_AGGR.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_MONTHLY_AGGR proprietary @@ -119,7 +119,7 @@ FAO/WAPOR/2/L1_NPP_D WAPOR Dekadal Net Primary Production 2.0 image_collection e FAO/WAPOR/2/L1_RET_D WAPOR Dekadal Reference Evapotranspiration 2.0 image_collection ee.ImageCollection('FAO/WAPOR/2/L1_RET_D') FAO UN 2009-01-01 2023-03-11 -30.15, -39.9953437, 65.13, 40.0044643 False agriculture, fao, wapor, water https://storage.googleapis.com/earthengine-stac/catalog/FAO/FAO_WAPOR_2_L1_RET_D.json https://developers.google.com/earth-engine/datasets/catalog/FAO_WAPOR_2_L1_RET_D proprietary FAO/WAPOR/2/L1_RET_E WAPOR Daily Reference Evapotranspiration 2.0 image_collection ee.ImageCollection('FAO/WAPOR/2/L1_RET_E') FAO UN 2009-01-01 2023-03-20 -30.15, -39.9953437, 65.13, 40.0044643 False agriculture, fao, wapor, water https://storage.googleapis.com/earthengine-stac/catalog/FAO/FAO_WAPOR_2_L1_RET_E.json https://developers.google.com/earth-engine/datasets/catalog/FAO_WAPOR_2_L1_RET_E proprietary FAO/WAPOR/2/L1_T_D WAPOR Dekadal Transpiration 2.0 image_collection ee.ImageCollection('FAO/WAPOR/2/L1_T_D') FAO UN 2009-01-01 2023-03-01 -30.0044643, -40.0044644, 65.0044644, 40.0044643 False agriculture, fao, wapor, water https://storage.googleapis.com/earthengine-stac/catalog/FAO/FAO_WAPOR_2_L1_T_D.json https://developers.google.com/earth-engine/datasets/catalog/FAO_WAPOR_2_L1_T_D proprietary -FIRMS FIRMS: Fire Information for Resource Management System image_collection ee.ImageCollection('FIRMS') NASA / LANCE / EOSDIS 2000-11-01 2023-10-16 -180, -90, 180, 90 False eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal https://storage.googleapis.com/earthengine-stac/catalog/FIRMS/FIRMS.json https://developers.google.com/earth-engine/datasets/catalog/FIRMS proprietary +FIRMS FIRMS: Fire Information for Resource Management System image_collection ee.ImageCollection('FIRMS') NASA / LANCE / EOSDIS 2000-11-01 2023-10-17 -180, -90, 180, 90 False eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal https://storage.googleapis.com/earthengine-stac/catalog/FIRMS/FIRMS.json https://developers.google.com/earth-engine/datasets/catalog/FIRMS proprietary FORMA/FORMA_500m FORMA Global Forest Watch Deforestation Alerts, 500m [deprecated] image ee.Image('FORMA/FORMA_500m') Global Forest Watch, World Resources Institute 2006-01-01 2015-06-10 -180, -90, 180, 90 True alerts, deforestation, forest, forma, geophysical, gfw, modis, nasa, wri https://storage.googleapis.com/earthengine-stac/catalog/FORMA/FORMA_FORMA_500m.json https://developers.google.com/earth-engine/datasets/catalog/FORMA_FORMA_500m proprietary Finland/MAVI/VV/50cm Finland NRG NLS orthophotos 50 cm by Mavi image_collection ee.ImageCollection('Finland/MAVI/VV/50cm') NLS orthophotos 2015-01-01 2018-01-01 59, 18, 69.4, 29.2 False falsecolor, finland, mavi, nrg, orthophoto https://storage.googleapis.com/earthengine-stac/catalog/Finland/Finland_MAVI_VV_50cm.json https://developers.google.com/earth-engine/datasets/catalog/Finland_MAVI_VV_50cm CC-BY-4.0 Finland/SMK/V/50cm Finland RGB NLS orthophotos 50 cm by SMK image_collection ee.ImageCollection('Finland/SMK/V/50cm') NLS orthophotos 2015-01-01 2023-01-01 59, 18, 69.4, 29.2 False finland, orthophoto, rgb, smk https://storage.googleapis.com/earthengine-stac/catalog/Finland/Finland_SMK_V_50cm.json https://developers.google.com/earth-engine/datasets/catalog/Finland_SMK_V_50cm proprietary @@ -133,8 +133,8 @@ GLIMS/20171027 GLIMS 2017: Global Land Ice Measurements From Space [deprecated] GLIMS/20210914 GLIMS 2021: Global Land Ice Measurements From Space table ee.FeatureCollection('GLIMS/20210914') National Snow and Ice Data Center (NSDIC) 1750-01-01 2019-07-18 -180, -90, 180, 90 False glacier, glims, ice, landcover, nasa, nsidc, snow https://storage.googleapis.com/earthengine-stac/catalog/GLIMS/GLIMS_20210914.json https://developers.google.com/earth-engine/datasets/catalog/GLIMS_20210914 proprietary GLIMS/current GLIMS Current: Global Land Ice Measurements From Space table ee.FeatureCollection('GLIMS/current') National Snow and Ice Data Center (NSDIC) 1750-01-01 2019-07-18 -180, -90, 180, 90 False glacier, glims, ice, landcover, nasa, nsidc, snow https://storage.googleapis.com/earthengine-stac/catalog/GLIMS/GLIMS_current.json https://developers.google.com/earth-engine/datasets/catalog/GLIMS_current proprietary GLOBAL_FLOOD_DB/MODIS_EVENTS/V1 Global Flood Database v1 (2000-2018) image_collection ee.ImageCollection('GLOBAL_FLOOD_DB/MODIS_EVENTS/V1') Cloud to Street (C2S) / Dartmouth Flood Observatory (DFO) 2000-02-17 2018-12-10 -180, -90, 180, 90 False c2s, cloudtostreet, dartmouth, dfo, flood, gfd, inundation, surface, water https://storage.googleapis.com/earthengine-stac/catalog/GLOBAL_FLOOD_DB/GLOBAL_FLOOD_DB_MODIS_EVENTS_V1.json https://developers.google.com/earth-engine/datasets/catalog/GLOBAL_FLOOD_DB_MODIS_EVENTS_V1 CC-BY-NC-4.0 -GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED Cloud Score+ S2_HARMONIZED V1 image_collection ee.ImageCollection('GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED') Google Earth Engine 2022-01-01 2023-10-17 -180, -90, 180, 90 False google, cloud, sentinel2_derived https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_CLOUD_SCORE_PLUS_V1_S2_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_CLOUD_SCORE_PLUS_V1_S2_HARMONIZED CC-BY-4.0 -GOOGLE/DYNAMICWORLD/V1 Dynamic World V1 image_collection ee.ImageCollection('GOOGLE/DYNAMICWORLD/V1') World Resources Institute 2015-06-23 2023-10-18 -180, -90, 180, 90 False global, google, landcover, landuse, nrt, sentinel2_derived https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_DYNAMICWORLD_V1.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_DYNAMICWORLD_V1 CC-BY-4.0 +GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED Cloud Score+ S2_HARMONIZED V1 image_collection ee.ImageCollection('GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED') Google Earth Engine 2022-01-01 2023-10-18 -180, -90, 180, 90 False google, cloud, sentinel2_derived https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_CLOUD_SCORE_PLUS_V1_S2_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_CLOUD_SCORE_PLUS_V1_S2_HARMONIZED CC-BY-4.0 +GOOGLE/DYNAMICWORLD/V1 Dynamic World V1 image_collection ee.ImageCollection('GOOGLE/DYNAMICWORLD/V1') World Resources Institute 2015-06-23 2023-10-19 -180, -90, 180, 90 False global, google, landcover, landuse, nrt, sentinel2_derived https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_DYNAMICWORLD_V1.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_DYNAMICWORLD_V1 CC-BY-4.0 GOOGLE/Research/open-buildings/v1/polygons Open Buildings V1 Polygons [deprecated] table ee.FeatureCollection('GOOGLE/Research/open-buildings/v1/polygons') Google Research - Open Buildings 2021-04-30 2021-04-30 -180, -90, 180, 90 True africa, building, built_up, open_buildings, structure https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_Research_open-buildings_v1_polygons.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings_v1_polygons CC-BY-4.0 GOOGLE/Research/open-buildings/v2/polygons Open Buildings V2 Polygons [deprecated] table ee.FeatureCollection('GOOGLE/Research/open-buildings/v2/polygons') Google Research - Open Buildings 2022-08-30 2022-08-30 -180, -90, 180, 90 True africa, asia, building, built_up, open_buildings, south_asia, southeast_asia, structure https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_Research_open-buildings_v2_polygons.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings_v2_polygons CC-BY-4.0 GOOGLE/Research/open-buildings/v3/polygons Open Buildings V3 Polygons table ee.FeatureCollection('GOOGLE/Research/open-buildings/v3/polygons') Google Research - Open Buildings 2023-05-30 2023-05-30 -180, -90, 180, 90 False africa, asia, building, built_up, open_buildings, south_asia, southeast_asia, structure https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_Research_open-buildings_v3_polygons.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings_v3_polygons CC-BY-4.0 @@ -301,12 +301,12 @@ LANDSAT/LC08/C02/T1_TOA USGS Landsat 8 Collection 2 Tier 1 TOA Reflectance image LANDSAT/LC08/C02/T2 USGS Landsat 8 Collection 2 Tier 2 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC08/C02/T2') USGS 2021-10-28 2023-10-13 -180, -90, 180, 90 False c2, global, l8, landsat, lc8, oli_tirs, radiance, t2, tier2, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T2 PDDL-1.0 LANDSAT/LC08/C02/T2_L2 USGS Landsat 8 Level 2, Collection 2, Tier 2 image_collection ee.ImageCollection('LANDSAT/LC08/C02/T2_L2') USGS 2013-03-18 2023-10-13 -180, -90, 180, 90 False cfmask, cloud, fmask, global, l8sr, landsat, lasrc, lc08, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T2_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T2_L2 proprietary LANDSAT/LC08/C02/T2_TOA USGS Landsat 8 Collection 2 Tier 2 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC08/C02/T2_TOA') USGS/Google 2021-10-28 2023-10-13 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T2_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T2_TOA PDDL-1.0 -LANDSAT/LC09/C02/T1 USGS Landsat 9 Collection 2 Tier 1 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1') USGS 2021-10-31 2023-10-18 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, oli_tirs, radiance, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1 PDDL-1.0 -LANDSAT/LC09/C02/T1_L2 USGS Landsat 9 Level 2, Collection 2, Tier 1 image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1_L2') USGS 2021-10-31 2023-10-16 -180, -90, 180, 90 False cfmask, cloud, fmask, global, l9sr, landsat, lasrc, lc09, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1_L2 proprietary -LANDSAT/LC09/C02/T1_TOA USGS Landsat 9 Collection 2 Tier 1 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1_TOA') USGS/Google 2021-10-31 2023-10-18 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1_TOA PDDL-1.0 -LANDSAT/LC09/C02/T2 USGS Landsat 9 Collection 2 Tier 2 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC09/C02/T2') USGS 2021-11-02 2023-10-18 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, oli_tirs, radiance, t2, tier2, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2 PDDL-1.0 -LANDSAT/LC09/C02/T2_L2 USGS Landsat 9 Level 2, Collection 2, Tier 2 image_collection ee.ImageCollection('LANDSAT/LC09/C02/T2_L2') USGS 2021-10-31 2023-10-16 -180, -90, 180, 90 False cfmask, cloud, fmask, global, l9sr, landsat, lasrc, lc09, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T2_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2_L2 proprietary -LANDSAT/LC09/C02/T2_TOA USGS Landsat 9 Collection 2 Tier 2 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC09/C02/T2_TOA') USGS/Google 2021-11-02 2023-10-18 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T2_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2_TOA PDDL-1.0 +LANDSAT/LC09/C02/T1 USGS Landsat 9 Collection 2 Tier 1 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1') USGS 2021-10-31 2023-10-19 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, oli_tirs, radiance, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1 PDDL-1.0 +LANDSAT/LC09/C02/T1_L2 USGS Landsat 9 Level 2, Collection 2, Tier 1 image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1_L2') USGS 2021-10-31 2023-10-17 -180, -90, 180, 90 False cfmask, cloud, fmask, global, l9sr, landsat, lasrc, lc09, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1_L2 proprietary +LANDSAT/LC09/C02/T1_TOA USGS Landsat 9 Collection 2 Tier 1 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1_TOA') USGS/Google 2021-10-31 2023-10-19 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1_TOA PDDL-1.0 +LANDSAT/LC09/C02/T2 USGS Landsat 9 Collection 2 Tier 2 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC09/C02/T2') USGS 2021-11-02 2023-10-19 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, oli_tirs, radiance, t2, tier2, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2 PDDL-1.0 +LANDSAT/LC09/C02/T2_L2 USGS Landsat 9 Level 2, Collection 2, Tier 2 image_collection ee.ImageCollection('LANDSAT/LC09/C02/T2_L2') USGS 2021-10-31 2023-10-17 -180, -90, 180, 90 False cfmask, cloud, fmask, global, l9sr, landsat, lasrc, lc09, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T2_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2_L2 proprietary +LANDSAT/LC09/C02/T2_TOA USGS Landsat 9 Collection 2 Tier 2 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC09/C02/T2_TOA') USGS/Google 2021-11-02 2023-10-19 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T2_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2_TOA PDDL-1.0 LANDSAT/LC8 USGS Landsat 8 Raw Scenes [deprecated] image_collection ee.ImageCollection('LANDSAT/LC8') USGS 2013-04-11 2017-05-01 -180, -90, 180, 90 True global, l8, landsat, lc8, oli_tirs, radiance, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC8.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC8 PDDL-1.0 LANDSAT/LC8_L1T USGS Landsat 8 Raw Scenes (Orthorectified) [deprecated] image_collection ee.ImageCollection('LANDSAT/LC8_L1T') USGS 2013-04-11 2017-05-01 -180, -90, 180, 90 True global, l8, landsat, lc8, oli_tirs, radiance, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC8_L1T.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC8_L1T PDDL-1.0 LANDSAT/LC8_L1T_32DAY_BAI Landsat 8 32-Day BAI Composite [deprecated] image_collection ee.ImageCollection('LANDSAT/LC8_L1T_32DAY_BAI') USGS 2013-04-07 2017-04-07 -180, -90, 180, 90 True bai, landsat, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC8_L1T_32DAY_BAI.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC8_L1T_32DAY_BAI PDDL-1.0 @@ -368,14 +368,14 @@ LANDSAT/LE07/C01/T1_TOA USGS Landsat 7 Collection 1 Tier 1 TOA Reflectance [depr LANDSAT/LE07/C01/T2 USGS Landsat 7 Collection 1 Tier 2 Raw Scenes [deprecated] image_collection ee.ImageCollection('LANDSAT/LE07/C01/T2') USGS 1999-05-28 2021-12-31 -180, -90, 180, 90 True c1, etm, global, l7, landsat, le7, radiance, t2, tier2, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C01_T2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C01_T2 PDDL-1.0 LANDSAT/LE07/C01/T2_SR USGS Landsat 7 Surface Reflectance Tier 2 [deprecated] image_collection ee.ImageCollection('LANDSAT/LE07/C01/T2_SR') USGS 1999-05-28 2021-10-17 -180, -90, 180, 90 True cfmask, cloud, fmask, global, landsat, le07, ledaps, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C01_T2_SR.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C01_T2_SR proprietary LANDSAT/LE07/C01/T2_TOA USGS Landsat 7 Collection 1 Tier 2 TOA Reflectance [deprecated] image_collection ee.ImageCollection('LANDSAT/LE07/C01/T2_TOA') USGS/Google 1999-05-28 2021-12-31 -180, -90, 180, 90 True global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C01_T2_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C01_T2_TOA PDDL-1.0 -LANDSAT/LE07/C02/T1 USGS Landsat 7 Collection 2 Tier 1 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LE07/C02/T1') USGS 1999-05-28 2023-09-21 -180, -90, 180, 90 False c2, etm, global, l7, landsat, le7, radiance, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T1.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T1 PDDL-1.0 -LANDSAT/LE07/C02/T1_L2 USGS Landsat 7 Level 2, Collection 2, Tier 1 image_collection ee.ImageCollection('LANDSAT/LE07/C02/T1_L2') USGS 1999-05-28 2023-09-21 -180, -90, 180, 90 False cfmask, cloud, etm, fmask, global, landsat, lasrc, le07, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T1_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T1_L2 proprietary -LANDSAT/LE07/C02/T1_RT USGS Landsat 7 Collection 2 Tier 1 and Real-Time data Raw Scenes image_collection ee.ImageCollection('LANDSAT/LE07/C02/T1_RT') USGS 1999-05-28 2023-10-18 -180, -90, 180, 90 False c2, etm, global, l7, landsat, le7, nrt, radiance, rt, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T1_RT.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T1_RT PDDL-1.0 -LANDSAT/LE07/C02/T1_RT_TOA USGS Landsat 7 Collection 2 Tier 1 and Real-Time data TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LE07/C02/T1_RT_TOA') USGS/Google 1999-05-28 2023-10-18 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T1_RT_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T1_RT_TOA PDDL-1.0 -LANDSAT/LE07/C02/T1_TOA USGS Landsat 7 Collection 2 Tier 1 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LE07/C02/T1_TOA') USGS/Google 1999-05-28 2023-09-21 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T1_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T1_TOA PDDL-1.0 -LANDSAT/LE07/C02/T2 USGS Landsat 7 Collection 2 Tier 2 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LE07/C02/T2') USGS 1999-05-28 2023-09-21 -180, -90, 180, 90 False c2, etm, global, l7, landsat, le7, radiance, t2, tier2, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T2 PDDL-1.0 -LANDSAT/LE07/C02/T2_L2 USGS Landsat 7 Level 2, Collection 2, Tier 2 image_collection ee.ImageCollection('LANDSAT/LE07/C02/T2_L2') USGS 1999-05-28 2023-09-21 -180, -90, 180, 90 False cfmask, cloud, etm, fmask, global, landsat, lasrc, le07, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T2_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T2_L2 proprietary -LANDSAT/LE07/C02/T2_TOA USGS Landsat 7 Collection 2 Tier 2 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LE07/C02/T2_TOA') USGS/Google 2003-12-01 2023-09-21 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T2_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T2_TOA PDDL-1.0 +LANDSAT/LE07/C02/T1 USGS Landsat 7 Collection 2 Tier 1 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LE07/C02/T1') USGS 1999-05-28 2023-09-23 -180, -90, 180, 90 False c2, etm, global, l7, landsat, le7, radiance, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T1.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T1 PDDL-1.0 +LANDSAT/LE07/C02/T1_L2 USGS Landsat 7 Level 2, Collection 2, Tier 1 image_collection ee.ImageCollection('LANDSAT/LE07/C02/T1_L2') USGS 1999-05-28 2023-09-23 -180, -90, 180, 90 False cfmask, cloud, etm, fmask, global, landsat, lasrc, le07, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T1_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T1_L2 proprietary +LANDSAT/LE07/C02/T1_RT USGS Landsat 7 Collection 2 Tier 1 and Real-Time data Raw Scenes image_collection ee.ImageCollection('LANDSAT/LE07/C02/T1_RT') USGS 1999-05-28 2023-10-19 -180, -90, 180, 90 False c2, etm, global, l7, landsat, le7, nrt, radiance, rt, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T1_RT.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T1_RT PDDL-1.0 +LANDSAT/LE07/C02/T1_RT_TOA USGS Landsat 7 Collection 2 Tier 1 and Real-Time data TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LE07/C02/T1_RT_TOA') USGS/Google 1999-05-28 2023-10-19 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T1_RT_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T1_RT_TOA PDDL-1.0 +LANDSAT/LE07/C02/T1_TOA USGS Landsat 7 Collection 2 Tier 1 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LE07/C02/T1_TOA') USGS/Google 1999-05-28 2023-09-23 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T1_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T1_TOA PDDL-1.0 +LANDSAT/LE07/C02/T2 USGS Landsat 7 Collection 2 Tier 2 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LE07/C02/T2') USGS 1999-05-28 2023-09-22 -180, -90, 180, 90 False c2, etm, global, l7, landsat, le7, radiance, t2, tier2, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T2 PDDL-1.0 +LANDSAT/LE07/C02/T2_L2 USGS Landsat 7 Level 2, Collection 2, Tier 2 image_collection ee.ImageCollection('LANDSAT/LE07/C02/T2_L2') USGS 1999-05-28 2023-09-22 -180, -90, 180, 90 False cfmask, cloud, etm, fmask, global, landsat, lasrc, le07, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T2_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T2_L2 proprietary +LANDSAT/LE07/C02/T2_TOA USGS Landsat 7 Collection 2 Tier 2 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LE07/C02/T2_TOA') USGS/Google 2003-12-01 2023-09-22 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T2_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T2_TOA PDDL-1.0 LANDSAT/LE7 USGS Landsat 7 Raw Scenes [deprecated] image_collection ee.ImageCollection('LANDSAT/LE7') USGS 1999-05-28 2017-04-30 -180, -90, 180, 90 True etm, global, l7, landsat, le7, radiance, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE7.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE7 PDDL-1.0 LANDSAT/LE7_L1T USGS Landsat 7 Raw Scenes (Orthorectified) [deprecated] image_collection ee.ImageCollection('LANDSAT/LE7_L1T') USGS 1999-05-28 2017-04-30 -180, -90, 180, 90 True etm, global, l7, landsat, le7, radiance, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE7_L1T.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE7_L1T PDDL-1.0 LANDSAT/LE7_L1T_32DAY_BAI Landsat 7 32-Day BAI Composite [deprecated] image_collection ee.ImageCollection('LANDSAT/LE7_L1T_32DAY_BAI') USGS 1999-01-01 2017-04-07 -180, -90, 180, 90 True bai, landsat, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE7_L1T_32DAY_BAI.