init

.Rprofile

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+source("renv/activate.R")

.gitignore

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+# R profile files
+*.Rproj.user
+*.Rhistory
+.Rproj.user
+
+# log files
+*.log
+
+# data files
+*.tif
+*.zip
+*.tar
+*.tar.bil
+*.bil
+*.hdr
+*.prj
+*.aux.xml
+*.stx
+*.qml
+*.tar.gz
+
+# system files
+.directory
+
+# do not ignore the following files
+!.gitkeep
+!*/

Makefile

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+all: readme data
+
+data:
+	R CMD BATCH --no-restore --no-save code/lumbierres-habitat-data.R
+
+clean:
+	rm -f results/*.tif
+
+readme:
+	R --slave -e "rmarkdown::render('README.Rmd')"
+
+.PHONY: all data readme

README.Rmd

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+---
+output:
+  rmarkdown::github_document:
+    html_preview: no
+---
+
+<!--- README.md is generated from README.Rmd. Please edit that file -->
+
+# Habitat classification data from Lumbierres *et al.* 2021
+
+[![lifecycle](https://img.shields.io/badge/Lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html)
+[![DOI](https://img.shields.io/badge/DOI-TODO-blue.svg)](https://doi.org/TODO)
+
+```{r, include = FALSE}
+knitr::opts_chunk$set(fig.path = "figures/README-", fig.align = "center")
+```
+
+This repository contains code to generate global habitat classification data (based on Lumbierres *et al.* 2021). Specifically, source data are downloaded from the [Zenodo Digital Archive](https://doi.org/10.5281/zenodo.5146072), and then projected to the World Behrmann coordinate reference system using (100 m resolution; [ESRI:4326 coordinate reference system](https://epsg.io/54017)). A processed version of the data can be downloaded from the [Zenodo Digital Repository](https://zenodo.org/badge/latestdoi/TODO). **All credit should go to Lumbierres *et al.* (2021), please cite their work if you use this dataset.**
+
+```{r "preliminary_processing", echo = FALSE, message = FALSE, warning = FALSE}
+# load packages
+library(dplyr)
+library(terra)
+library(ggplot2)
+
+# find file paths
+data_path <- dir("results", "^.*tif$", full.names = TRUE)
+
+# load raster
+data_raster <- terra::rast(data_path)
+
+# extract data to plot (note that we spatially sample data to reduce run time)
+plot_data <-
+  data_raster %>%
+  terra::spatSample(size = 400000, method = "regular", as.raster = TRUE) %>%
+  terra::as.data.frame(xy = TRUE) %>%
+  dplyr::rename(value = 3) %>%
+  dplyr::mutate(title = "Habitat classification") %>%
+  dplyr::mutate(subtitle = basename(data_path)) %>%
+  dplyr::mutate(value = as.character(value))
+
+# create an underlying map
+p <-
+  ggplot() +
+  coord_fixed(expand = FALSE) +
+  geom_tile(
+    data = plot_data,
+    mapping = aes(x = x, y = y, fill = value)
+  ) +
+  facet_wrap(~ title + subtitle) +
+  theme(
+    legend.pos = "hide",
+    axis.ticks = element_blank(),
+    axis.text = element_blank(),
+    axis.title = element_blank(),
+    axis.line = element_blank(),
+    axis.ticks.length = unit(0, "null"),
+    axis.ticks.margin = unit(0, "null"),
+    panel.border = element_blank(),
+    panel.background = element_blank(),
+    panel.grid = element_blank(),
+    legend.text = element_text(size = 8),
+    legend.margin = unit(0, "null"),
+    plot.margin = unit(c(0.001, 0.001, 0.001, 0.01), "pt"),
+    strip.background = ggplot2::element_rect(color = "black", fill = "black"),
+    strip.text = ggplot2::element_text(color = "white")
+  )
+```
+
+```{r "map", echo = FALSE, message = FALSE, warning = FALSE, fig.height = 2.4, fig.width = 5.0, dpi = 250}
+# render plot
+print(p)
+```
+
+## Metadata
+
+The habitat classification data are stored in a raster (GeoTIFF) file. The file name contains the version number of the original datasets (i.e., per the digital object identifier). The latest version of the file is ``r basename(data_path)``.
+
+The metadata for the ``r basename(data_path)`` raster file is shown below.
+
+```{r, echo = FALSE, comment = NA}
+withr::with_dir("results", {
+  cat(
+    system(paste("gdalinfo", basename(data_path)), intern = TRUE),
+    sep = "\n"
+  )
+})
+```
+
+## Usage
+
+You can run the code to produce the dataset using the system command `make clean all`. After processing has successfully completed, the code will produce two raster (GeoTIFF) files in the `results` directory.
+
+## Software requirements
+
+Operating system
+
+* Ubuntu (21.10) (300 Gb disk space available)
+
+Software
+
+* GNU make (version 4.1)
+* GDAL (version 3.2.2)
+* R (version 4.1.1)
+
+System packages
+
+* `gdal-bin`
+* `libudunits2-dev`
+* `libgdal-dev`
+* `libgeos-dev`
+* `libproj-dev`
+* `libxml2-dev`
+* `libssl-dev`
+
+## Citation
+
+This dataset was derived from Lumbierres *et al.* (2021). If you use this dataset, you should cite their work - they deserve all the credit!
+
+> Lumbierres, M (2021). *Map of habitat classes (Level 1) from the IUCN Habitat.* Zenodo Digital Repository. Available at https://doi.org/10.5281/zenodo.5146072.
+
+> Lumbierres M, Dahal PR, Di Marco M, Butchart SHM, Donald PF, and Rondinini C (2021) Translating habitat class to land cover to map area of habitat of terrestrial vertebrates. *Conservation Biology*, **In press**, DOI:10.1111/cobi.13851. Available at https://doi.org/10.1111/cobi.13851.