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE7_L1T_32DAY_BAI PDDL-1.0 @@ -641,7 +641,7 @@ MODIS/061/MCD12Q1 MCD12Q1.061 MODIS Land Cover Type Yearly Global 500m image_col MODIS/061/MCD12Q2 MCD12Q2.006 Land Cover Dynamics Yearly Global 500m image_collection ee.ImageCollection('MODIS/061/MCD12Q2') NASA LP DAAC at the USGS EROS Center 2001-01-01 2022-01-01 -180, -90, 180, 90 False evi, global, modis, onset_greenness, phenology, usgs, yearly https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD12Q2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD12Q2 proprietary MODIS/061/MCD15A3H MCD15A3H.061 MODIS Leaf Area Index/FPAR 4-Day Global 500m image_collection ee.ImageCollection('MODIS/061/MCD15A3H') NASA LP DAAC at the USGS EROS Center 2002-07-04 2023-10-08 -180, -90, 180, 90 False 4_day, fpar, global, lai, mcd15a3h, modis, nasa, usgs, vegetation https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD15A3H.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD15A3H proprietary MODIS/061/MCD18C2 MCD18C2.061 Photosynthetically Active Radiation Daily 3-Hour image_collection ee.ImageCollection('MODIS/061/MCD18C2') NASA LP DAAC at the USGS EROS Center 2002-02-24 2023-09-01 -180, -90, 180, 90 False par, radiation https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD18C2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD18C2 proprietary -MODIS/061/MCD19A1_GRANULES MCD19A1.061: Land Surface BRF Daily L2G Global 500m and 1km image_collection ee.ImageCollection('MODIS/061/MCD19A1_GRANULES') NASA LP DAAC at the USGS EROS Center 2000-12-21 2007-11-18 -180, -90, 180, 90 False aerosol, aod, aqua, daily, global, maiac, modis, nasa, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD19A1_GRANULES.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD19A1_GRANULES proprietary +MODIS/061/MCD19A1_GRANULES MCD19A1.061: Land Surface BRF Daily L2G Global 500m and 1km image_collection ee.ImageCollection('MODIS/061/MCD19A1_GRANULES') NASA LP DAAC at the USGS EROS Center 2000-12-21 2008-02-04 -180, -90, 180, 90 False aerosol, aod, aqua, daily, global, maiac, modis, nasa, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD19A1_GRANULES.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD19A1_GRANULES proprietary MODIS/061/MCD19A2_GRANULES MCD19A2.061: Terra & Aqua MAIAC Land Aerosol Optical Depth Daily 1km image_collection ee.ImageCollection('MODIS/061/MCD19A2_GRANULES') NASA LP DAAC at the USGS EROS Center 2000-02-24 2023-10-16 -180, -90, 180, 90 False aerosol, aod, aqua, daily, global, maiac, mcd19a2, modis, nasa, terra, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD19A2_GRANULES.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD19A2_GRANULES proprietary MODIS/061/MCD43A1 MCD43A1.061 MODIS BRDF-Albedo Model Parameters Daily 500m image_collection ee.ImageCollection('MODIS/061/MCD43A1') NASA LP DAAC at the USGS EROS Center 2000-02-24 2023-10-04 -180, -90, 180, 90 False albedo, brdf, daily, global, mcd43a1, modis, nasa, reflectance, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD43A1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD43A1 proprietary MODIS/061/MCD43A2 MCD43A2.061 MODIS BRDF-Albedo Quality Daily 500m image_collection ee.ImageCollection('MODIS/061/MCD43A2') NASA LP DAAC at the USGS EROS Center 2000-02-24 2023-10-04 -180, -90, 180, 90 False albedo, brdf, daily, global, modis, nasa, quality, reflectance, usgs https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_061_MCD43A2.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MCD43A2 proprietary @@ -771,7 +771,7 @@ NASA/GSFC/MERRA/flx/2 MERRA-2 M2T1NXFLX: Surface Flux Diagnostics V5.12.4 image_ NASA/GSFC/MERRA/lnd/2 MERRA-2 M2T1NXLND: Land Surface Diagnostics V5.12.4 image_collection ee.ImageCollection('NASA/GSFC/MERRA/lnd/2') NASA/MERRA 1980-01-01 2023-09-01 -180, -90, 180, 90 False evaporation, ice, merra, temperature https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GSFC_MERRA_lnd_2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GSFC_MERRA_lnd_2 proprietary NASA/GSFC/MERRA/rad/2 MERRA-2 M2T1NXRAD: Radiation Diagnostics V5.12.4 image_collection ee.ImageCollection('NASA/GSFC/MERRA/rad/2') NASA/MERRA 1980-01-01 2023-09-01 -180, -90, 180, 90 False albedo, emissivity, merra, shortwave, temperature https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GSFC_MERRA_rad_2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GSFC_MERRA_rad_2 proprietary NASA/GSFC/MERRA/slv/2 MERRA-2 M2T1NXSLV: Single-Level Diagnostics V5.12.4 image_collection ee.ImageCollection('NASA/GSFC/MERRA/slv/2') NASA/MERRA 1980-01-01 2023-09-01 -180, -90, 180, 90 False condensation, humidity, merra, nasa, omega, pressure, slv, temperature, vapor, water, wind https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GSFC_MERRA_slv_2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GSFC_MERRA_slv_2 proprietary -NASA/HLS/HLSL30/v002 HLSL30: HLS-2 Landsat Operational Land Imager Surface Reflectance and TOA Brightness Daily Global 30m image_collection ee.ImageCollection('NASA/HLS/HLSL30/v002') USGS 2013-04-11 2023-10-14 -180, -90, 180, 90 False landsat, nasa, sentinel, usgs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_HLS_HLSL30_v002.json https://developers.google.com/earth-engine/datasets/catalog/NASA_HLS_HLSL30_v002 proprietary +NASA/HLS/HLSL30/v002 HLSL30: HLS-2 Landsat Operational Land Imager Surface Reflectance and TOA Brightness Daily Global 30m image_collection ee.ImageCollection('NASA/HLS/HLSL30/v002') USGS 2013-04-11 2023-10-15 -180, -90, 180, 90 False landsat, nasa, sentinel, usgs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_HLS_HLSL30_v002.json https://developers.google.com/earth-engine/datasets/catalog/NASA_HLS_HLSL30_v002 proprietary NASA/JPL/global_forest_canopy_height_2005 Global Forest Canopy Height, 2005 image ee.Image('NASA/JPL/global_forest_canopy_height_2005') NASA/JPL 2005-05-20 2005-06-23 -180, -90, 180, 90 False canopy, forest, geophysical, glas, jpl, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_JPL_global_forest_canopy_height_2005.json https://developers.google.com/earth-engine/datasets/catalog/NASA_JPL_global_forest_canopy_height_2005 proprietary NASA/MEASURES/GFCC/TC/v3 Global Forest Cover Change (GFCC) Tree Cover Multi-Year Global 30m image_collection ee.ImageCollection('NASA/MEASURES/GFCC/TC/v3') NASA LP DAAC at the USGS EROS Center 2000-01-01 2015-01-01 -180, -90, 180, 90 False forest, glcf, landsat_derived, nasa, umd https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_MEASURES_GFCC_TC_v3.json https://developers.google.com/earth-engine/datasets/catalog/NASA_MEASURES_GFCC_TC_v3 proprietary NASA/NASADEM_HGT/001 NASADEM: NASA NASADEM Digital Elevation 30m image ee.Image('NASA/NASADEM_HGT/001') NASA / USGS / JPL-Caltech 2000-02-11 2000-02-22 -180, -56, 180, 60 False dem, elevation, geophysical, nasa, nasadem, srtm, topography, usgs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_NASADEM_HGT_001.json https://developers.google.com/earth-engine/datasets/catalog/NASA_NASADEM_HGT_001 proprietary @@ -812,22 +812,22 @@ NOAA/CFSR CFSR: Climate Forecast System Reanalysis image_collection ee.ImageColl NOAA/CFSV2/FOR6H CFSV2: NCEP Climate Forecast System Version 2, 6-Hourly Products image_collection ee.ImageCollection('NOAA/CFSV2/FOR6H') NOAA NWS National Centers for Environmental Prediction (NCEP) 1979-01-01 2023-10-18 -180, -90, 180, 90 False climate, daylight, flux, forecast, geophysical, ncep, noaa, nws, precipitation, radiation, snow, temperature, vapor, water, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CFSV2_FOR6H.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CFSV2_FOR6H proprietary NOAA/DMSP-OLS/CALIBRATED_LIGHTS_V4 DMSP OLS: Global Radiance-Calibrated Nighttime Lights Version 4, Defense Meteorological Program Operational Linescan System image_collection ee.ImageCollection('NOAA/DMSP-OLS/CALIBRATED_LIGHTS_V4') Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines 1996-03-16 2011-07-31 -180, -65, 180, 75 False calibrated, dmsp, eog, imagery, lights, nighttime, ols, radiance, visible, yearly https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_DMSP-OLS_CALIBRATED_LIGHTS_V4.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_DMSP-OLS_CALIBRATED_LIGHTS_V4 proprietary NOAA/DMSP-OLS/NIGHTTIME_LIGHTS DMSP OLS: Nighttime Lights Time Series Version 4, Defense Meteorological Program Operational Linescan System image_collection ee.ImageCollection('NOAA/DMSP-OLS/NIGHTTIME_LIGHTS') Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines 1992-01-01 2014-01-01 -180, -65, 180, 75 False dmsp, eog, imagery, lights, nighttime, ols, visible, yearly https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_DMSP-OLS_NIGHTTIME_LIGHTS.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_DMSP-OLS_NIGHTTIME_LIGHTS proprietary -NOAA/GFS0P25 GFS: Global Forecast System 384-Hour Predicted Atmosphere Data image_collection ee.ImageCollection('NOAA/GFS0P25') NOAA/NCEP/EMC 2015-07-01 2023-10-18 -180, -90, 180, 90 False climate, cloud, emc, flux, forecast, geophysical, gfs, humidity, ncep, noaa, precipitation, radiation, temperature, vapor, weather, wind https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GFS0P25.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GFS0P25 proprietary -NOAA/GOES/16/FDCC GOES-16 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/16/FDCC') NOAA 2017-05-24 2023-10-18 -152.11, 14, -49.18, 56.77 False abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_FDCC proprietary -NOAA/GOES/16/FDCF GOES-16 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/16/FDCF') NOAA 2017-05-24 2023-10-18 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_FDCF proprietary -NOAA/GOES/16/MCMIPC GOES-16 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPC') NOAA 2017-07-10 2023-10-18 -152.11, 14, -49.18, 56.77 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPC proprietary -NOAA/GOES/16/MCMIPF GOES-16 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPF') NOAA 2017-07-10 2023-10-18 -180, -90, 180, 90 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPF proprietary -NOAA/GOES/16/MCMIPM GOES-16 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Mesoscale image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPM') NOAA 2017-07-10 2023-10-18 -180, -90, 180, 90 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPM proprietary +NOAA/GFS0P25 GFS: Global Forecast System 384-Hour Predicted Atmosphere Data image_collection ee.ImageCollection('NOAA/GFS0P25') NOAA/NCEP/EMC 2015-07-01 2023-10-19 -180, -90, 180, 90 False climate, cloud, emc, flux, forecast, geophysical, gfs, humidity, ncep, noaa, precipitation, radiation, temperature, vapor, weather, wind https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GFS0P25.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GFS0P25 proprietary +NOAA/GOES/16/FDCC GOES-16 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/16/FDCC') NOAA 2017-05-24 2023-10-19 -152.11, 14, -49.18, 56.77 False abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_FDCC proprietary +NOAA/GOES/16/FDCF GOES-16 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/16/FDCF') NOAA 2017-05-24 2023-10-19 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_FDCF proprietary +NOAA/GOES/16/MCMIPC GOES-16 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPC') NOAA 2017-07-10 2023-10-19 -152.11, 14, -49.18, 56.77 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPC proprietary +NOAA/GOES/16/MCMIPF GOES-16 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPF') NOAA 2017-07-10 2023-10-19 -180, -90, 180, 90 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPF proprietary +NOAA/GOES/16/MCMIPM GOES-16 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Mesoscale image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPM') NOAA 2017-07-10 2023-10-19 -180, -90, 180, 90 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPM proprietary NOAA/GOES/17/FDCC GOES-17 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/17/FDCC') NOAA 2018-08-27 2023-01-10 -180, 14.57, 180, 53.51 False abi, climate, fdc, fire, goes, goes_17, goes_s, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_FDCC proprietary NOAA/GOES/17/FDCF GOES-17 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/17/FDCF') NOAA 2018-08-27 2023-01-10 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_17, goes_s, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_FDCF proprietary NOAA/GOES/17/MCMIPC GOES-17 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/17/MCMIPC') NOAA 2018-12-04 2023-01-10 -180, 14.57, 180, 53.51 False abi, climate, goes, goes_17, goes_s, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_MCMIPC proprietary NOAA/GOES/17/MCMIPF GOES-17 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/17/MCMIPF') NOAA 2018-12-04 2023-01-10 -180, -90, 180, 90 False abi, climate, goes, goes_17, goes_s, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_MCMIPF proprietary NOAA/GOES/17/MCMIPM GOES-17 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/17/MCMIPM') NOAA 2018-12-04 2023-01-10 -180, -90, 180, 90 False abi, climate, goes, goes_17, goes_s, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_MCMIPM proprietary -NOAA/GOES/18/FDCC GOES-18 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/18/FDCC') NOAA 2022-10-13 2023-10-18 -180, 14.57, 180, 53.51 False abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_FDCC proprietary -NOAA/GOES/18/FDCF GOES-18 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/FDCF') NOAA 2022-10-13 2023-10-18 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_FDCF proprietary -NOAA/GOES/18/MCMIPC GOES-18 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPC') NOAA 2018-12-04 2023-10-18 -180, 14.57, 180, 53.51 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPC proprietary -NOAA/GOES/18/MCMIPF GOES-18 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPF') NOAA 2018-12-04 2023-10-18 -180, -90, 180, 90 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPF proprietary -NOAA/GOES/18/MCMIPM GOES-18 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPM') NOAA 2018-12-04 2023-10-18 -180, -90, 180, 90 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPM proprietary +NOAA/GOES/18/FDCC GOES-18 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/18/FDCC') NOAA 2022-10-13 2023-10-19 -180, 14.57, 180, 53.51 False abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_FDCC proprietary +NOAA/GOES/18/FDCF GOES-18 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/FDCF') NOAA 2022-10-13 2023-10-19 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_FDCF proprietary +NOAA/GOES/18/MCMIPC GOES-18 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPC') NOAA 2018-12-04 2023-10-19 -180, 14.57, 180, 53.51 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPC proprietary +NOAA/GOES/18/MCMIPF GOES-18 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPF') NOAA 2018-12-04 2023-10-19 -180, -90, 180, 90 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPF proprietary +NOAA/GOES/18/MCMIPM GOES-18 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPM') NOAA 2018-12-04 2023-10-19 -180, -90, 180, 90 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPM proprietary NOAA/NCEP_DOE_RE2/total_cloud_coverage NCEP-DOE Reanalysis 2 (Gaussian Grid), Total Cloud Coverage image_collection ee.ImageCollection('NOAA/NCEP_DOE_RE2/total_cloud_coverage') NOAA 1979-01-01 2023-09-30 -180, -90, 180, 90 False atmosphere, climate, cloud, geophysical, ncep, noaa, reanalysis https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NCEP_DOE_RE2_total_cloud_coverage.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NCEP_DOE_RE2_total_cloud_coverage proprietary NOAA/NGDC/ETOPO1 ETOPO1: Global 1 Arc-Minute Elevation image ee.Image('NOAA/NGDC/ETOPO1') NOAA 2008-08-01 2008-08-01 -180, -90, 180, 90 False bedrock, dem, elevation, geophysical, ice, noaa, topography https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NGDC_ETOPO1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NGDC_ETOPO1 proprietary NOAA/NHC/HURDAT2/atlantic NOAA NHC HURDAT2 Atlantic Hurricane Catalog table ee.FeatureCollection('NOAA/NHC/HURDAT2/atlantic') NOAA NHC 1851-06-25 2018-11-04 -109.5, 7.2, 63, 81 False hurricane, nhc, noaa, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NHC_HURDAT2_atlantic.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NHC_HURDAT2_atlantic proprietary @@ -842,8 +842,8 @@ NOAA/VIIRS/001/VNP15A2H VNP15A2H: LAI/FPAR 8-Day L4 Global 500m SIN Grid image_c NOAA/VIIRS/001/VNP21A1D VNP21A1D: Day Land Surface Temperature and Emissivity Daily 1km image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP21A1D') NASA LP DAAC at the USGS EROS Center 2012-01-19 2023-09-01 -180, -90, 180, 90 False daily, day, land, nasa, noaa, surface, temperature, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP21A1D.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP21A1D proprietary NOAA/VIIRS/001/VNP21A1N VNP21A1N: Night Land Surface Temperature and Emissivity Daily 1km image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP21A1N') NASA LP DAAC at the USGS EROS Center 2012-01-19 2023-09-01 -180, -90, 180, 90 False daily, land, nasa, night, noaa, surface, temperature, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP21A1N.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP21A1N proprietary NOAA/VIIRS/001/VNP22Q2 VNP22Q2: Land Surface Phenology Yearly L3 Global 500m SIN Grid image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP22Q2') NASA LP DAAC at the USGS EROS Center 2013-01-01 2022-01-01 -180, -90, 180, 90 False land, nasa, ndvi, noaa, npp, onset_greenness, phenology, surface, vegetation, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP22Q2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP22Q2 proprietary -NOAA/VIIRS/001/VNP43IA1 VNP43IA1: BRDF/Albedo Model Parameters Daily L3 Global 500m SIN Grid image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP43IA1') NASA LP DAAC at the USGS EROS Center 2012-01-17 2023-10-08 -180, -90, 180, 90 False land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP43IA1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP43IA1 proprietary -NOAA/VIIRS/001/VNP43IA2 VNP43IA2: BRDF/Albedo Quality Daily L3 Global 500m SIN Grid image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP43IA2') NASA LP DAAC at the USGS EROS Center 2012-01-17 2023-10-08 -180, -90, 180, 90 False land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP43IA2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP43IA2 proprietary +NOAA/VIIRS/001/VNP43IA1 VNP43IA1: BRDF/Albedo Model Parameters Daily L3 Global 500m SIN Grid image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP43IA1') NASA LP DAAC at the USGS EROS Center 2012-01-17 2023-10-09 -180, -90, 180, 90 False land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP43IA1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP43IA1 proprietary +NOAA/VIIRS/001/VNP43IA2 VNP43IA2: BRDF/Albedo Quality Daily L3 Global 500m SIN Grid image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP43IA2') NASA LP DAAC at the USGS EROS Center 2012-01-17 2023-10-09 -180, -90, 180, 90 False land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP43IA2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP43IA2 proprietary NOAA/VIIRS/001/VNP46A1 VNP46A1: VIIRS Daily Gridded Day Night Band 500m Linear Lat Lon Grid Night image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP46A1') NASA LP DAAC at the USGS EROS Center 2012-01-19 2023-10-16 -180, -90, 180, 90 False daily, dnb, nasa, noaa, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP46A1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP46A1 proprietary NOAA/VIIRS/001/VNP46A2 VNP46A2: VIIRS Lunar Gap-Filled BRDF Nighttime Lights Daily L3 Global 500m image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP46A2') NASA LP DAAC at the USGS EROS Center 2012-01-19 2023-06-12 -180, -90, 180, 90 False brdf, daily, nasa, noaa, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP46A2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP46A2 proprietary NOAA/VIIRS/001/VNP64A1 VNP64A1: Burned Area Monthly L4 Global 500m SIN Grid image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP64A1') NASA LP DAAC at the USGS EROS Center 2014-01-01 2019-01-01 -180, -90, 180, 90 False burn, land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP64A1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP64A1 proprietary @@ -914,7 +914,7 @@ TIGER/2018/States TIGER: US Census States 2018 table ee.FeatureCollection('TIGER TIGER/2020/BG TIGER: US Census Block Groups (BG) 2020 table ee.FeatureCollection('TIGER/2020/BG') United States Census Bureau 2020-01-01 2020-01-02 -180, -14.69, -64.435, 71.567 False census, city, neighborhood, tiger, urban, us https://storage.googleapis.com/earthengine-stac/catalog/TIGER/TIGER_2020_BG.json https://developers.google.com/earth-engine/datasets/catalog/TIGER_2020_BG proprietary TIGER/2020/TABBLOCK20 TIGER: 2020 Tabulation (Census) Block table ee.FeatureCollection('TIGER/2020/TABBLOCK20') United States Census Bureau 2020-01-01 2020-01-02 -180, -14.69, -64.435, 71.567 False census, city, neighborhood, tiger, urban, us https://storage.googleapis.com/earthengine-stac/catalog/TIGER/TIGER_2020_TABBLOCK20.json https://developers.google.com/earth-engine/datasets/catalog/TIGER_2020_TABBLOCK20 proprietary TIGER/2020/TRACT TIGER: US Census Tracts table ee.FeatureCollection('TIGER/2020/TRACT') United States Census Bureau 2020-01-01 2020-01-02 -180, -14.69, -64.435, 71.567 False census, city, neighborhood, tiger, urban, us https://storage.googleapis.com/earthengine-stac/catalog/TIGER/TIGER_2020_TRACT.json https://developers.google.com/earth-engine/datasets/catalog/TIGER_2020_TRACT proprietary -TOMS/MERGED TOMS and OMI Merged Ozone Data image_collection ee.ImageCollection('TOMS/MERGED') NASA / GES DISC 1978-11-01 2023-10-15 -180, -90, 180, 90 False atmosphere, aura, climate, geophysical, ges_disc, goddard, nasa, omi, ozone, toms https://storage.googleapis.com/earthengine-stac/catalog/TOMS/TOMS_MERGED.json https://developers.google.com/earth-engine/datasets/catalog/TOMS_MERGED proprietary +TOMS/MERGED TOMS and OMI Merged Ozone Data image_collection ee.ImageCollection('TOMS/MERGED') NASA / GES DISC 1978-11-01 2023-10-16 -180, -90, 180, 90 False atmosphere, aura, climate, geophysical, ges_disc, goddard, nasa, omi, ozone, toms https://storage.googleapis.com/earthengine-stac/catalog/TOMS/TOMS_MERGED.json https://developers.google.com/earth-engine/datasets/catalog/TOMS_MERGED proprietary TRMM/3B42 TRMM 3B42: 3-Hourly Precipitation Estimates image_collection ee.ImageCollection('TRMM/3B42') NASA GES DISC at NASA Goddard Space Flight Center 1998-01-01 2019-12-31 -180, -50, 180, 50 False 3_hourly, climate, geophysical, jaxa, nasa, precipitation, rainfall, trmm, weather https://storage.googleapis.com/earthengine-stac/catalog/TRMM/TRMM_3B42.json https://developers.google.com/earth-engine/datasets/catalog/TRMM_3B42 proprietary TRMM/3B43V7 TRMM 3B43: Monthly Precipitation Estimates image_collection ee.ImageCollection('TRMM/3B43V7') NASA GES DISC at NASA Goddard Space Flight Center 1998-01-01 2019-12-01 -180, -50, 180, 50 False climate, geophysical, jaxa, nasa, precipitation, rainfall, trmm, weather https://storage.googleapis.com/earthengine-stac/catalog/TRMM/TRMM_3B43V7.json https://developers.google.com/earth-engine/datasets/catalog/TRMM_3B43V7 proprietary TUBerlin/BigEarthNet/v1 TUBerlin/BigEarthNet/v1 image_collection ee.ImageCollection('TUBerlin/BigEarthNet/v1') BigEarthNet 2017-06-01 2018-05-31 -9, 36.9, 31.6, 68.1 False chip, copernicus, corine_derived, label, ml, sentinel, tile https://storage.googleapis.com/earthengine-stac/catalog/TUBerlin/TUBerlin_BigEarthNet_v1.json https://developers.google.com/earth-engine/datasets/catalog/TUBerlin_BigEarthNet_v1 proprietary diff --git a/nasa_cmr_catalog.json b/nasa_cmr_catalog.json index dc43794..4050e94 100644 --- a/nasa_cmr_catalog.json +++ b/nasa_cmr_catalog.json @@ -25,6 +25,58 @@ "description": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. This dataset comprises the Level 3 aerosol daily and monthly gridded products from MERIS for 2008, using the ALAMO algorithm, version 2.2. The data have been provided by Hygeos.For further details about these data products please see the linked documentation.", "license": "not-provided" }, + { + "id": "12-hourly_interpolated_surface_position_from_buoys", + "title": "12-Hourly Interpolated Surface Position from Buoys", + "catalog": "SCIOPS", + "state_date": "1979-01-01", + "end_date": "2009-12-01", + "bbox": "-180, 60, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214600619-SCIOPS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214600619-SCIOPS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/12-hourly_interpolated_surface_position_from_buoys", + "description": "This data set contains Arctic Ocean daily buoy positions interpolated to hours 0Z and 12Z.", + "license": "not-provided" + }, + { + "id": "12-hourly_interpolated_surface_velocity_from_buoys", + "title": "12-Hourly Interpolated Surface Velocity from Buoys", + "catalog": "SCIOPS", + "state_date": "1979-01-01", + "end_date": "2009-12-02", + "bbox": "-180, 74, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214600621-SCIOPS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214600621-SCIOPS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/12-hourly_interpolated_surface_velocity_from_buoys", + "description": "This data set contains 12-hourly interpolated surface velocity data from buoys. Point grid: Latitude 74N to 90N - 4 degree increment Longitude 0E to 320E - 20 and 40 degree increment.", + "license": "not-provided" + }, + { + "id": "12_hourly_interpolated_surface_air_pressure_from_buoys", + "title": "12 Hourly Interpolated Surface Air Pressure from Buoys", + "catalog": "SCIOPS", + "state_date": "1979-01-01", + "end_date": "2007-11-30", + "bbox": "-180, 70, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214600618-SCIOPS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214600618-SCIOPS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/12_hourly_interpolated_surface_air_pressure_from_buoys", + "description": "Optimally interpolated atmospheric surface pressure over the Arctic Ocean Basin. Temporal format - twice daily (0Z and 12Z) Spatial format - 2 degree latitude x 10 degree longitude - latitude: 70 N - 90 N - longitude: 0 E - 350 E", + "license": "not-provided" + }, + { + "id": "14c_of_soil_co2_from_ipy_itex_cross_site_comparison", + "title": "14C of soil CO2 from IPY ITEX Cross Site Comparison", + "catalog": "SCIOPS", + "state_date": "2008-01-16", + "end_date": "2008-01-21", + "bbox": "-157.4, -36.9, 147.29, 71.3", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214602443-SCIOPS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214602443-SCIOPS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/14c_of_soil_co2_from_ipy_itex_cross_site_comparison", + "description": "Study sites: Toolik Lake Field Station Alaska, USA 68.63 N, 149.57 W; Atqasuk, Alaska USA 70.45 N, 157.40 W; Barrow, Alaska, USA 71.30 N, 156.67 W; Latnjajaure, Sweden 68.35 N, 18.50 E; Falls Creek, Australia: Site 2-unburned 36.90 S 147.29 E; Site 3-burned 36.89 S 147.28 E. Additional sites will be added summer 2008, but the exact sites are not finalized. Purpose: Collect soil CO2 for analysis of radiocarbon to evaluate the age of the carbon respired in controls and warmed plots from across the ITEX network. Treatments: control and ITEX OTC warming experiment (1994-2007). Design: 5 replicates of each treatment at dry site and moist site. Sampling frequency: Once per peak season.", + "license": "not-provided" + }, { "id": "200708_CEAMARC_CASO_TRACE_ELEMENT_SAMPLES.v1", "title": "2007-08 CEAMARC-CASO VOYAGE TRACE ELEMENT SAMPLING AROUND AN ICEBERG", @@ -571,58 +623,6 @@ "description": "The ACIDD (Across the Channel Investigating Diel Dynamics) project, in the Santa Barbara Channel, was initially designed to characterize daily variations in phytoplankton populations, but with the Thomas Fire in the Santa Barbara Hills December 2017, this project evolved into a study to characterize the effects of smoke and ash on the mixed layer in the Santa Barbara Channel.", "license": "not-provided" }, - { - "id": "ACOS_L2S.v7.3", - "title": "ACOS GOSAT/TANSO-FTS Level 2 Full Physics Standard Product V7.3 (ACOS_L2S) at GES DISC", - "catalog": "GES_DISC", - "state_date": "2009-04-20", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1339230297-GES_DISC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1339230297-GES_DISC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/ACOS_L2S.v7.3", - "description": "Version 7.3 is the current version of the data set. Version 3.5 is no longer available and has been superseded by Version 7.3. This data set is currently provided by the OCO (Orbiting Carbon Observatory) Project. In expectation of the OCO-2 launch, the algorithm was developed by the Atmospheric CO2 Observations from Space (ACOS) Task as a preparatory project, using GOSAT TANSO-FTS spectra. After the OCO-2 launch, \"ACOS\" data are still produced and improved, using approaches applied to the OCO-2 spectra. The \"ACOS\" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances, and algorithm build version 7.3. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the \"ACOS\" Level 2 production process. Even though the GES DISC is not publicly distributing Level 1B ACOS products, it should be known that changes in this version are affecting both Level 1B and Level 2 data. An important enhancement in Level1B will address the degradation in the number of quality-passed soundings. Elimination of many systematic biases, and better agreement with TCCON (Total Carbon Column Observing Network), is expected in Level 2 retrievals. The key changes to the L2 algorithm include scaling the O2-A band spectroscopy (reducing XCO2 bias by 4 or 5 ppm); using interpolation with the instrument lineshape [ ILS ] (reducing XCO2 bias by 1.5 ppm); and fitting a zero level offset to the A-band. Users have to also carefully familiarize themselves with the disclaimer in the new documentation. An important element to note are the updates on data screening. Although a Master Quality Flag is provided in the data product, further analysis of a larger set of data has allowed the science team to provide an updated set of screening criteria. These are listed in the data user's guide, and are recommended instead of the Master Quality Flag. Lastly, users should continue to carefully observe and weigh information from three important flags: \"warn_level\" - Provides a value that summarizes each sounding's acceptability to a larger set of quality filters. A high warn level predicts that the sounding would fail most data filters applied to it. A low warn level suggests that the sounding would pass most quality filters that might be applied. \"sounding_qual_flag\" - quality of input data provided to the retrieval processing \"outcome_flag\" - retrieval quality based upon certain internal thresholds (not thoroughly evaluated) \"master_quality_flag\" - four possible values: \"Good\", \"Caution\" and \"Bad\", and \"Failed\", as determined from other flags in the L2 productThe short name for this data type is ACOS_L2S.", - "license": "not-provided" - }, - { - "id": "ACOS_L2S.v9r", - "title": "ACOS GOSAT/TANSO-FTS Level 2 Full Physics Standard Product V9r (ACOS_L2S) at GES DISC", - "catalog": "GES_DISC", - "state_date": "2009-04-20", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1633158704-GES_DISC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1633158704-GES_DISC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/ACOS_L2S.v9r", - "description": "Version 9r is the current version of the data set. Older versions will no longer be available and are superseded by Version 9r. This data set is currently provided by the OCO (Orbiting Carbon Observatory) Project. In expectation of the OCO-2 launch, the algorithm was developed by the Atmospheric CO2 Observations from Space (ACOS) Task as a preparatory project, using GOSAT TANSO-FTS spectra. After the OCO-2 launch, \"ACOS\" data are still produced and improved, using approaches applied to the OCO-2 spectra. The \"ACOS\" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances, and algorithm build version 7.3. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the \"ACOS\" Level 2 production process. Even though the GES DISC is not publicly distributing Level 1B ACOS products, it should be known that changes in this version are affecting both Level 1B and Level 2 data. An important enhancement in Level1B will address the degradation in the number of quality-passed soundings. Elimination of many systematic biases, and better agreement with TCCON (Total Carbon Column Observing Network), is expected in Level 2 retrievals. The key changes to the L2 algorithm include scaling the O2-A band spectroscopy (reducing XCO2 bias by 4 or 5 ppm); using interpolation with the instrument lineshape [ ILS ] (reducing XCO2 bias by 1.5 ppm); and fitting a zero level offset to the A-band. Users have to also carefully familiarize themselves with the disclaimer in the new documentation. An important element to note are the updates on data screening. Although a Master Quality Flag is provided in the data product, further analysis of a larger set of data has allowed the science team to provide an updated set of screening criteria. These are listed in the data user's guide, and are recommended instead of the Master Quality Flag. Lastly, users should continue to carefully observe and weigh information from three important flags: \"sounding_qual_flag\" - quality of input data provided to the retrieval processing \"outcome_flag\" - retrieval quality based upon certain internal thresholds (not thoroughly evaluated) ", - "license": "not-provided" - }, - { - "id": "ACOS_L2_Lite_FP.v7.3", - "title": "ACOS GOSAT/TANSO-FTS Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files V7.3 (ACOS_L2_Lite_FP) at GES DISC", - "catalog": "GES_DISC", - "state_date": "2009-04-21", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1339230298-GES_DISC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1339230298-GES_DISC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/ACOS_L2_Lite_FP.v7.3", - "description": "The ACOS Lite files contain bias-corrected XCO2 along with other select fields aggregated as daily files. Orbital granules of the ACOS Level 2 standard product (ACOS_L2S) are used as input. The \"ACOS\" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the \"ACOS\" Level 2 production process.", - "license": "not-provided" - }, - { - "id": "ACOS_L2_Lite_FP.v9r", - "title": "ACOS GOSAT/TANSO-FTS Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files V9r (ACOS_L2_Lite_FP) at GES DISC", - "catalog": "GES_DISC", - "state_date": "2009-04-20", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1720416694-GES_DISC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1720416694-GES_DISC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/ACOS_L2_Lite_FP.v9r", - "description": "Version 9r is the current version of the data set. Older versions will no longer be available and are superseded by Version 9r. The ACOS Lite files contain bias-corrected XCO2 along with other select fields aggregated as daily files. Orbital granules of the ACOS Level 2 standard product (ACOS_L2S) are used as input. The \"ACOS\" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the \"ACOS\" Level 2 production process.", - "license": "not-provided" - }, { "id": "ACR3L2DM.v1", "title": "ACRIM III Level 2 Daily Mean Data V001", @@ -935,19 +935,6 @@ "description": "Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) is a collection of monthly files (see known issues for gaps) for each year of global emissivity. The ASTER GED data products are generated for 2000 through 2015 using the ASTER Temperature Emissivity Separation (TES) algorithm atmospheric correction method. This algorithm method uses Moderate Resolution Imaging Spectroradiometer (MODIS) Atmospheric Profiles product (MOD07) (https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html) and the MODerate spectral resolution TRANsmittance (MODTRAN) 5.2 radiative transfer model along with the snow cover data from the standard monthly MODIS/Terra snow cover monthly global 0.05 degree product (MOD10CM) (https://doi.org/10.5067/MODIS/MOD10CM.006), and vegetation information from the MODIS monthly gridded NDVI product (MOD13C2) (https://doi.org/10.5067/MODIS/MOD13C2.006). ASTER GED Monthly V041 data products are offered in Hierarchical Data Format 5 (HDF5). The National Aeronautics and Space Administration\u2019s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product.", "license": "not-provided" }, - { - "id": "AIRABRAD.v005", - "title": "AIRS/Aqua L1B AMSU (A1/A2) geolocated and calibrated brightness temperatures V005 (AIRABRAD) at GES DISC", - "catalog": "GES_DISC", - "state_date": "2002-05-21", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1243477366-GES_DISC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1243477366-GES_DISC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/AIRABRAD.v005", - "description": "The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. The AMSU-A instrument is co-aligned with AIRS so that successive blocks of 3 x 3 AIRS footprints are contained within one AMSU-A footprint. AMSU-A is primarily a temperature sounder that provides atmospheric information in the presence of clouds, which can be used to correct the AIRS infrared measurements for the effects of clouds. This is possible because non-precipitating clouds are for the most part transparent to microwave radiation, in contrast to visible and infrared radiation which are strongly scattered and absorbed by clouds. AMSU-A1 has 13 channels from 50 - 90 GHz and AMSU-A2 has 2 channels from 23 - 32 GHz. The AIRABRAD_005 products are stored in files (often referred to as \"granules\") that contain 6 minutes of data, 30 footprints across track by 45 lines along track.", - "license": "not-provided" - }, { "id": "AIRSAR_INT_JPG.v1", "title": "AIRSAR_ALONGTRACK_INTERFEROMETRY_JPG", @@ -1078,71 +1065,6 @@ "description": "AIRSAR topographic SAR digital elevation model P_Stokes product", "license": "not-provided" }, - { - "id": "AIRSM_CPR_MAT.v3.2", - "title": "AIRS-AMSU variables-CloudSat cloud mask, radar reflectivities, and cloud classification matchups V3.2 (AIRSM_CPR_MAT) at GES DISC", - "catalog": "GES_DISC", - "state_date": "2006-06-15", - "end_date": "2012-12-14", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1236224182-GES_DISC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1236224182-GES_DISC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/AIRSM_CPR_MAT.v3.2", - "description": "This is AIRS-CloudSat collocated subset, in NetCDF 4 format. These data contain collocated: AIRS/AMSU retrievals at AMSU footprints, CloudSat radar reflectivities, and MODIS cloud mask. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple \"A-train\" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, CloudSat), classify each \"scene\" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time \"matchups\" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRSM_CPR_MAT Parameters contained in the data files include the following: Variable Name|Description|Units CH4_total_column|Retrieved total column CH4| (molecules/cm2) CloudFraction|CloudSat/CALIPSO Cloud Fraction| (None) CloudLayers| Number of hydrometeor layers| (count) clrolr|Clear-sky Outgoing Longwave Radiation|(Watts/m**2) CO_total_column|Retrieved total column CO| (molecules/cm2) CPR_Cloud_mask| CPR Cloud Mask |(None) Data_quality| Data Quality |(None) H2OMMRSat|Water vapor saturation mass mixing ratio|(gm/kg) H2OMMRStd|Water Vapor Mass Mixing Ratio |(gm/kg dry air) MODIS_Cloud_Fraction| MODIS 250m Cloud Fraction| (None) MODIS_scene_var |MODIS scene variability| (None) nSurfStd|1-based index of the first valid level|(None) O3VMRStd|Ozone Volume Mixing Ratio|(vmr) olr|All-sky Outgoing Longwave Radiation|(Watts/m**2) Radar_Reflectivity| Radar Reflectivity Factor| (dBZe) Sigma-Zero| Sigma-Zero| (dB*100) TAirMWOnlyStd|Atmospheric Temperature retrieved using only MW|(K) TCldTopStd|Cloud top temperature|(K) totH2OStd|Total precipitable water vapor| (kg/m**2) totO3Std|Total ozone burden| (Dobson) TSurfAir|Atmospheric Temperature at Surface|(K) TSurfStd|Surface skin temperature|(K) End of parameter information", - "license": "not-provided" - }, - { - "id": "AIRS_CPR_IND.v4.0", - "title": "AIRS-CloudSat cloud mask and radar reflectivities collocation indexes V4.0 (AIRS_CPR_IND) at GES_DISC", - "catalog": "GES_DISC", - "state_date": "2006-06-15", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1236224151-GES_DISC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1236224151-GES_DISC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/AIRS_CPR_IND.v4.0", - "description": "Version 4.1 is the current version of the data set. Previous versions are no longer available and have been superseded by Version 4.1. This is AIRS-AMSU-CloudSat collocation indexes, in netCDF-4 format. These data map CloudSat profile indexes to the collocated AMSU field of views, and AIRS IR footprints, per AIRS 6-min granule time. Hence it can be considered as Level 1. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple \"A-train\" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, & CloudSat), classify each \"scene\" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time \"matchups\" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRS_CPR_IND", - "license": "not-provided" - }, - { - "id": "AIRS_CPR_MAT.v3.2", - "title": "AIRS-CloudSat cloud mask, radar reflectivities, and cloud classification matchups V3.2 (AIRS_CPR_MAT) at GES DISC", - "catalog": "GES_DISC", - "state_date": "2006-06-15", - "end_date": "2012-12-14", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1236224153-GES_DISC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1236224153-GES_DISC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/AIRS_CPR_MAT.v3.2", - "description": "This is AIRS-CloudSat collocated subset, in NetCDF-4 format. These data contain collocated: AIRS Level 1b radiances spectra, CloudSat radar reflectivities, and MODIS cloud mask. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple \"A-train\" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, CloudSat), classify each \"scene\" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time \"matchups\" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRS_CPR_MAT Parameters contained in the data files include the following: Variable Name|Description|Units CldFrcStdErr|Cloud Fraction|(None) CloudLayers| Number of hydrometeor layers| (count) CPR_Cloud_mask| CPR Cloud Mask| (None) DEM_elevation| Digital Elevation Map| (m) dust_flag|Dust Flag|(None) latAIRS|AIRS IR latitude|(deg) Latitude|CloudSat Latitude |(degrees) LayerBase| Height of Layer Base| (m) LayerTop| Height of layer top| (m) lonAIRS|AIRS IR longitude|(deg) Longitude|CloudSat Longitude| (degrees) MODIS_cloud_flag| MOD35_bit_2and3_cloud_flag| (None) Radar_Reflectivity| Radar Reflectivity Factor| (dBZe) radiances|Radiances|(milliWatts/m**2/cm**-1/steradian) Sigma-Zero| Sigma-Zero| (dB*100) spectral_clear_indicator|Spectral Clear Indicator|(None) Vertical_binsize|CloudSat vertical binsize| (m) End of parameter information", - "license": "not-provided" - }, - { - "id": "AIRXAMAP.v005", - "title": "AIRS/Aqua Granule map product V005 (AIRXAMAP) at GES DISC", - "catalog": "GES_DISC", - "state_date": "2002-05-21", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1233769004-GES_DISC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1233769004-GES_DISC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/AIRXAMAP.v005", - "description": "The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. An AIRS granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. The AIRS Granule Map Product consists of images of granule coverage in PDF and JPG format. The images are daily ones but updated every 6 minutes to capture any new available granule. Granules are assembled by ascending, descending, in north and south hemisphere, and the maps are in global cylindrical projection and satellite projection for better view.", - "license": "not-provided" - }, - { - "id": "AIRXBCAL.v005", - "title": "AIRS/Aqua L1B Calibration subset V005 (AIRXBCAL) at GES DISC", - "catalog": "GES_DISC", - "state_date": "2002-08-31", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1243477315-GES_DISC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1243477315-GES_DISC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/AIRXBCAL.v005", - "description": "The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. AIRS/Aqua Level-1B calibration subset including clear cases, special calibration sites, random nadir spots, and high clouds. The AIRS Visible/Near Infrared (VIS/NIR) level 1B data set contains AIRS visible and near-infrared calibrated and geolocated radiances in W/m^2/micron/steradian. This data set is generated from AIRS level 1A digital numbers (DN), including 4 channels in the 0.4 to 1.0 um region of the spectrum.", - "license": "not-provided" - }, { "id": "AK_AVHRR", "title": "Alaska AVHRR Twice-Monthly Composites", @@ -2027,6 +1949,19 @@ "description": "On the background of these requirements for sensor calibration, intercalibration and product validation, the subgroup on Calibration and Validation of the Committee on Earth Observing System (CEOS) formulated the following recommendation during the plenary session held in China at the end of 2004, with the goal of setting-up and operating an internet based system to provide sensor data, protocols and guidelines for these purposes: Background: Reference Datasets are required to support the understanding of climate change and quality assure operational services by Earth Observing satellites. The data from different sensors and the resulting synergistic data products require a high level of accuracy that can only be obtained through continuous traceable calibration and validation activities. Requirement: Initiate an activity to document a reference methodology to predict Top of Atmosphere (TOA) radiance for which currently flying and planned wide swath sensors can be intercompared, i.e. define a standard for traceability. Also create and maintain a fully accessible web page containing, on an instrument basis, links to all instrument characteristics needed for intercomparisons as specified above, ideally in a common format. In addition, create and maintain a database (e.g. SADE) of instrument data for specific vicarious calibration sites, including site characteristics, in a common format. Each agency is responsible for providing data for their instruments in this common format. Recommendation : The required activities described above should be supported for an implementation period of two years and a maintenance period over two subsequent years. The CEOS should encourage a member agency to accept the lead role in supporting this activity. CEOS should request all member agencies to support this activity by providing appropriate information and data in a timely manner. Pseudo-Invariant Calibration Sites (PICS): Algeria 3 is one of six CEOS reference Pseudo-Invariant Calibration Sites (PICS) that are CEOS Reference Test Sites. Besides the nominally good site characteristics (temporal stability, uniformity, homogeneity, etc.), these six PICS were selected by also taking into account their heritage and the large number of datasets from multiple instruments that already existed in the EO archives and the long history of characterization performed over these sites. The PICS have high reflectance and are usually made up of sand dunes with climatologically low aerosol loading and practically no vegetation. Consequently, these PICS can be used to evaluate the long-term stability of instrument and facilitate inter-comparison of multiple instruments.", "license": "not-provided" }, + { + "id": "CH-OG-1-GPS-10S.v0.0", + "title": "10 sec GPS ground tracking data", + "catalog": "SCIOPS", + "state_date": "2001-05-28", + "end_date": "", + "bbox": "-63.51, -45.69, 170.42, 78.87", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214586614-SCIOPS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214586614-SCIOPS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/CH-OG-1-GPS-10S.v0.0", + "description": "This data set comprises GPS ground data of a sample rate of 10 sec, generated by decoding and sampling GPS high rate ground data. This raw data passed no quality control. The data are given in the Rinex 2.1 format.", + "license": "not-provided" + }, { "id": "CIESIN_SEDAC_EPI_2008.v2008.00", "title": "2008 Environmental Performance Index (EPI)", @@ -2989,6 +2924,19 @@ "description": "The data received from IMS1, HySI which operates in 64 spectral bands in VNIR bands(400-900nm) with 500 meter spatial resolution and swath of 128 kms.", "license": "not-provided" }, + { + "id": "ISERV.v1", + "title": "International Space Station SERVIR Environmental Research and Visualization System V1", + "catalog": "USGS_EROS", + "state_date": "2013-03-27", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1379906336-USGS_EROS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1379906336-USGS_EROS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/USGS_EROS/collections/ISERV.v1", + "description": "Abstract: The ISS SERVIR Environmental Research and Visualization System (ISERV) acquired images of the Earth's surface from the International Space Station (ISS). The goal was to improve automatic image capturing and data transfer. ISERV's main component was the optical assembly which consisted of a 9.25 inch Schmidt-Cassegrain telescope, a focal reducer (field of view enlarger), a digital single lens reflex camera, and a high precision focusing mechanism. A motorized 2-axis pointing mount allowed pointing at targets approximately 23 degrees from nadir in both along- and across-track directions.", + "license": "not-provided" + }, { "id": "IXBMIGEO.v2", "title": "MISR Geometric Parameters subset for the INTEX-B region V002", @@ -3132,6 +3080,19 @@ "description": "Korean Antarctic survey was conducted in the continental margin (II region) of the northwestern Antarctic Peninsula. We took on lease Russian R/V \"Yuzhmorgeologiya\" (5500 ton, ice strengthed vessel) and 10 researchers participated in the cruise, including acquisition of multichannel seismic, gravity, and magnetometer as well as a detailed samplings (box cores, gravity cores, and grab samples). 1. Geophysical researches (Multichannel seismic and SBP surveys) 2. Paleoceanographic researches", "license": "not-provided" }, + { + "id": "KUKRI_He", + "title": "(U-Th)/He ages from the Kukri Hills of southern Victoria Land", + "catalog": "SCIOPS", + "state_date": "1970-01-01", + "end_date": "", + "bbox": "162.7, -77.7, 162.7, -77.7", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214587974-SCIOPS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214587974-SCIOPS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/KUKRI_He", + "description": "The data set consists of (U-Th)/He ages collected from three vertical profiles from the the Kukri Hills (north side of the Ferrar Glacier) of Southern Victoria Land. The data set provides information on the cooling history and hence the denduation history of the Transantarctic Mountains in this area. Analyses were all carried out at the (U-Th)/He lab of Ken Farley at the Californai Institute of Technology.", + "license": "not-provided" + }, { "id": "L1B_Wind_Products", "title": "Aeolus preliminary HLOS (horizontal line-of-sight) wind observations for Rayleigh and Mie receivers", @@ -3301,19 +3262,6 @@ "description": "The combined MODIS (Aqua/Terra) Cloud Properties Level 3 monthly, 1x1 degree grid product represents a new addition that is especially geared to facilitate climate scientists who deal with both models and observations. MCD06COSP_D3_MODIS represents the daily product\u2019s short-name. The \u201cCOSP\u201d acronym in its short-name stands for Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package. The L3 monthly product is derived by aggregating the daily-produced Aqua+Terra/MODIS D3 Cloud Properties product (MCD06COSP_D3_MODIS). Provided in netCDF4 format, it contains 23 aggregated science data sets (SDS/parameters).", "license": "not-provided" }, - { - "id": "MCD14DL_C5_NRT.v005", - "title": "MODIS/Aqua+Terra Thermal Anomalies/Fire locations 1km FIRMS V005 NRT", - "catalog": "LM_FIRMS", - "state_date": "2014-01-28", - "end_date": "", - "bbox": "-180, -80, 180, 80", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1219768065-LM_FIRMS.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1219768065-LM_FIRMS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/LM_FIRMS/collections/MCD14DL_C5_NRT.v005", - "description": "Near Real-Time (NRT) MODIS Thermal Anomalies / Fire locations processed by FIRMS (Fire Information for Resource Management System) - Land Atmosphere Near real time Capability for EOS (LANCE), using swath products (MOD14/MYD14) rather than the tiled MOD14A1 and MYD14A1 products. The thermal anomalies / active fire represent the center of a 1km pixel that is flagged by the MODIS MOD14/MYD14 Fire and Thermal Anomalies algorithm (Giglio 2003) as containing one or more fires within the pixel. This is the most basic fire product in which active fires and other thermal anomalies, such as volcanoes, are identified.MCD14DL are available in the following formats: TXT, SHP, KML, WMS. These data are also provided through the FIRMS Fire Email Alerts. Please note only the TXT and SHP files contain all the attributes.", - "license": "not-provided" - }, { "id": "MIANACP.v1", "title": "MISR Aerosol Climatology Product V001", @@ -3561,6 +3509,19 @@ "description": "The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate scenarios for the globe that are derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios known as Representative Concentration Pathways (RCPs). The CMIP5 GCM runs were developed in support of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). The NEX-GDDP dataset includes downscaled projections for RCP 4.5 and RCP 8.5 from the 21 models and scenarios for which daily scenarios were produced and distributed under CMIP5. Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100. The spatial resolution of the dataset is 0.25 degrees (~25 km x 25 km). The NEX-GDDP dataset is provided to assist the science community in conducting studies of climate change impacts at local to regional scales, and to enhance public understanding of possible future global climate patterns at the spatial scale of individual towns, cities, and watersheds. Each of the climate projections includes monthly averaged maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2005 (Retrospective Run) and from 2006 to 2099 (Prospective Run). ", "license": "not-provided" }, + { + "id": "NIPR_UAP_ELF_SYO", + "title": "1-100Hz ULF/ELF Electromagnetic Wave Observation at Syowa Station", + "catalog": "SCIOPS", + "state_date": "2000-01-01", + "end_date": "", + "bbox": "39.6, -69, 39.6, -69", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214590112-SCIOPS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214590112-SCIOPS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/NIPR_UAP_ELF_SYO", + "description": "1-100Hz ULF/ELF Electromagnetic Wave Observation at Syowa Station", + "license": "not-provided" + }, { "id": "NMMIEAI-L2-NRT.v2", "title": "OMPS-NPP L2 NM Aerosol Index swath orbital NRT", @@ -4458,6 +4419,19 @@ "description": "The \"Land Surface Temperature derived from NOAA-AVHRR data (LST_AVHRR)\" is a fixed grid map (in stereographic projection ) with a spatial resolution of 1.1 km. The total size covering Europe is 4100 samples by 4300 lines. Within 24 hours of acquiring data from the satellite, day-time and night-time LSTs are calculated. In general, the products utilise data from all six of the passes that the satellite makes over Europe in each 24 hour period. For the daily day-time LST maps, the compositing criterion for the three day-time passes is maximum NDVI value and for daily night-time LST maps, the criterion is the maximum night-time LST value of the three night-time passes. Weekly and monthly day-time or night-time LST composite products are also produced by averaging daily day-time or daily night-time LST values, respectively. The range of LST values is scaled between \u201339.5\u00b0C and +87\u00b0C with a radiometric resolution of 0.5\u00b0C. A value of \u201340\u00b0C is used for water. Clouds are masked out as bad values. For additional information, please see: https://wdc.dlr.de/sensors/avhrr/", "license": "not-provided" }, + { + "id": "blue_ice_core_DML2004_AS", + "title": "101.1 m long horizontal blue ice core collected from Scharffenbergbotnen, DML, Antarctica, in 2003/2004", + "catalog": "SCIOPS", + "state_date": "1970-01-01", + "end_date": "", + "bbox": "-180, -90, 180, -62.83", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214614210-SCIOPS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214614210-SCIOPS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/blue_ice_core_DML2004_AS", + "description": "Horizontal blue ice core collected from the surface of a blue ice area in Scharffenbergbotnen, Heimefrontfjella, DML. Samples were collected in austral summer 2003/2004 and transported to Finland for chemical analyses. The blue ice core is estimated to represent a 1000-year period of climate history 20 - 40 kyr B.P.. The results of the analyses will be available in 2005.", + "license": "not-provided" + }, { "id": "chesapeake_val_2013.v0", "title": "2013 Chesapeake Bay measurements", @@ -4484,6 +4458,19 @@ "description": "Indian Remote Sensing satellites (IRS) are a series of Earth Observation satellites, built, launched and maintained by Indian Space Research Organisation. The IRS series provides many remote sensing services to India and international ground stations. The satellite has two panchromatic cameras that were especially designed for in flight stereo viewing. However, this collection contains the monoscopic data.", "license": "not-provided" }, + { + "id": "envidat-lwf-34.v2019-03-06", + "title": "10-HS Pfynwald", + "catalog": "SCIOPS", + "state_date": "2019-01-01", + "end_date": "2019-01-01", + "bbox": "7.61211, 46.30279, 7.61211, 46.30279", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1647993129-SCIOPS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1647993129-SCIOPS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/envidat-lwf-34.v2019-03-06", + "description": "Continuous measurement of soil water content at 10 and 80 cm depth (3 replications) with 10-HS soil moisture probes (Decagon Incorporation, Pullman, WA, USA). ### Purpose: ### Monitoring of the soil water matrix potential ### Paper Citation: ### * Dobbertin, M.; Eilmann, B.; Bleuler, P.; Giuggiola, A.; Graf Pannatier, E.; Landolt, W.; Schleppi, P.; Rigling, A., 2010: Effect of irrigation on needle morphology, shoot and stem growth in a drought-exposed Pinus sylvestris forest. Tree Physiology, 30, 3: 346-360. [doi: 10.1093/treephys/tpp123](http://doi.org/10.1093/treephys/tpp123) ", + "license": "not-provided" + }, { "id": "gov.noaa.nodc:0000029", "title": "1990, 1991, 1992 and 1995 CRETM/LMER Zooplankton Data Sets (NCEI Accession 0000029)", @@ -4666,6 +4653,19 @@ "description": "2014 Lake Erie measurements.", "license": "not-provided" }, + { + "id": "latent-reserves-in-the-swiss-nfi.v1.0", + "title": "'Latent reserves' within the Swiss NFI", + "catalog": "SCIOPS", + "state_date": "2020-01-01", + "end_date": "2020-01-01", + "bbox": "5.95587, 45.81802, 10.49203, 47.80838", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1931110427-SCIOPS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1931110427-SCIOPS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/latent-reserves-in-the-swiss-nfi.v1.0", + "description": "The files refer to the data used in Portier et al. \"\u2018Latent reserves\u2019: a hidden treasure in National Forest Inventories\" (2020) *Journal of Ecology*. **'Latent reserves'** are defined as plots in National Forest Inventories (NFI) that have been free of human influence for >40 to >70 years. They can be used to investigate and acquire a deeper understanding of attributes and processes of near-natural forests using existing long-term data. To determine which NFI sample plots could be considered \u2018latent reserves\u2019, criteria were defined based on the information available in the Swiss NFI database: * Shrub forests were excluded. * Plots must have been free of any kind of management, including salvage logging or sanitary cuts, for a minimum amount of time. Thresholds of 40, 50, 60 and 70 years without intervention were tested. * To ensure that species composition was not influenced by past management, plots where potential vegetation was classified as deciduous by Ellenberg & Kl\u00f6tzli (1972) had to have an observed proportion of deciduous trees matching the theoretical proportion expected in a natural deciduous forest, as defined by Kienast, Brzeziecki, & Wildi (1994). * Plots had to originate from natural regeneration. * Intensive livestock grazing must never have occurred on the plots. The tables stored here were derived from the first, second and third campaigns of the Swiss NFI. The raw data from the Swiss NFI can be provided free of charge within the scope of a contractual agreement (http://www.lfi.ch/dienstleist/daten-en.php). **** The files 'Data figure 2' to 'Data figure 8' are publicly available and contain the data used to produce the figures published in the paper. The files 'Plot-level data for characterisation of 'latent reserves' and 'Tree-level data for characterisation of 'latent reserves' contain all the data required to reproduce the section of the article concerning the characterisation of 'latent reserves' and the comparison to managed forests. The file 'Data for mortality analyses' contains the data required to reproduce the section of the article concerning tree mortality in 'latent reserves'. The access to these three files is restricted as they contain some raw data from the Swiss NFI, submitted to the Swiss law and only accessible upon contractual agreement. ", + "license": "not-provided" + }, { "id": "law_dome_annual_msa.v1", "title": "150 year MSA sea ice proxy record