README.md

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+
+<!--- README.md is generated from README.Rmd. Please edit that file -->
+
+# Habitat classification data from Lumbierres *et al.* 2021
+
+[![lifecycle](https://img.shields.io/badge/Lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html)
+[![DOI](https://img.shields.io/badge/DOI-TODO-blue.svg)](https://doi.org/TODO)
+
+This repository contains code to generate global habitat classification
+data (based on Lumbierres *et al.* 2021). Specifically, source data are
+downloaded from the [Zenodo Digital
+Archive](https://doi.org/10.5281/zenodo.5146072), and then projected to
+the World Behrmann coordinate reference system using (100 m resolution;
+[ESRI:4326 coordinate reference system](https://epsg.io/54017)). A
+processed version of the data can be downloaded from the [Zenodo Digital
+Repository](https://zenodo.org/badge/latestdoi/TODO). **All credit
+should go to Lumbierres *et al.* (2021), please cite their work if you
+use this dataset.**
+
+<img src="figures/README-map-1.png" style="display: block; margin: auto;" />
+
+## Metadata
+
+The habitat classification data are stored in a raster (GeoTIFF) file.
+The file name contains the version number of the original datasets
+(i.e., per the digital object identifier). The latest version of the
+file is `lumbierres-10-5281_zenodo-5146073.tif`.
+
+The metadata for the `lumbierres-10-5281_zenodo-5146073.tif` raster file
+is shown below.
+
+    Driver: GTiff/GeoTIFF
+    Files: lumbierres-10-5281_zenodo-5146073.tif
+    Size is 347351, 132926
+    Coordinate System is:
+    PROJCRS["World_Behrmann",
+        BASEGEOGCRS["WGS 84",
+            DATUM["World Geodetic System 1984",
+                ELLIPSOID["WGS 84",6378137,298.257223563,
+                    LENGTHUNIT["metre",1]]],
+            PRIMEM["Greenwich",0,
+                ANGLEUNIT["degree",0.0174532925199433]],
+            ID["EPSG",4326]],
+        CONVERSION["Lambert Cylindrical Equal Area",
+            METHOD["Lambert Cylindrical Equal Area",
+                ID["EPSG",9835]],
+            PARAMETER["Latitude of 1st standard parallel",30,
+                ANGLEUNIT["degree",0.0174532925199433],
+                ID["EPSG",8823]],
+            PARAMETER["Longitude of natural origin",0,
+                ANGLEUNIT["degree",0.0174532925199433],
+                ID["EPSG",8802]],
+            PARAMETER["False easting",0,
+                LENGTHUNIT["metre",1],
+                ID["EPSG",8806]],
+            PARAMETER["False northing",0,
+                LENGTHUNIT["metre",1],
+                ID["EPSG",8807]]],
+        CS[Cartesian,2],
+            AXIS["easting",east,
+                ORDER[1],
+                LENGTHUNIT["metre",1,
+                    ID["EPSG",9001]]],
+            AXIS["northing",north,
+                ORDER[2],
+                LENGTHUNIT["metre",1,
+                    ID["EPSG",9001]]]]
+    Data axis to CRS axis mapping: 1,2
+    Origin = (-17367531.000000000000000,7287077.000000000000000)
+    Pixel Size = (100.000000000000000,-100.000000000000000)
+    Metadata:
+      AREA_OR_POINT=Area
+      TIFFTAG_SOFTWARE=GRASS GIS 7.8.5 with GDAL 3.0.4
+    Image Structure Metadata:
+      COMPRESSION=DEFLATE
+      INTERLEAVE=BAND
+    Corner Coordinates:
+    Upper Left  (-17367531.000, 7287077.000) (179d59'59.98"E, 83d 0'14.04"N)
+    Lower Left  (-17367531.000,-6005523.000) (179d59'59.98"E, 55d 0' 0.03"S)
+    Upper Right (17367569.000, 7287077.000) (179d59'58.56"W, 83d 0'14.04"N)
+    Lower Right (17367569.000,-6005523.000) (179d59'58.56"W, 55d 0' 0.03"S)
+    Center      (      19.000,  640777.000) (  0d 0' 0.71"E,  5d 1'44.75"N)
+    Band 1 Block=256x256 Type=Byte, ColorInterp=Gray
+      Description = habitat_CGLS
+      NoData Value=0
+      Metadata:
+        COLOR_TABLE_RULES_COUNT=1
+        COLOR_TABLE_RULE_RGB_0=0.000000e+00 1.200000e+02 255 255 255 150 123 0
+
+## Usage
+
+You can run the code to produce the dataset using the system command
+`make clean all`. After processing has successfully completed, the code
+will produce two raster (GeoTIFF) files in the `results` directory.
+
+## Software requirements
+
+Operating system
+
+-   Ubuntu (21.10) (300 Gb disk space available)
+
+Software
+
+-   GNU make (version 4.1)
+-   GDAL (version 3.2.2)
+-   R (version 4.1.1)
+
+System packages
+
+-   `gdal-bin`
+-   `libudunits2-dev`
+-   `libgdal-dev`
+-   `libgeos-dev`
+-   `libproj-dev`
+-   `libxml2-dev`
+-   `libssl-dev`
+
+## Citation
+
+This dataset was derived from Lumbierres *et al.* (2021). If you use
+this dataset, you should cite their work - they deserve all the credit!
+
+> Lumbierres, M (2021). *Map of habitat classes (Level 1) from the IUCN
+> Habitat.* Zenodo Digital Repository. Available at
+> <https://doi.org/10.5281/zenodo.5146072>.
+
+> Lumbierres M, Dahal PR, Di Marco M, Butchart SHM, Donald PF, and
+> Rondinini C (2021) Translating habitat class to land cover to map area
+> of habitat of terrestrial vertebrates. *Conservation Biology*, **In
+> press**, <DOI:10.1111/cobi.13851>. Available at
+> <https://doi.org/10.1111/cobi.13851>.