from Law Dome, Antarctica", diff --git a/nasa_cmr_catalog.tsv b/nasa_cmr_catalog.tsv index 5fd9e56..b8988e0 100644 --- a/nasa_cmr_catalog.tsv +++ b/nasa_cmr_catalog.tsv @@ -1,6 +1,10 @@ id title catalog state_date end_date bbox url description license 0f4324af-fa0a-4aaf-9b97-89a4f3325ce1 DESIS - Hyperspectral Images - Global FEDEO 2018-08-30 -180, -52, 180, 52 https://cmr.earthdata.nasa.gov/search/concepts/C2207458058-FEDEO.json The hyperspectral instrument DESIS (DLR Earth Sensing Imaging Spectrometer) is one of four possible payloads of MUSES (Multi-User System for Earth Sensing), which is mounted on the International Space Station (ISS). DLR developed and delivered a Visual/Near-Infrared Imaging Spectrometer to Teledyne Brown Engineering, which was responsible for integrating the instrument. Teledyne Brown designed and constructed, integrated and tested the platform before delivered to NASA. Teledyne Brown collaborates with DLR in several areas, including basic and applied research for use of data. DESIS is operated in the wavelength range from visible through the near infrared and enables precise data acquisition from Earth's surface for applications including fire-detection, change detection, maritime domain awareness, and atmospheric research. Three product types can be ordered, which are Level 1B (systematic and radiometric corrected), Level 1C (geometrically corrected) and Level 2A (atmospherically corrected). The spatial resolution is about 30m on ground. DESIS is sensitive between 400nm and 1000nm with a spectral resolution of about 3.3nm. DESIS data are delivered in tiles of about 30x30km. For more information concerning DESIS the reader is referred to https://www.dlr.de/eoc/en/desktopdefault.aspx/tabid-13614/ not-provided 11c5f6df1abc41968d0b28fe36393c9d ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from MERIS (ALAMO algorithm), Version 2.2 FEDEO 2008-01-01 2008-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2548143004-FEDEO.json The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. This dataset comprises the Level 3 aerosol daily and monthly gridded products from MERIS for 2008, using the ALAMO algorithm, version 2.2. The data have been provided by Hygeos.For further details about these data products please see the linked documentation. not-provided +12-hourly_interpolated_surface_position_from_buoys 12-Hourly Interpolated Surface Position from Buoys SCIOPS 1979-01-01 2009-12-01 -180, 60, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214600619-SCIOPS.json This data set contains Arctic Ocean daily buoy positions interpolated to hours 0Z and 12Z. not-provided +12-hourly_interpolated_surface_velocity_from_buoys 12-Hourly Interpolated Surface Velocity from Buoys SCIOPS 1979-01-01 2009-12-02 -180, 74, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214600621-SCIOPS.json This data set contains 12-hourly interpolated surface velocity data from buoys. Point grid: Latitude 74N to 90N - 4 degree increment Longitude 0E to 320E - 20 and 40 degree increment. not-provided +12_hourly_interpolated_surface_air_pressure_from_buoys 12 Hourly Interpolated Surface Air Pressure from Buoys SCIOPS 1979-01-01 2007-11-30 -180, 70, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214600618-SCIOPS.json Optimally interpolated atmospheric surface pressure over the Arctic Ocean Basin. Temporal format - twice daily (0Z and 12Z) Spatial format - 2 degree latitude x 10 degree longitude - latitude: 70 N - 90 N - longitude: 0 E - 350 E not-provided +14c_of_soil_co2_from_ipy_itex_cross_site_comparison 14C of soil CO2 from IPY ITEX Cross Site Comparison SCIOPS 2008-01-16 2008-01-21 -157.4, -36.9, 147.29, 71.3 https://cmr.earthdata.nasa.gov/search/concepts/C1214602443-SCIOPS.json Study sites: Toolik Lake Field Station Alaska, USA 68.63 N, 149.57 W; Atqasuk, Alaska USA 70.45 N, 157.40 W; Barrow, Alaska, USA 71.30 N, 156.67 W; Latnjajaure, Sweden 68.35 N, 18.50 E; Falls Creek, Australia: Site 2-unburned 36.90 S 147.29 E; Site 3-burned 36.89 S 147.28 E. Additional sites will be added summer 2008, but the exact sites are not finalized. Purpose: Collect soil CO2 for analysis of radiocarbon to evaluate the age of the carbon respired in controls and warmed plots from across the ITEX network. Treatments: control and ITEX OTC warming experiment (1994-2007). Design: 5 replicates of each treatment at dry site and moist site. Sampling frequency: Once per peak season. not-provided 200708_CEAMARC_CASO_TRACE_ELEMENT_SAMPLES.v1 2007-08 CEAMARC-CASO VOYAGE TRACE ELEMENT SAMPLING AROUND AN ICEBERG AU_AADC 2008-01-01 2008-03-20 139.01488, -67.07104, 150.06479, -42.88246 https://cmr.earthdata.nasa.gov/search/concepts/C1214305618-AU_AADC.json We collected surface seawater samples using trace clean 1L Nalgene bottles on the end of a long bamboo pole. We will analyse these samples for trace elements. Iron is the element of highest interest to our group. We will determine dissolved iron and total dissolvable iron concentrations. Samples collected from 7 sites: Sites 1, 2, 3, 4 were a transect perpendicular to the edge of the iceberg to try and determine if there is a iron concentration gradient relative to the iceberg. Sites 4, 5, 6 were along the edge of the iceberg to determine if there is any spatial variability along the iceberg edge. Site 7 was away from the iceberg to determine what the iron concentration is in the surrounding waters not influenced by the iceberg. not-provided 2019 Mali CropType Training Data.v1 2019 Mali CropType Training Data MLHUB 2020-01-01 2023-01-01 -6.9444015, 12.8185552, -6.5890481, 13.3734391 https://cmr.earthdata.nasa.gov/search/concepts/C2781412344-MLHUB.json This dataset produced by the NASA Harvest team includes crop types labels from ground referencing matched with time-series of Sentinel-2 imagery during the growing season. Ground reference data are collected using an ODK app. Crop types include Maize, Millet, Rice and Sorghum. Labels are vectorized over the Sentinel-2 grid, and provided as raster files. Funding for this dataset is provided by Lutheran World Relief, Bill & Melinda Gates Foundation, and University of Maryland NASA Harvest program. not-provided 39480 1988 Mosaic of Aerial Photography of the Salt River Bay National Historical Park and Ecological Preserve NOAA_NCEI 1988-11-24 1988-11-24 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2102656753-NOAA_NCEI.json Aerial photographs taken by NOAA's National Geodetic Survey during 1988 were mosaicked and orthorectified by the Biogeography Branch. The resulting image was used to digitize benthic, land cover and mangrove habitat maps of the Salt River Bay National Historic Park and Ecological Preserve (National Park Service), on St. Croix, in the U.S. Virgin Islands.The mosaic is centered on the National Park Service Site, located on the north central coast of St. Croix, and extends beyond the park boundaries approximately 0.5 - 4.0 km. not-provided @@ -43,10 +47,6 @@ ACEPOL_AircraftRemoteSensing_AirHARP_Data.v1 ACEPOL Airborne Hyper Angular Rainb ACEPOL_AircraftRemoteSensing_AirSPEX_Data.v1 ACEPOL Airborne Spectrometer for Planetary Exploration (AirSPEX) Remotely Sensed Data Version 1 LARC_ASDC 2017-10-19 2017-11-09 -130, 25, -100, 45 https://cmr.earthdata.nasa.gov/search/concepts/C1758588281-LARC_ASDC.json ACEPOL_AircraftRemoteSensing_AirSPEX_Data are remotely sensed measurements collected by the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA’s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which make them valuable resources for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions. not-provided ACEPOL_AircraftRemoteSensing_CPL_Data.v1 ACEPOL Cloud Physics Lidar (CPL) Remotely Sensed Data Version 1 LARC_ASDC 2017-10-19 2017-11-09 -130, 25, -100, 45 https://cmr.earthdata.nasa.gov/search/concepts/C1758588308-LARC_ASDC.json ACEPOL Cloud Physics Lidar (CPL) Remotely Sensed Data (ACEPOL_AircraftRemoteSensing_CPL_Data) are remotely sensed measurements collected by the Cloud Physics Lidar (CPL) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA’s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which make them valuable resources for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions. not-provided ACIDD.v0 Across the Channel Investigating Diel Dynamics project OB_DAAC 2017-12-16 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360091-OB_DAAC.json The ACIDD (Across the Channel Investigating Diel Dynamics) project, in the Santa Barbara Channel, was initially designed to characterize daily variations in phytoplankton populations, but with the Thomas Fire in the Santa Barbara Hills December 2017, this project evolved into a study to characterize the effects of smoke and ash on the mixed layer in the Santa Barbara Channel. not-provided -ACOS_L2S.v7.3 ACOS GOSAT/TANSO-FTS Level 2 Full Physics Standard Product V7.3 (ACOS_L2S) at GES DISC GES_DISC 2009-04-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1339230297-GES_DISC.json "Version 7.3 is the current version of the data set. Version 3.5 is no longer available and has been superseded by Version 7.3. This data set is currently provided by the OCO (Orbiting Carbon Observatory) Project. In expectation of the OCO-2 launch, the algorithm was developed by the Atmospheric CO2 Observations from Space (ACOS) Task as a preparatory project, using GOSAT TANSO-FTS spectra. After the OCO-2 launch, ""ACOS"" data are still produced and improved, using approaches applied to the OCO-2 spectra. The ""ACOS"" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances, and algorithm build version 7.3. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the ""ACOS"" Level 2 production process. Even though the GES DISC is not publicly distributing Level 1B ACOS products, it should be known that changes in this version are affecting both Level 1B and Level 2 data. An important enhancement in Level1B will address the degradation in the number of quality-passed soundings. Elimination of many systematic biases, and better agreement with TCCON (Total Carbon Column Observing Network), is expected in Level 2 retrievals. The key changes to the L2 algorithm include scaling the O2-A band spectroscopy (reducing XCO2 bias by 4 or 5 ppm); using interpolation with the instrument lineshape [ ILS ] (reducing XCO2 bias by 1.5 ppm); and fitting a zero level offset to the A-band. Users have to also carefully familiarize themselves with the disclaimer in the new documentation. An important element to note are the updates on data screening. Although a Master Quality Flag is provided in the data product, further analysis of a larger set of data has allowed the science team to provide an updated set of screening criteria. These are listed in the data user's guide, and are recommended instead of the Master Quality Flag. Lastly, users should continue to carefully observe and weigh information from three important flags: ""warn_level"" - Provides a value that summarizes each sounding's acceptability to a larger set of quality filters. A high warn level predicts that the sounding would fail most data filters applied to it. A low warn level suggests that the sounding would pass most quality filters that might be applied. ""sounding_qual_flag"" - quality of input data provided to the retrieval processing ""outcome_flag"" - retrieval quality based upon certain internal thresholds (not thoroughly evaluated) ""master_quality_flag"" - four possible values: ""Good"", ""Caution"" and ""Bad"", and ""Failed"", as determined from other flags in the L2 productThe short name for this data type is ACOS_L2S." not-provided -ACOS_L2S.v9r ACOS GOSAT/TANSO-FTS Level 2 Full Physics Standard Product V9r (ACOS_L2S) at GES DISC GES_DISC 2009-04-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633158704-GES_DISC.json "Version 9r is the current version of the data set. Older versions will no longer be available and are superseded by Version 9r. This data set is currently provided by the OCO (Orbiting Carbon Observatory) Project. In expectation of the OCO-2 launch, the algorithm was developed by the Atmospheric CO2 Observations from Space (ACOS) Task as a preparatory project, using GOSAT TANSO-FTS spectra. After the OCO-2 launch, ""ACOS"" data are still produced and improved, using approaches applied to the OCO-2 spectra. The ""ACOS"" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances, and algorithm build version 7.3. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the ""ACOS"" Level 2 production process. Even though the GES DISC is not publicly distributing Level 1B ACOS products, it should be known that changes in this version are affecting both Level 1B and Level 2 data. An important enhancement in Level1B will address the degradation in the number of quality-passed soundings. Elimination of many systematic biases, and better agreement with TCCON (Total Carbon Column Observing Network), is expected in Level 2 retrievals. The key changes to the L2 algorithm include scaling the O2-A band spectroscopy (reducing XCO2 bias by 4 or 5 ppm); using interpolation with the instrument lineshape [ ILS ] (reducing XCO2 bias by 1.5 ppm); and fitting a zero level offset to the A-band. Users have to also carefully familiarize themselves with the disclaimer in the new documentation. An important element to note are the updates on data screening. Although a Master Quality Flag is provided in the data product, further analysis of a larger set of data has allowed the science team to provide an updated set of screening criteria. These are listed in the data user's guide, and are recommended instead of the Master Quality Flag. Lastly, users should continue to carefully observe and weigh information from three important flags: ""sounding_qual_flag"" - quality of input data provided to the retrieval processing ""outcome_flag"" - retrieval quality based upon certain internal thresholds (not thoroughly evaluated) " not-provided -ACOS_L2_Lite_FP.v7.3 ACOS GOSAT/TANSO-FTS Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files V7.3 (ACOS_L2_Lite_FP) at GES DISC GES_DISC 2009-04-21 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1339230298-GES_DISC.json "The ACOS Lite files contain bias-corrected XCO2 along with other select fields aggregated as daily files. Orbital granules of the ACOS Level 2 standard product (ACOS_L2S) are used as input. The ""ACOS"" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the ""ACOS"" Level 2 production process." not-provided -ACOS_L2_Lite_FP.v9r ACOS GOSAT/TANSO-FTS Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files V9r (ACOS_L2_Lite_FP) at GES DISC GES_DISC 2009-04-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1720416694-GES_DISC.json "Version 9r is the current version of the data set. Older versions will no longer be available and are superseded by Version 9r. The ACOS Lite files contain bias-corrected XCO2 along with other select fields aggregated as daily files. Orbital granules of the ACOS Level 2 standard product (ACOS_L2S) are used as input. The ""ACOS"" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the ""ACOS"" Level 2 production process." not-provided ACR3L2DM.v1 ACRIM III Level 2 Daily Mean Data V001 LARC 2000-04-05 2013-11-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179031504-LARC.json ACR3L2DM_1 is the Active Cavity Radiometer Irradiance Monitor (ACRIM) III Level 2 Daily Mean Data version 1 product consists of Level 2 total solar irradiance in the form of daily means gathered by the ACRIM III instrument on the ACRIMSAT satellite. The daily means are constructed from the shutter cycle results for each day. not-provided ACR3L2SC.v1 ACRIM III Level 2 Shutter Cycle Data V001 LARC 2000-04-05 2013-11-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C61787524-LARC.json ACR3L2SC_1 is the Active Cavity Radiometer Irradiance Monitor (ACRIM) III Level 2 Shutter Cycle Data version 1 product contains Level 2 total solar irradiance in the form of shutter cycles gathered by the ACRIM instrument on the ACRIMSAT satellite. not-provided ADAM.Surface.Reflectance.Database ADAM Surface Reflectance Database v4.0 ESA 2005-01-01 2005-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1965336812-ESA.json ADAM enables generating typical monthly variations of the global Earth surface reflectance at 0.1° spatial resolution (Plate Carree projection) and over the spectral range 240-4000nm. The ADAM product is made of gridded monthly mean climatologies over land and ocean surfaces, and of a companion API toolkit that enables the calculation of hyperspectral (at 1 nm resolution over the whole 240-4000 nm spectral range) and multidirectional reflectances (i.e. in any illumination/viewing geometry) depending on user choices. The ADAM climatologies that feed the ADAM calculation tools are: For ocean: monthly chlorophyll concentration derived from SeaWiFS-OrbView-2 (1999-2009); it is used to compute the water column reflectance (which shows large spectral variations in the visible, but is insignificant in the near and mid infrared). monthly wind speed derived from SeaWinds-QuikSCAT-(1999-2009); it is used to calculate the ocean glint reflectance. For land: monthly normalized surface reflectances in the 7 MODIS narrow spectral bands derived from FondsdeSol processing chain of MOD09A1 products (derived from Aqua and Terra observations), on which relies the modelling of the hyperspectral/multidirectional surface (soil/vegetation/snow) reflectance. uncertainty variance-covariance matrix for the 7 spectral bands associated to the normalized surface reflectance. For sea-ice: Sea ice pixels (masked in the original MOD09A1 products) have been accounted for by a gap-filling approach relying on the spatial-temporal distribution of sea ice coverage provided by the CryoClim climatology for year 2005. not-provided @@ -71,7 +71,6 @@ AFOLVIS1A.v1 AfriSAR LVIS L1A Geotagged Images V001 NSIDC_ECS 2016-02-20 2016-03 AG100.v003 ASTER Global Emissivity Dataset, 100 meter, HDF5 V003 LPDAAC_ECS 2000-01-01 2008-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000362-LPDAAC_ECS.json Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) land surface temperature and emissivity (LST&E) data products are generated using the ASTER Temperature Emissivity Separation (TES) algorithm with a Water Vapor Scaling (WVS) atmospheric correction method using Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD07) (https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html) atmospheric profiles and the MODerate spectral resolution TRANsmittance (MODTRAN 5.2 radiative transfer model). This dataset is computed from all clear-sky pixels of ASTER scenes acquired from 2000 through 2008. AG100 data are available globally at spatial resolution of 100 meters. The National Aeronautics and Space Administration’s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product. not-provided AG1km.v003 ASTER Global Emissivity Dataset, 1 kilometer, HDF5 V003 LPDAAC_ECS 2000-01-01 2008-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000380-LPDAAC_ECS.json Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) land surface temperature and emissivity (LST&E) data products are generated using the ASTER Temperature Emissivity Separation (TES) algorithm with a Water Vapor Scaling (WVS) atmospheric correction method using Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD07) (https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html) atmospheric profiles and the MODerate Spectral resolution TRANsmittance (MODTRAN) 5.2 radiative transfer model. This dataset is computed from all clear-sky pixels of ASTER scenes acquired from 2000 through 2008. AG1KM data are available globally at spatial resolution of 1 kilometer. The National Aeronautics and Space Administration’s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product. not-provided AG5KMMOH.v041 ASTER Global Emissivity Dataset, Monthly, 0.05 deg, HDF5 V041 LPDAAC_ECS 2000-03-01 2015-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1344831606-LPDAAC_ECS.json Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) is a collection of monthly files (see known issues for gaps) for each year of global emissivity. The ASTER GED data products are generated for 2000 through 2015 using the ASTER Temperature Emissivity Separation (TES) algorithm atmospheric correction method. This algorithm method uses Moderate Resolution Imaging Spectroradiometer (MODIS) Atmospheric Profiles product (MOD07) (https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html) and the MODerate spectral resolution TRANsmittance (MODTRAN) 5.2 radiative transfer model along with the snow cover data from the standard monthly MODIS/Terra snow cover monthly global 0.05 degree product (MOD10CM) (https://doi.org/10.5067/MODIS/MOD10CM.006), and vegetation information from the MODIS monthly gridded NDVI product (MOD13C2) (https://doi.org/10.5067/MODIS/MOD13C2.006). ASTER GED Monthly V041 data products are offered in Hierarchical Data Format 5 (HDF5). The National Aeronautics and Space Administration’s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product. not-provided -AIRABRAD.v005 AIRS/Aqua L1B AMSU (A1/A2) geolocated and calibrated brightness temperatures V005 (AIRABRAD) at GES DISC GES_DISC 2002-05-21 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243477366-GES_DISC.json "The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. The AMSU-A instrument is co-aligned with AIRS so that successive blocks of 3 x 3 AIRS footprints are contained within one AMSU-A footprint. AMSU-A is primarily a temperature sounder that provides atmospheric information in the presence of clouds, which can be used to correct the AIRS infrared measurements for the effects of clouds. This is possible because non-precipitating clouds are for the most part transparent to microwave radiation, in contrast to visible and infrared radiation which are strongly scattered and absorbed by clouds. AMSU-A1 has 13 channels from 50 - 90 GHz and AMSU-A2 has 2 channels from 23 - 32 GHz. The AIRABRAD_005 products are stored in files (often referred to as ""granules"") that contain 6 minutes of data, 30 footprints across track by 45 lines along track." not-provided AIRSAR_INT_JPG.v1 AIRSAR_ALONGTRACK_INTERFEROMETRY_JPG ASF 1998-10-25 2004-03-05 -172.880269, -27.388834, -49.704356, 69.25925 https://cmr.earthdata.nasa.gov/search/concepts/C1213921626-ASF.json AIRSAR along-track interferometric browse product JPG not-provided AIRSAR_POL_3FP.v1 AIRSAR_POLSAR_3_FREQ_POLARIMETRY ASF 1990-03-02 2004-03-21 -172.880269, -27.388834, -49.704356, 69.25925 https://cmr.earthdata.nasa.gov/search/concepts/C1213921661-ASF.json AIRSAR three-frequency polarimetric frame product not-provided AIRSAR_POL_SYN_3FP.v1 AIRSAR_POLSAR_SYNOPTIC_3_FREQ_POLARIMETRY ASF 1990-03-29 1991-07-16 -172.880269, -27.388834, -49.704356, 69.25925 https://cmr.earthdata.nasa.gov/search/concepts/C1213928843-ASF.json AIRSAR three-frequency polarimetric synoptic product not-provided @@ -82,11 +81,6 @@ AIRSAR_TOP_DEM_L.v1 AIRSAR_TOPSAR_DEM_L ASF 1993-06-08 2004-12-04 -172.880269, - AIRSAR_TOP_DEM_P.v1 AIRSAR_TOPSAR_DEM_P ASF 1993-06-08 2004-12-04 -172.880269, -27.388834, -49.704356, 69.25925 https://cmr.earthdata.nasa.gov/search/concepts/C1213926777-ASF.json AIRSAR topographic SAR digital elevation model PTIF product not-provided AIRSAR_TOP_L-STOKES.v1 AIRSAR_TOPSAR_L-BAND_STOKES ASF 1993-06-08 2004-12-04 -172.880269, -27.388834, -49.704356, 69.25925 https://cmr.earthdata.nasa.gov/search/concepts/C1213927939-ASF.json AIRSAR topographic SAR digital elevation model L_Stokes product not-provided AIRSAR_TOP_P-STOKES.v1 AIRSAR_TOPSAR_P-BAND_STOKES ASF 1993-06-08 2004-12-04 -172.880269, -27.388834, -49.704356, 69.25925 https://cmr.earthdata.nasa.gov/search/concepts/C1213928209-ASF.json AIRSAR topographic SAR digital elevation model P_Stokes product not-provided -AIRSM_CPR_MAT.v3.2 AIRS-AMSU variables-CloudSat cloud mask, radar reflectivities, and cloud classification matchups V3.2 (AIRSM_CPR_MAT) at GES DISC GES_DISC 2006-06-15 2012-12-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236224182-GES_DISC.json "This is AIRS-CloudSat collocated subset, in NetCDF 4 format. These data contain collocated: AIRS/AMSU retrievals at AMSU footprints, CloudSat radar reflectivities, and MODIS cloud mask. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple ""A-train"" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, CloudSat), classify each ""scene"" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time ""matchups"" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRSM_CPR_MAT Parameters contained in the data files include the following: Variable Name|Description|Units CH4_total_column|Retrieved total column CH4| (molecules/cm2) CloudFraction|CloudSat/CALIPSO Cloud Fraction| (None) CloudLayers| Number of hydrometeor layers| (count) clrolr|Clear-sky Outgoing Longwave Radiation|(Watts/m**2) CO_total_column|Retrieved total column CO| (molecules/cm2) CPR_Cloud_mask| CPR Cloud Mask |(None) Data_quality| Data Quality |(None) H2OMMRSat|Water vapor saturation mass mixing ratio|(gm/kg) H2OMMRStd|Water Vapor Mass Mixing Ratio |(gm/kg dry air) MODIS_Cloud_Fraction| MODIS 250m Cloud Fraction| (None) MODIS_scene_var |MODIS scene variability| (None) nSurfStd|1-based index of the first valid level|(None) O3VMRStd|Ozone Volume Mixing Ratio|(vmr) olr|All-sky Outgoing Longwave Radiation|(Watts/m**2) Radar_Reflectivity| Radar Reflectivity Factor| (dBZe) Sigma-Zero| Sigma-Zero| (dB*100) TAirMWOnlyStd|Atmospheric Temperature retrieved using only MW|(K) TCldTopStd|Cloud top temperature|(K) totH2OStd|Total precipitable water vapor| (kg/m**2) totO3Std|Total ozone burden| (Dobson) TSurfAir|Atmospheric Temperature at Surface|(K) TSurfStd|Surface skin temperature|(K) End of parameter information" not-provided -AIRS_CPR_IND.v4.0 AIRS-CloudSat cloud mask and radar reflectivities collocation indexes V4.0 (AIRS_CPR_IND) at GES_DISC GES_DISC 2006-06-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236224151-GES_DISC.json "Version 4.1 is the current version of the data set. Previous versions are no longer available and have been superseded by Version 4.1. This is AIRS-AMSU-CloudSat collocation indexes, in netCDF-4 format. These data map CloudSat profile indexes to the collocated AMSU field of views, and AIRS IR footprints, per AIRS 6-min granule time. Hence it can be considered as Level 1. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple ""A-train"" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, & CloudSat), classify each ""scene"" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time ""matchups"" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRS_CPR_IND" not-provided -AIRS_CPR_MAT.v3.2 AIRS-CloudSat cloud mask, radar reflectivities, and cloud classification matchups V3.2 (AIRS_CPR_MAT) at GES DISC GES_DISC 2006-06-15 2012-12-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236224153-GES_DISC.json "This is AIRS-CloudSat collocated subset, in NetCDF-4 format. These data contain collocated: AIRS Level 1b radiances spectra, CloudSat radar reflectivities, and MODIS cloud mask. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple ""A-train"" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, CloudSat), classify each ""scene"" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time ""matchups"" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRS_CPR_MAT Parameters contained in the data files include the following: Variable Name|Description|Units CldFrcStdErr|Cloud Fraction|(None) CloudLayers| Number of hydrometeor layers| (count) CPR_Cloud_mask| CPR Cloud Mask| (None) DEM_elevation| Digital Elevation Map| (m) dust_flag|Dust Flag|(None) latAIRS|AIRS IR latitude|(deg) Latitude|CloudSat Latitude |(degrees) LayerBase| Height of Layer Base| (m) LayerTop| Height of layer top| (m) lonAIRS|AIRS IR longitude|(deg) Longitude|CloudSat Longitude| (degrees) MODIS_cloud_flag| MOD35_bit_2and3_cloud_flag| (None) Radar_Reflectivity| Radar Reflectivity Factor| (dBZe) radiances|Radiances|(milliWatts/m**2/cm**-1/steradian) Sigma-Zero| Sigma-Zero| (dB*100) spectral_clear_indicator|Spectral Clear Indicator|(None) Vertical_binsize|CloudSat vertical binsize| (m) End of parameter information" not-provided -AIRXAMAP.v005 AIRS/Aqua Granule map product V005 (AIRXAMAP) at GES DISC GES_DISC 2002-05-21 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1233769004-GES_DISC.json The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. An AIRS granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. The AIRS Granule Map Product consists of images of granule coverage in PDF and JPG format. The images are daily ones but updated every 6 minutes to capture any new available granule. Granules are assembled by ascending, descending, in north and south hemisphere, and the maps are in global cylindrical projection and satellite projection for better view. not-provided -AIRXBCAL.v005 AIRS/Aqua L1B Calibration subset V005 (AIRXBCAL) at GES DISC GES_DISC 2002-08-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243477315-GES_DISC.json The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. AIRS/Aqua Level-1B calibration subset including clear cases, special calibration sites, random nadir spots, and high clouds. The AIRS Visible/Near Infrared (VIS/NIR) level 1B data set contains AIRS visible and near-infrared calibrated and geolocated radiances in W/m^2/micron/steradian. This data set is generated from AIRS level 1A digital numbers (DN), including 4 channels in the 0.4 to 1.0 um region of the spectrum. not-provided AK_AVHRR Alaska AVHRR Twice-Monthly Composites USGS_LTA 1990-06-16 -179, 51, -116, 70 https://cmr.earthdata.nasa.gov/search/concepts/C1220565954-USGS_LTA.json The goal of the Alaska Advanced Very High Resolution Radiometer (AVHRR) project is to compile a time series data set of calibrated, georegistered daily observations and twice-monthly maximum normalized difference vegetation index (NDVI) composites for Alaska's annual growing season (April-October). This data set has applications for environmental monitoring and for assessing impacts of global climate change. An Alaska AVHRR data set is comprised of twice-monthly maximum NDVI composites of daily satellite observations. The NDVI composites contain 10 bands of information, including AVHRR channels 1-5, maximum NDVI, satellite zenith, solar zenith, and relative azimuth. The daily observations, bands 1-9, have been calibrated to reflectance, scaled to byte data, and geometrically registered to the Albers Equal-Area Conic map projection. The 10th band is a pointer to identify the date and scene ID of the source daily observation (scene) for each pixel. The compositing process required each daily overpass to be registered to a common map projection to ensure that from day to day each 1-km pixel represented the exact same ground location. The Albers Equal-Area Conic map projection provides for equal area representation, which enables easy measurement of area throughout the data. Each daily observation for the growing season was registered to a base image using image-to-image correlation. The NDVI data are calculated from the calibrated, geometrically registered daily observations. The NDVI value is the difference between near-infrared (AVHRR Channel 2) and visible (AVHRR Channel 1) reflectance values divided by total measured reflectance. A maximum NDVI compositing process was used on the daily observations. The NDVI is examined pixel by pixel for each observation during the compositing period to determine and retain the maximum value. Often when displaying data covering large areas, such as AVHRR data, it is beneficial to include an overlay of either familiar linework for reflectance or polygon data sets to derive statistical summaries of regions. All of the linework images represent lines in raster format as 1-km cells and the strata are represented as polygons registered to the AVHRR data. The linework and polygon data sets include international boundaries, Alaskan roads with the Trans-Alaska Pipeline, and a raster polygon mask of the State. not-provided ALOS Alos African Coverage ESA archive ESA 2006-07-09 2009-05-12 -26, -37, 53, 37 https://cmr.earthdata.nasa.gov/search/concepts/C1965336815-ESA.json ALOS Africa is a dataset of the best available (cloud minimal, below 10%) African coverage acquired by AVNIR-2 in OBS mode and PRISM in OB1 mode (all Backward, Nadir and Forward views, in separated products), two different collections one for each instrument. The processing level for both AVNIR-2 and PRISM products is L1B. not-provided ALOS.AVNIR-2.L1C ALOS AVNIR-2 L1C ESA 2006-04-28 2011-04-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2119689548-ESA.json This collection is providing access to the ALOS-1 AVNIR-2 (Advanced Visible and Near Infrared Radiometer type 2) L1C data acquired by ESA stations in the ADEN zone plus some worldwide data requested by European scientists. The ADEN zone (https://earth.esa.int/eogateway/documents/20142/37627/ALOS-ADEN-Zone.pdf) was the area belonging to the European Data node and covered both the European and the African continents, large part of the Greenland and the Middle East. The full mission is covered, obviously with gaps outside to the ADEN zone: • Time windows: from 2006-04-28 to 2011-04-20 • Orbits: from 1375 to 27898 • Path (corresponds to JAXA track number): from 1 to 670 • Row (corresponds to JAXA scene centre frame number): from 370 to 5230 One single Level 1C product types is offered for the OBS instrument mode: AV2_OBS_1C. not-provided @@ -155,6 +149,7 @@ CDDIS_SLR_products_ITRF2020_REPRO2020.v1 CDDIS SLR products ITRF2020 Station Pos CDDIS_VLBI_data_aux.v1 CDDIS VLBI Auxilliary Files CDDIS 2005-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2404928689-CDDIS.json Very Long Baseline Interferometry (VLBI) auxiliary ASCII files provided by the International VLBI Service for Geodesy and Astrometry (IVS) include schedules, notes, and session log files. not-provided CEAMARC_CASO_200708030_EVENT_BATHYMETRY_PLOTS.v1 2007-08 V3 CEAMARC-CASO Bathymetry Plots Over Time During Events AU_AADC 2007-12-17 2008-01-26 139.01488, -67.07104, 150.06479, -42.88246 https://cmr.earthdata.nasa.gov/search/concepts/C1214308504-AU_AADC.json A routine was developed in R ('bathy_plots.R') to plot bathymetry data over time during individual CEAMARC events. This is so we can analyse benthic data in relation to habitat, ie. did we trawl over a slope or was the sea floor relatively flat. Note that the depth range in the plots is autoscaled to the data, so a small range in depths appears as a scatetring of points. As long as you look at the depth scale though interpretation will be ok. The R files need a file of bathymetry data in '200708V3_one_minute.csv' which is a file containing a data export from the underway PostgreSQL ship database and 'events.csv' which is a stripped down version of the events export from the ship board events database export. If you wish to run the code again you may need to change the pathnames in the R script to relevant locations. If you have opened the csv files in excel at any stage and the R script gets an error you may need to format the date/time columns as yyyy-mm-dd hh;mm:ss, save and close the file as csv without opening it again and then run the R script. However, all output files are here for every CEAMARC event. Filenames contain a reference to CEAMARC event id. Files are in eps format and can be viewed using Ghostview which is available as a free download on the internet. not-provided CEOS_CalVal_Test_Sites-Algeria3 CEOS Cal Val Test Site - Algeria 3 - Pseudo-Invariant Calibration Site (PICS) USGS_LTA 1972-08-11 5.22, 29.09, 10.01, 31.36 https://cmr.earthdata.nasa.gov/search/concepts/C1220567099-USGS_LTA.json On the background of these requirements for sensor calibration, intercalibration and product validation, the subgroup on Calibration and Validation of the Committee on Earth Observing System (CEOS) formulated the following recommendation during the plenary session held in China at the end of 2004, with the goal of setting-up and operating an internet based system to provide sensor data, protocols and guidelines for these purposes: Background: Reference Datasets are required to support the understanding of climate change and quality assure operational services by Earth Observing satellites. The data from different sensors and the resulting synergistic data products require a high level of accuracy that can only be obtained through continuous traceable calibration and validation activities. Requirement: Initiate an activity to document a reference methodology to predict Top of Atmosphere (TOA) radiance for which currently flying and planned wide swath sensors can be intercompared, i.e. define a standard for traceability. Also create and maintain a fully accessible web page containing, on an instrument basis, links to all instrument characteristics needed for intercomparisons as specified above, ideally in a common format. In addition, create and maintain a database (e.g. SADE) of instrument data for specific vicarious calibration sites, including site characteristics, in a common format. Each agency is responsible for providing data for their instruments in this common format. Recommendation : The required activities described above should be supported for an implementation period of two years and a maintenance period over two subsequent years. The CEOS should encourage a member agency to accept the lead role in supporting this activity. CEOS should request all member agencies to support this activity by providing appropriate information and data in a timely manner. Pseudo-Invariant Calibration Sites (PICS): Algeria 3 is one of six CEOS reference Pseudo-Invariant Calibration Sites (PICS) that are CEOS Reference Test Sites. Besides the nominally good site characteristics (temporal stability, uniformity, homogeneity, etc.), these six PICS were selected by also taking into account their heritage and the large number of datasets from multiple instruments that already existed in the EO archives and the long history of characterization performed over these sites. The PICS have high reflectance and are usually made up of sand dunes with climatologically low aerosol loading and practically no vegetation. Consequently, these PICS can be used to evaluate the long-term stability of instrument and facilitate inter-comparison of multiple instruments. not-provided +CH-OG-1-GPS-10S.v0.0 10 sec GPS ground tracking data SCIOPS 2001-05-28 -63.51, -45.69, 170.42, 78.87 https://cmr.earthdata.nasa.gov/search/concepts/C1214586614-SCIOPS.json This data set comprises GPS ground data of a sample rate of 10 sec, generated by decoding and sampling GPS high rate ground data. This raw data passed no quality control. The data are given in the Rinex 2.1 format. not-provided CIESIN_SEDAC_EPI_2008.v2008.00 2008 Environmental Performance Index (EPI) SEDAC 1994-01-01 2007-12-31 -180, -55, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179001707-SEDAC.json The 2008 Environmental Performance Index (EPI) centers on two broad environmental protection objectives: (1) reducing environmental stresses on human health, and (2) promoting ecosystem vitality and sound natural resource management. Derived from a careful review of the environmental literature, these twin goals mirror the priorities expressed by policymakers. Environmental health and ecosystem vitality are gauged using 25 indicators tracked in six well-established policy categories: Environmental Health (Environmental Burden of Disease, Water, and Air Pollution), Air Pollution (effects on ecosystems), Water (effects on ecosystems), Biodiversity and Habitat, Productive Natural Resources (Forestry, Fisheries, and Agriculture), and Climate Change. The 2008 EPI utilizes a proximity-to-target methodology in which performance on each indicator is rated on a 0 to 100 scale (100 represents �at target�). By identifying specific targets and measuring how close each country comes to them, the EPI provides a foundation for policy analysis and a context for evaluating performance. Issue-by-issue and aggregate rankings facilitate cross-country comparisons both globally and within relevant peer groups. The 2008 EPI is the result of collaboration among the Yale Center for Environmental Law and Policy (YCELP), Columbia University Center for International Earth Science Information Network (CIESIN), World Economic Forum (WEF), and the Joint Research Centre (JRC), European Commission. not-provided CIESIN_SEDAC_EPI_2010.v2010.00 2010 Environmental Performance Index (EPI) SEDAC 1994-01-01 2009-12-31 -180, -55, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179002147-SEDAC.json The 2010 Environmental Performance Index (EPI) ranks 163 countries on environmental performance based on twenty-five indicators grouped within ten core policy categories addressing environmental health, air quality, water resource management, biodiversity and habitat, forestry, fisheries, agriculture, and climate change in the context of two broad objectives: environmental health and ecosystem vitality. The EPI�s proximity-to-target methodology facilitates cross-country comparisons among economic and regional peer groups. It was formally released in Davos, Switzerland, at the annual meeting of the World Economic Forum on January 28, 2010. The 2010 EPI is the result of collaboration between the Yale Center for Environmental Law and Policy (YCELP) and the Columbia University Center for International Earth Science Information Network (CIESIN). not-provided CIESIN_SEDAC_EPI_2012.v2012.00 2012 Environmental Performance Index and Pilot Trend Environmental Performance Index SEDAC 2000-01-01 2010-12-31 -180, -55, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000000-SEDAC.json The 2012 Environmental Performance Index (EPI) ranks 132 countries on 22 performance indicators in the following 10 policy categories: environmental burden of disease, water (effects on human health), air pollution (effects on human health), air pollution (ecosystem effects), water resources (ecosystem effects), biodiversity and habitat, forestry, fisheries, agriculture and climate change. These categories track performance and progress on two broad policy objectives, environmental health and ecosystem vitality. Each indicator has an associated environmental public health or ecosystem sustainability target. The EPI's proximity-to-target methodology facilitates cross-country comparisons among economic and regional peer groups. The Pilot Trend Environmental Performance Index (Trend EPI) ranks countries on the change in their environmental performance over the last decade. As a complement to the EPI, the Trend EPI shows who is improving and who is declining over time. The 2012 EPI and Pilot Trend EPI were formally released in Davos, Switzerland, at the annual meeting of the World Economic Forum on January 27, 2012. These are the result of collaboration between the Yale Center for Environmental Law and Policy (YCELP) and the Columbia University Center for International Earth Science Information Network (CIESIN). The Interactive Website for the 2012 EPI is at http://epi.yale.edu/. not-provided @@ -229,6 +224,7 @@ GreenBay.v0 2010 Measurements made in Green Bay, Wisconsin OB_DAAC 2010-09-17 - IKONOS_MSI_L1B.v1 IKONOS Level 1B Multispectral 4-Band Satellite Imagery CSDA 1999-10-14 2015-03-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2497453433-CSDA.json The IKONOS Level 1B Multispectral 4-Band Imagery collection contains satellite imagery acquired from Maxar Technologies (formerly known as DigitalGlobe) by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery was collected by the IKONOS satellite using the Optical Sensor Assembly instrument across the global land surface from October 1999 to March 2015. This satellite imagery is in the visible and near-infrared waveband range with data in the blue, green, red, and near-infrared wavelengths. The spatial resolution is 3.2m at nadir and the temporal resolution is approximately 3 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program. not-provided IKONOS_Pan_L1B.v1 IKONOS Level 1B Panchromatic Satellite Imagery CSDA 1999-10-24 2015-03-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2497468825-CSDA.json The IKONOS Panchromatic Imagery collection contains satellite imagery acquired from Maxar Technologies (formerly known as DigitalGlobe) by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery was collected by the IKONOS satellite using the Optical Sensor Assembly instrument across the global land surface from October 1999 to March 2015. This data product includes panchromatic imagery with a spatial resolution of 0.82m at nadir and a temporal resolution of approximately 3 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program. not-provided IMS1_HYSI_GEO.v1.0 IMS-1 HYSI TOA Radiance and Reflectance Product ISRO 2008-06-22 2012-09-10 -6.0364, -78.8236, 152.6286, 78.6815 https://cmr.earthdata.nasa.gov/search/concepts/C1214622602-ISRO.json The data received from IMS1, HySI which operates in 64 spectral bands in VNIR bands(400-900nm) with 500 meter spatial resolution and swath of 128 kms. not-provided +ISERV.v1 International Space Station SERVIR Environmental Research and Visualization System V1 USGS_EROS 2013-03-27 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1379906336-USGS_EROS.json Abstract: The ISS SERVIR Environmental Research and Visualization System (ISERV) acquired images of the Earth's surface from the International Space Station (ISS). The goal was to improve automatic image capturing and data transfer. ISERV's main component was the optical assembly which consisted of a 9.25 inch Schmidt-Cassegrain telescope, a focal reducer (field of view enlarger), a digital single lens reflex camera, and a high precision focusing mechanism. A motorized 2-axis pointing mount allowed pointing at targets approximately 23 degrees from nadir in both along- and across-track directions. not-provided IXBMIGEO.v2 MISR Geometric Parameters subset for the INTEX-B region V002 LARC 2006-02-28 2006-04-03 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000301-LARC.json This file contains the Geometric Parameters which measure the sun and view angles at the reference ellipsoid for the INTEXB_2006 theme. not-provided KOPRI-KPDC-00000008.v1 1998 Seismic Data, Antarctica AMD_KOPRI 1998-12-07 1998-12-11 -66.266667, -64.616667, -64.416667, -62.995 https://cmr.earthdata.nasa.gov/search/concepts/C2244292774-AMD_KOPRI.json "Korean Antarctic survey carried out as part of step 2 project in year 2 of 'the Antarctic Undersea Geological Survey' was conducted in the Ⅱ region around the northwestern continent of the Antarctic Peninsula. This area is northwest of Anvers Island, including areas around the pericontinent from the continental shelf to the continental rise zone. The investigation period for this project took a total of 8 days for moving navigation, the survey of the side lines and drilling investigation. After seismic investigation, a surface drilling investigation was conducted in coring point was decided from the reference seismic section. 10 researcher from ‘Korea Ocean Research and Development Institute’ participated in the field survey. We took on lease Russian icebreaker ""Yuzhmorgeologiya""." not-provided KOPRI-KPDC-00000009.v1 1997 Seismic Data, Antarctica AMD_KOPRI 1997-12-23 1997-12-28 -64.699722, -63.525, -62.157778, -62.041389 https://cmr.earthdata.nasa.gov/search/concepts/C2244293126-AMD_KOPRI.json Korean Antarctic survey carried out as part of step 2 project in year 1 of ‘The Antarctic Undersea Geological Survey’ in 1997 was conducted in a continental shelf in the northwestern part of the Antarctic Peninsula. The research period took a total of 8 days, including 6 days for the seismic survey and 2 days for the drilling investigation. We took on lease Norway R/V 'Polar Duke' and 10 researchers from ‘Korea Ocean Research and Development Institute’ participated as field investigation personnel. The Teac single-channel recorder, EPC Recorder, Q/C MicroMax system etc. was used mainly by Sleeve gun used as a sound source, compressor for creating compressed air, DFS-V Recorder for multi-channel Seismic record, 12 –channel geophone of seismic streamers. Additional Gravity Core was used for sediment research through drilling. not-provided @@ -240,6 +236,7 @@ KOPRI-KPDC-00000052.v1 1995 Sediment Core, Antarctica AMD_KOPRI 1995-12-19 1995- KOPRI-KPDC-00000053.v1 1996 Sediment Core, Antarctica AMD_KOPRI 1996-12-16 1996-12-16 -60.151944, -62.100278, -59.717778, -62.051389 https://cmr.earthdata.nasa.gov/search/concepts/C2244291950-AMD_KOPRI.json "Korean Antarctic survey was conducted in west of the Bransfeed Strait, a basin between the Antarctic Peninsula and the south Shetland Islands. It tooks 9 days. seismic investigation and drilling investigation were conducted at the same time during the field survey. We took on lease Russian R/V ""Yuzhmorgeologiya"" which is marine geology, geophysical survey vessel and Icebreaker and 10 researchers from ‘Korea Ocean Research and Development Institute’ and 3 academic personnel participated in the cruise as field investigation personnel." not-provided KOPRI-KPDC-00000054.v1 1997 Sediment Core, Antarctica AMD_KOPRI 1997-12-28 1997-12-29 -63.396667, -63.886111, -62.700833, -62.536389 https://cmr.earthdata.nasa.gov/search/concepts/C2244292254-AMD_KOPRI.json Korean Antarctic survey was conducted in 1997 carried out in a continental shelf in the northwestern part of the Antarctic Peninsula. It took 2 days. We took on lease Norway R/V 'Polar Duke' and 11 researchers from ‘Korea Ocean Research and Development Institute’ participated as field investigation personnel. The Teac single-channel recorder, EPC Recorder, Q/C MicroMax system etc. was used mainly by Sleeve gun used as a sound source, compressor for creating compressed air, DFS-V Recorder for multi-channel Seismic record, 12-channel geophone of seismic streamers. Additional Gravity Core was used for sediment research through drilling. not-provided KOPRI-KPDC-00000055.v1 1998 Sediment Core, Antarctica AMD_KOPRI 1998-12-11 1998-12-12 -66.32, -63.95, -63.47, -62.943333 https://cmr.earthdata.nasa.gov/search/concepts/C2244294165-AMD_KOPRI.json "Korean Antarctic survey was conducted in the continental margin (II region) of the northwestern Antarctic Peninsula. We took on lease Russian R/V ""Yuzhmorgeologiya"" (5500 ton, ice strengthed vessel) and 10 researchers participated in the cruise, including acquisition of multichannel seismic, gravity, and magnetometer as well as a detailed samplings (box cores, gravity cores, and grab samples). 1. Geophysical researches (Multichannel seismic and SBP surveys) 2. Paleoceanographic researches" not-provided +KUKRI_He (U-Th)/He ages from the Kukri Hills of southern Victoria Land SCIOPS 1970-01-01 162.7, -77.7, 162.7, -77.7 https://cmr.earthdata.nasa.gov/search/concepts/C1214587974-SCIOPS.json The data set consists of (U-Th)/He ages collected from three vertical profiles from the the Kukri Hills (north side of the Ferrar Glacier) of Southern Victoria Land. The data set provides information on the cooling history and hence the denduation history of the Transantarctic Mountains in this area. Analyses were all carried out at the (U-Th)/He lab of Ken Farley at the Californai Institute of Technology. not-provided L1B_Wind_Products Aeolus preliminary HLOS (horizontal line-of-sight) wind observations for Rayleigh and Mie receivers ESA 2020-04-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2119689596-ESA.json The Level 1B wind product of the Aeolus mission contains the preliminary HLOS (horizontal line-of-sight) wind observations for Rayleigh and Mie receivers, which are generated in Near Real Time. Standard atmospheric correction (Rayleigh channel), receiver response and bias correction is applied. The product is generated within 3 hours after data acquisition. not-provided L2B_Wind_Products Aeolus Scientific L2B Rayleigh/Mie wind product ESA 2020-04-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2119689544-ESA.json The Level 2B wind product of the Aeolus mission is a geo-located consolidated HLOS (horizontal line-of-sight) wind observation with actual atmospheric correction applied to Rayleigh channel. The product is generated by within 3 hours after data acquisition. not-provided L2C_Wind_products Aeolus Level 2C assisted wind fields resulting from NWP Numerical Weather Prediction assimilation processing ESA 2020-07-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2619280864-ESA.json The Level 2C wind product of the Aeolus mission provides ECMWF analysis horizontal wind vectors at the geolocations of assimilated L2B HLOS wind components. The L2C can therefore be described as an Aeolus-assisted horizontal wind vector product. The L2C is a distinct product, however the L2C and L2B share a common Earth Explorer file template, with the L2C being a superset of the L2B. The L2C consists of extra datasets appended to the L2B product with information which are relevant to the data assimilation of the L2B winds. not-provided @@ -253,7 +250,6 @@ M1_ AVH09C1.v6 METOP-B AVHRR Atmospherically Corrected Surface Reflectance Daily M1_AVH13C1.v6 METOP-B AVHRR Atmospherically Corrected Normalized Difference Vegetation Index Daily L3 Global 0.05 Deg. CMG LAADS 2013-01-16 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2751635237-LAADS.json The Long-Term Data Record (LTDR) produces, validates, and distributes a global land surface climate data record (CDR) that uses both mature and well-tested algorithms in concert with the best-available polar-orbiting satellite data from past to the present. The CDR is critically important to studying global climate change. The LTDR project is unique in that it serves as a bridge that connects data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR), the EOS Moderate resolution Imaging Spectroradiometer (MODIS), the Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Joint Polar Satellite System (JPSS) VIIRS missions. The LTDR draws from the following eight AVHRR missions: NOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19, and MetOp-B. Currently, the project generates a daily surface reflectance product as the fundamental climate data record (FCDR) and derives daily Normalized Differential Vegetation Index (NDVI) and Leaf-Area Index/fraction of absorbed Photosynthetically Active Radiation (LAI/fPAR) as two thematic CDRs (TCDR). LAI/fPAR was developed as an experimental product. The METOP-B AVHRR Atmospherically Corrected Normalized Difference Vegetation Index (NDVI) Daily L3 Global 0.05 Deg CMG, short-name M1_AVH13C1 is generated from GIMMS Advanced Processing System (GAPS) BRDF-corrected Surface Reflectance product (M1_AVH01C1). The M1_AVH13C1 product is available in HDF4 file format. not-provided MCD06COSP_D3_MODIS.v6.1 MODIS (Aqua/Terra) Cloud Properties Level 3 daily, 1x1 degree grid LAADS 2002-07-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1887589686-LAADS.json The combined MODIS (Aqua/Terra) Cloud Properties Level 3 daily, 1x1 degree grid product represents a new addition that is especially geared to facilitate climate scientists who deal with both models and observations. MCD06COSP_D3_MODIS represents the daily product’s short-name. The “COSP” acronym in its short-name stands for Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package. This product is an aggregation of combined MODIS Level-2 inputs from both the Terra and Aqua incarnations (MOD35/MOD06 and MYD35/MYD06, respectively), and employs an aggregation methodology consistent with the MOD08 and MYD08 products. Provided in netCDF4 format, it contains 23 aggregated science data sets (SDS/parameters). not-provided MCD06COSP_M3_MODIS.v6.1 MODIS (Aqua/Terra) Cloud Properties Level 3 monthly, 1x1 degree grid LAADS 2002-07-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1888024429-LAADS.json The combined MODIS (Aqua/Terra) Cloud Properties Level 3 monthly, 1x1 degree grid product represents a new addition that is especially geared to facilitate climate scientists who deal with both models and observations. MCD06COSP_D3_MODIS represents the daily product’s short-name. The “COSP” acronym in its short-name stands for Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package. The L3 monthly product is derived by aggregating the daily-produced Aqua+Terra/MODIS D3 Cloud Properties product (MCD06COSP_D3_MODIS). Provided in netCDF4 format, it contains 23 aggregated science data sets (SDS/parameters). not-provided -MCD14DL_C5_NRT.v005 MODIS/Aqua+Terra Thermal Anomalies/Fire locations 1km FIRMS V005 NRT LM_FIRMS 2014-01-28 -180, -80, 180, 80 https://cmr.earthdata.nasa.gov/search/concepts/C1219768065-LM_FIRMS.json Near Real-Time (NRT) MODIS Thermal Anomalies / Fire locations processed by FIRMS (Fire Information for Resource Management System) - Land Atmosphere Near real time Capability for EOS (LANCE), using swath products (MOD14/MYD14) rather than the tiled MOD14A1 and MYD14A1 products. The thermal anomalies / active fire represent the center of a 1km pixel that is flagged by the MODIS MOD14/MYD14 Fire and Thermal Anomalies algorithm (Giglio 2003) as containing one or more fires within the pixel. This is the most basic fire product in which active fires and other thermal anomalies, such as volcanoes, are identified.MCD14DL are available in the following formats: TXT, SHP, KML, WMS. These data are also provided through the FIRMS Fire Email Alerts. Please note only the TXT and SHP files contain all the attributes. not-provided MIANACP.v1 MISR Aerosol Climatology Product V001 LARC 1999-11-22 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C185127378-LARC.json MIANACP_1 is the Multi-angle Imaging SpectroRadiometer (MISR) Aerosol Climatology Product version 1. It is 1) the microphysical and scattering characteristics of pure aerosol upon which routine retrievals are based; 2) mixtures of pure aerosol to be compared with MISR observations; and 3) likelihood value assigned to each mode geographically. The ACP describes mixtures of up to three component aerosol types from a list of eight components, in varying proportions. ACP component aerosol particle data quality depends on the ACP input data, which are based on aerosol particles described in the literature, and consider MISR-specific sensitivity to particle size, single-scattering albedo, and shape, and shape - roughly: small, medium and large; dirty and clean; spherical and nonspherical [Kahn et al. , 1998; 2001]. Also reported in the ACP are the mixtures of these components used by the retrieval algorithm. The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward, and four cameras pointing aftward. It takes seven minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm. not-provided MIANCAGP.v1 MISR Ancillary Geographic Product V001 LARC 1999-11-07 2005-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C183897339-LARC.json MIANCAGP_1 is the Multi-angle Imaging SpectroRadiometer (MISR) Ancillary Geographic Product version 1. It is a set of 233 pre-computed files. Each AGP file pertains to a single Terra orbital path. MISR production software relies on information in the AGP, such as digital terrain elevation, as input to the algorithms which generate MISR products. The AGP contains eleven fields of geographical data. This product consists primarily of geolocation data on a Space Oblique Mercator (SOM) Grid. It has 233 parts, corresponding to the 233 repeat orbits of the EOS-AM1 Spacecraft. The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward, and four cameras pointing aftward. It takes seven minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm. not-provided MIANCARP.v2 MISR Ancillary Radiometric Product V002 LARC 1999-12-28 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179031521-LARC.json MIANCARP_2 is the Multi-angle Imaging SpectroRadiometer (MISR) Ancillary Radiometric Product version 2. It is composed of 4 files covering instrument characterization data, pre-flight calibration data, in-flight calibration data, and configuration parameters. The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward, and four cameras pointing aftward. It takes seven minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm. not-provided @@ -273,6 +269,7 @@ MYDCSR_B.v6.1 MODIS/Aqua 8-Day Clear Sky Radiance Bias Daily L3 Global 1Deg Zona MYDGB0.v6.1NRT MODIS/Aqua 5-minute GBAD data in L0 format - NRT LANCEMODIS 2017-10-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1427015288-LANCEMODIS.json MODIS/Aqua Near Real Time (NRT) 5-minute GBAD data in L0 format. not-provided NEX-DCP30.v1 Downscaled 30 Arc-Second CMIP5 Climate Projections for Studies of Climate Change Impacts in the United States NCCS 1950-01-01 2099-12-31 -125.0208333, 24.0625, -66.4791667, 49.9375 https://cmr.earthdata.nasa.gov/search/concepts/C1542175061-NCCS.json This NASA dataset is provided to assist the science community in conducting studies of climate change impacts at local to regional scales, and to enhance public understanding of possible future climate patterns and climate impacts at the scale of individual neighborhoods and communities. This dataset is intended for use in scientific research only, and use of this dataset for other purposes, such as commercial applications, and engineering or design studies is not recommended without consultation with a qualified expert. Community feedback to improve and validate the dataset for modeling usage is appreciated. Email comments to bridget@climateanalyticsgroup.org. Dataset File Name: NASA Earth Exchange (NEX) Downscaled Climate Projections (NEXDCP30), https://portal.nccs.nasa.gov/portal_home/published/NEX.html not-provided NEX-GDDP.v1 NASA Earth Exchange Global Daily Downscaled Projections NCCS 1950-01-01 2100-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1374483929-NCCS.json The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate scenarios for the globe that are derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios known as Representative Concentration Pathways (RCPs). The CMIP5 GCM runs were developed in support of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). The NEX-GDDP dataset includes downscaled projections for RCP 4.5 and RCP 8.5 from the 21 models and scenarios for which daily scenarios were produced and distributed under CMIP5. Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100. The spatial resolution of the dataset is 0.25 degrees (~25 km x 25 km). The NEX-GDDP dataset is provided to assist the science community in conducting studies of climate change impacts at local to regional scales, and to enhance public understanding of possible future global climate patterns at the spatial scale of individual towns, cities, and watersheds. Each of the climate projections includes monthly averaged maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2005 (Retrospective Run) and from 2006 to 2099 (Prospective Run). not-provided +NIPR_UAP_ELF_SYO 1-100Hz ULF/ELF Electromagnetic Wave Observation at Syowa Station SCIOPS 2000-01-01 39.6, -69, 39.6, -69 https://cmr.earthdata.nasa.gov/search/concepts/C1214590112-SCIOPS.json 1-100Hz ULF/ELF Electromagnetic Wave Observation at Syowa Station not-provided NMMIEAI-L2-NRT.v2 OMPS-NPP L2 NM Aerosol Index swath orbital NRT OMINRT 2011-11-07 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1657477341-OMINRT.json The OMPS-NPP L2 NM Aerosol Index swath orbital V2 for Near Real Time. For the standard product see the OMPS_NPP_NMMIEAI_L2 product in CMR .The aerosol index is derived from normalized radiances using 2 wavelength pairs at 340 and 378.5 nm. Additionally, this data product contains measurements of normalized radiances, reflectivity, cloud fraction, reflectivity, and other ancillary variables. not-provided NMSO2-PCA-L2-NRT.v2 OMPS/NPP PCA SO2 Total Column 1-Orbit L2 Swath 50x50km NRT OMINRT 2011-10-28 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1439293808-OMINRT.json The OMPS-NPP L2 NM Sulfur Dioxide (SO2) Total and Tropospheric Column swath orbital collection 2 version 2.0 product contains the retrieved sulfur dioxide (SO2) measured by the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) sensor on the Suomi-NPP satellite. A Principle Component Analysis (PCA) algorithm is used to retrieve the SO2 total column amount and column amounts in the lower (centered at 2.5 km), middle (centered at 7.5 km) and upper (centered at 11 km) troposphere, as well as the lower stratosphere (centered at 16 km). Each granule contains data from the daylight portion for a single orbit or about 50 minutes. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14 orbits per day each with a swath width of 2600 km. There are 35 pixels in the cross-track direction, with a pixel resolution of about 50 km x 50 km at nadir. The files are written using the Hierarchical Data Format Version 5 or HDF5. not-provided NMTO3NRT.v2 OMPS-NPP L2 NM Ozone (O3) Total Column swath orbital NRT OMINRT 2011-10-28 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1439272084-OMINRT.json The OMPS-NPP L2 NM Ozone (O3) Total Column swath orbital product provides total ozone measurements from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) instrument on the Suomi-NPP satellite.The total column ozone amount is derived from normalized radiances using 2 wavelength pairs 317.5 and 331.2 nm under most conditions, and 331.2 and 360 nm for high ozone and high solar zenith angle conditions. Additionally, this data product contains measurements of UV aerosol index and reflectivity at 331 nm.Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14.5 orbits per day, each has typically 400 swaths. The swath width of the NM is about 2800 km with 36 scenes, or pixels, with a footprint size of 50 km x 50 km at nadir. The L2 NM Ozone data are written using the Hierarchical Data Format Version 5 or HDF5. not-provided @@ -342,8 +339,10 @@ amsua16sp.v1 ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-16 V1 G asas Advanced Solid-state Array Spectroradiometer (ASAS) USGS_LTA 1988-06-26 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220566261-USGS_LTA.json The Advanced Solid-state Array Spectroradiometer (ASAS) data collection contains data collected by the ASAS sensor flown aboard NASA aircraft. A fundamental use of ASAS data is to characterize and understand the directional variability in solar energy scattered by various land surface cover types (e.g.,crops, forests, prairie grass, snow, or bare soil). The sensor's Bidirectional Reflectance Distribution Function determines the variation in the reflectance of a surface as a function of both the view zenith angle and solar illumination angle. The ASAS sensor is a hyperspectral, multiangle, airborne remote sensing instrument maintained and operated by the Laboratory for Terrestrial Physics at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The ASAS instrument is mounted on the underside of either NASA C-130 or NASA P-3 aircraft and is capable of off-nadir pointing from approximately 70 degrees forward to 55 degrees aft along the direction of flight. The aircraft is flown at an altitude of 5000 - 6000 meters (approximately 16,000 - 20,000 ft.). Data in the ASAS collection primarily cover areas over the continental United States, but some ASAS data are also available over areas in Canada and western Africa. The ASAS data were collected between 1988 and 1994. not-provided aster_global_dem ASTER Global DEM USGS_LTA 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220567908-USGS_LTA.json ASTER is capable of collecting in-track stereo using nadir- and aft-looking near infrared cameras. Since 2001, these stereo pairs have been used to produce single-scene (60- x 60-kilomenter (km)) digital elevation models (DEM) having vertical (root-mean-squared-error) accuracies generally between 10- and 25-meters (m). The methodology used by Japan's Sensor Information Laboratory Corporation (SILC) to produce the ASTER GDEM involves automated processing of the entire ASTER Level-1A archive. Stereo-correlation is used to produce over one million individual scene-based ASTER DEMs, to which cloud masking is applied to remove cloudy pixels. All cloud-screened DEMS are stacked and residual bad values and outliers are removed. Selected data are averaged to create final pixel values, and residual anomalies are corrected before partitioning the data into 1 degree (°) x 1° tiles. The ASTER GDEM covers land surfaces between 83°N and 83°S and is comprised of 22,702 tiles. Tiles that contain at least 0.01% land area are included. The ASTER GDEM is distributed as Geographic Tagged Image File Format (GeoTIFF) files with geographic coordinates (latitude, longitude). The data are posted on a 1 arc-second (approximately 30–m at the equator) grid and referenced to the 1984 World Geodetic System (WGS84)/ 1996 Earth Gravitational Model (EGM96) geoid. not-provided b673f41b-d934-49e4-af6b-44bbdf164367 AVHRR - Land Surface Temperature (LST) - Europe, Daytime FEDEO 1998-02-23 -24, 28, 57, 78 https://cmr.earthdata.nasa.gov/search/concepts/C2207458008-FEDEO.json "The ""Land Surface Temperature derived from NOAA-AVHRR data (LST_AVHRR)"" is a fixed grid map (in stereographic projection ) with a spatial resolution of 1.1 km. The total size covering Europe is 4100 samples by 4300 lines. Within 24 hours of acquiring data from the satellite, day-time and night-time LSTs are calculated. In general, the products utilise data from all six of the passes that the satellite makes over Europe in each 24 hour period. For the daily day-time LST maps, the compositing criterion for the three day-time passes is maximum NDVI value and for daily night-time LST maps, the criterion is the maximum night-time LST value of the three night-time passes. Weekly and monthly day-time or night-time LST composite products are also produced by averaging daily day-time or daily night-time LST values, respectively. The range of LST values is scaled between –39.5°C and +87°C with a radiometric resolution of 0.5°C. A value of –40°C is used for water. Clouds are masked out as bad values. For additional information, please see: https://wdc.dlr.de/sensors/avhrr/" not-provided +blue_ice_core_DML2004_AS 101.1 m long horizontal blue ice core collected from Scharffenbergbotnen, DML, Antarctica, in 2003/2004 SCIOPS 1970-01-01 -180, -90, 180, -62.83 https://cmr.earthdata.nasa.gov/search/concepts/C1214614210-SCIOPS.json Horizontal blue ice core collected from the surface of a blue ice area in Scharffenbergbotnen, Heimefrontfjella, DML. Samples were collected in austral summer 2003/2004 and transported to Finland for chemical analyses. The blue ice core is estimated to represent a 1000-year period of climate history 20 - 40 kyr B.P.. The results of the analyses will be available in 2005. not-provided chesapeake_val_2013.v0 2013 Chesapeake Bay measurements OB_DAAC 2013-04-11 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360188-OB_DAAC.json 2013 Chesapeake Bay measurements. not-provided ef6a9266-a210-4431-a4af-06cec4274726 Cartosat-1 (IRS-P5) - Panchromatic Images (PAN) - Europe, Monographic FEDEO 2015-02-10 -25, 30, 45, 80 https://cmr.earthdata.nasa.gov/search/concepts/C2207457985-FEDEO.json Indian Remote Sensing satellites (IRS) are a series of Earth Observation satellites, built, launched and maintained by Indian Space Research Organisation. The IRS series provides many remote sensing services to India and international ground stations. The satellite has two panchromatic cameras that were especially designed for in flight stereo viewing. However, this collection contains the monoscopic data. not-provided +envidat-lwf-34.v2019-03-06 10-HS Pfynwald SCIOPS 2019-01-01 2019-01-01 7.61211, 46.30279, 7.61211, 46.30279 https://cmr.earthdata.nasa.gov/search/concepts/C1647993129-SCIOPS.json Continuous measurement of soil water content at 10 and 80 cm depth (3 replications) with 10-HS soil moisture probes (Decagon Incorporation, Pullman, WA, USA). ### Purpose: ### Monitoring of the soil water matrix potential ### Paper Citation: ### * Dobbertin, M.; Eilmann, B.; Bleuler, P.; Giuggiola, A.; Graf Pannatier, E.; Landolt, W.; Schleppi, P.; Rigling, A., 2010: Effect of irrigation on needle morphology, shoot and stem growth in a drought-exposed Pinus sylvestris forest. Tree Physiology, 30, 3: 346-360. [doi: 10.1093/treephys/tpp123](http://doi.org/10.1093/treephys/tpp123) not-provided gov.noaa.nodc:0000029 1990, 1991, 1992 and 1995 CRETM/LMER Zooplankton Data Sets (NCEI Accession 0000029) NOAA_NCEI 1990-09-26 1995-05-26 -124.041667, 0.766667, -16.25, 46.263167 https://cmr.earthdata.nasa.gov/search/concepts/C2089372282-NOAA_NCEI.json Not provided not-provided gov.noaa.nodc:0000035 1996 - Early 1998 CRETM/LMER Phytoplankton Data (NCEI Accession 0000035) NOAA_NCEI 1996-07-09 1998-03-06 -124.003, 46.179833, -123.183167, 46.261667 https://cmr.earthdata.nasa.gov/search/concepts/C2089372325-NOAA_NCEI.json Pump cast sampling, and associated CTD casts took place from a fixed vessel during one 28-35 day cruise per year in 1990, 1991, 1992, 1995, and 1996. In 1997 there were 2 week cruises in May, July, and October. not-provided gov.noaa.nodc:0000052 1988 Resurrection Bay Zooplankton Data Set from 01 March 1988 to 28 June 1988 (NCEI Accession 0000052) NOAA_NCEI 1988-03-01 1988-06-28 -149.4083, 59.9117, -149.3583, 60.02 https://cmr.earthdata.nasa.gov/search/concepts/C2089372461-NOAA_NCEI.json Zooplantkon and beach tar data were collected using plankton net casts in the Gulf of Alaska from the ALPHA HELIX. Data were collected from 01 March 1988 to 28 June 1988 by University of Alaska in Fairbanks; Institute of Marine Science with support from the Gulf of Alaska - 1 (GAK-1) project. not-provided @@ -358,6 +357,7 @@ gov.noaa.nodc:GHRSST-OISST_UHR_NRT-GOS-L4-BLK.v2.0 Black Sea Ultra High Resoluti gov.noaa.nodc:GHRSST-REMSS-L2P_GRIDDED_25-TMI.v4.0 GHRSST L2P Gridded Global Subskin Sea Surface Temperature from the Tropical Rainfall Mapping Mission (TRMM) Microwave Imager (TMI) (GDS version 1) GHRSSTCWIC 1998-01-01 2015-04-06 -180, -40, 180, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2213645156-GHRSSTCWIC.json "The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is a well calibrated passive microwave radiometer, similar to SSM/I, that contains lower frequency channels required for sea surface temperature (SST) retrievals. The TRMM is a joint venture between NASA and the Japan Aerospace Exploration Agency (JAXA) to measure precipitation, water vapor, SST and wind in the global tropical regions and was launched in November 1997. The TRMM satellite travels west to east in a 402 km altitude semi-equatorial precessing orbit that results in day-to-day changes in the observation time of any given earth location between 38S and 38N. In contrast to infrared SST observations, microwave retrievals can be measured through most clouds, and are also insensitive to water vapor and aerosols. Remote Sensing Systems is the producer of these gridded TMI SST data for the Group for High Resolution Sea Surface Temperature (GHRSST) Project. Although the product designation is ""L2P_GRIDDED"" it is in actuality a Level 3 Collated (L3C) product as defined in the GHRSST Data Processing Specification (GDS) version 2.0. Its ""L2P_GRIDDED"" name derives from a deprecated specification in the early Pilot Project phase of GHRSST (pre 2008) and has remained for file naming continuity. In this dataset, both ascending (daytime) and descending (daytime) gridded orbital passes on packaged into the same daily file." not-provided gov.noaa.nodc:GHRSST-VIIRS_NPP-NAVO-L2P.v3.0 GHRSST Level 2P 1 m Depth Global Sea Surface Temperature version 3.0 from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite (GDS version 2) GHRSSTCWIC 2013-06-28 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2213644303-GHRSSTCWIC.json A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on retrievals from the Visible Infrared Imaging Radiometer Suite (VIIRS). This sensor resides on the Suomi National Polar-orbiting Partnership (Suomi_NPP) satellite launched on 28 October 2011. VIIRS is a whiskbroom scanning radiometer which takes measurements in the cross-track direction within a field of regard of 112.56 degrees using 16 detectors and a double-sided mirror assembly. At a nominal altitude of 829 km, the swath width is 3060 km, providing full daily coverage both on the day and night side of the Earth. The VIIRS instrument is a 22-band, multi-spectral scanning radiometer that builds on the heritage of the MODIS, AVHRR and SeaWiFS sensors for sea surface temperature (SST) and ocean color. For the infrared bands for SST the effective pixel size is 750 meters at nadir and the pixel size variation across the swath is constrained to no more than 1600 meters at the edge of the swath. This L2P SST v3.0 is upgraded from the v2.0 with several significant improvements in processing algorithms, including contamination detection, cloud detection, and data format upgrades. It contains the global near daily-coverage Sea Surface Temperature at 1-meter depth with 750 m (along) x 750 m (cross) spatial resolution in swath coordinates. Each netCDF file has 768 x 3200 pixels in size, in compliance with the GHRSST Data Processing Specification (GDS) version 2 format specifications. not-provided lake_erie_aug_2014.v0 2014 Lake Erie measurements OB_DAAC 2014-08-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360418-OB_DAAC.json 2014 Lake Erie measurements. not-provided +latent-reserves-in-the-swiss-nfi.v1.0 'Latent reserves' within the Swiss NFI SCIOPS 2020-01-01 2020-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C1931110427-SCIOPS.json "The files refer to the data used in Portier et al. ""‘Latent reserves’: a hidden treasure in National Forest Inventories"" (2020) *Journal of Ecology*. **'Latent reserves'** are defined as plots in National Forest Inventories (NFI) that have been free of human influence for >40 to >70 years. They can be used to investigate and acquire a deeper understanding of attributes and processes of near-natural forests using existing long-term data. To determine which NFI sample plots could be considered ‘latent reserves’, criteria were defined based on the information available in the Swiss NFI database: * Shrub forests were excluded. * Plots must have been free of any kind of management, including salvage logging or sanitary cuts, for a minimum amount of time. Thresholds of 40, 50, 60 and 70 years without intervention were tested. * To ensure that species composition was not influenced by past management, plots where potential vegetation was classified as deciduous by Ellenberg & Klötzli (1972) had to have an observed proportion of deciduous trees matching the theoretical proportion expected in a natural deciduous forest, as defined by Kienast, Brzeziecki, & Wildi (1994). * Plots had to originate from natural regeneration. * Intensive livestock grazing must never have occurred on the plots. The tables stored here were derived from the first, second and third campaigns of the Swiss NFI. The raw data from the Swiss NFI can be provided free of charge within the scope of a contractual agreement (http://www.lfi.ch/dienstleist/daten-en.php). **** The files 'Data figure 2' to 'Data figure 8' are publicly available and contain the data used to produce the figures published in the paper. The files 'Plot-level data for characterisation of 'latent reserves' and 'Tree-level data for characterisation of 'latent reserves' contain all the data required to reproduce the section of the article concerning the characterisation of 'latent reserves' and the comparison to managed forests. The file 'Data for mortality analyses' contains the data required to reproduce the section of the article concerning tree mortality in 'latent reserves'. The access to these three files is restricted as they contain some raw data from the Swiss NFI, submitted to the Swiss law and only accessible upon contractual agreement. " not-provided law_dome_annual_msa.v1 150 year MSA sea ice proxy record from Law Dome, Antarctica AU_AADC 1841-01-01 1995-12-31 112.806946, -66.76972, 112.806946, -66.76972 https://cmr.earthdata.nasa.gov/search/concepts/C1214313532-AU_AADC.json "This MSA record (1841-1995) is from a Law Dome ice core called ""DSS"" in East Antarctica. It was calibrated against satellite sea ice records and used to reconstruct sea ice extent prior to the satellite era. The following is taken from the abstract of the paper (Curran et al., 2003). The instrumental record of Antarctic sea ice in recent decades does not reveal a clear signature of warming despite observational evidence from coastal Antarctica. This work shows a significant correlation (P less than 0.002) between methanesulphonic acid (MSA) concentrations from a Law Dome ice core and 22 years of satellite-derived sea ice extent (SIE) for the 80 degrees E to 140 degrees E sector. Applying this instrumental calibration to longer term MSA data (1841 to 1995 A.D.) suggests that there has been a 20% decline in SIE since about 1950. The decline is not uniform, showing large cyclical variations, with periods of about 11 years, that confuse trend detection over the relatively short satellite era. This work was completed as part of ASAC project 757 (ASAC_757)." not-provided mbs_wilhelm_msa_hooh.v1 15 year Wilhelm II Land MSA and HOOH shallow ice core record from Mount Brown South (MBS) AU_AADC 1984-01-01 1998-12-31 86.082, -69.13, 86.084, -69.12 https://cmr.earthdata.nasa.gov/search/concepts/C1214313640-AU_AADC.json This work presents results from a short firn core spanning 15 years collected from near Mount Brown, Wilhelm II Land, East Antarctica. Variations of methanesulphonic acid (MSA) at Mount Brown were positively correlated with sea-ice extent from the coastal region surrounding Mount Brown (60-1208 E) and from around the entire Antarctic coast (0-3608 E). Previous results from Law Dome identified this MSA-sea-ice relationship and proposed it as an Antarctic sea-ice proxy (Curran and others, 2003), with the strongest results found for the local Law Dome region. Our data provide supporting evidence for the Law Dome proxy (at another site in East Antarctica), but a deeper Mount Brown ice core is required to confirm the sea-ice decline suggested by Curran and others (2003). Results also indicate that this deeper record may also provide a more circum-Antarctic sea-ice proxy. This work was completed as part of ASAC project 757 (ASAC_757). not-provided urn:ogc:def:EOP:VITO:VGT_S10.v1 10 Days Synthesis of SPOT VEGETATION Images (VGT-S10) FEDEO 1998-04-01 2014-05-31 -180, -56, 180, 75 https://cmr.earthdata.nasa.gov/search/concepts/C2207472890-FEDEO.json The VGT-S10 are near-global or continental, 10-daily composite images which are synthesised from the 'best available' observations registered in the course of every 'dekad' by the orbiting earth observation system SPOT-VEGETATION. The products provide data from all spectral bands (SWIR, NIR, RED, BLUE), the NDVI and auxiliary data on image acquisition parameters. The VEGETATION system allows operational and near real-time applications, at global, continental and regional scales, in very broad environmentally and socio-economically critical fields. The VEGETATION instrument is operational since April 1998, first with VGT1, from March 2003 onwards, with VGT2. More information is available on: https://docs.terrascope.be/#/DataProducts/SPOT-VGT/Level3/Level3 not-provided