code/lumbierres-habitat-data.R

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+# Initialization
+## load packages
+library(aoh)
+library(raster)
+library(terra)
+library(sf)
+library(rappdirs)
+library(gdalUtilities)
+
+## set variables
+### set number of threads
+n_threads <- max(1, parallel::detectCores() - 2)
+
+### change this to where you want to save the inputs
+input_dir <- "inputs"
+
+### change this to where you want to save the outputs
+output_dir <- "results"
+
+### set version to process
+### note that latest_zenodo_version() fails for Zenodo archives that only have
+## one version, so here we manually specify the first version if it fails
+version <- try(
+  aoh:::latest_zenodo_version(
+    x = "10.5281/zenodo.5146072",
+    file = "habitat_CGLS.tiff"
+  ),
+  silent = TRUE
+)
+if (inherits(version, "try-error")) {
+ version <- "10.5281/zenodo.5146073"
+}
+
+# Preliminary processing
+## print version
+cli::cli_alert_info(paste0("Version: ", version))
+cli::cli_alert_info(paste0("GDAL_CACHEMAX: ", Sys.getenv("GDAL_CACHEMAX")))
+
+## download data
+raw_path <- aoh:::get_zenodo_data(
+  x = version,
+  dir = input_dir,
+  force = FALSE,
+  file = "habitat_CGLS.tiff"
+)
+
+## construct output path
+output_path <- gsub(
+  ".", "-", gsub("/", "_", version, fixed = TRUE), fixed = TRUE
+)
+output_path <- file.path(tempdir(), paste0("lumbierres-", output_path, ".tif"))
+output_path <- gsub("\\", "/", output_path, fixed = TRUE)
+
+# Main processing
+## import habitat data
+raw_data <- terra::rast(raw_path)
+
+## import elevation data
+elev_data <- get_global_elevation_data(
+  dir = rappdirs::user_data_dir("aoh"),
+  version = "latest",
+  force = FALSE,
+  verbose = TRUE
+)
+
+## project habitat data to match elevation data
+habitat_data <- aoh:::terra_gdal_project(
+  x = raw_data,
+  y = elev_data,
+  filename = output_path,
+  method = "near",
+  n_threads = n_threads,
+  datatype = "INT1U",
+  cache_limit = 5000,
+  tiled = TRUE,
+  bigtiff = TRUE,
+  compress = "DEFLATE",
+  NAflag = 0,
+  verbose = TRUE
+)
+
+## verification
+habitat_data <- terra::rast(output_path)
+assertthat::assert_that(
+  terra::compareGeom(habitat_data, elev_data, res = TRUE, stopiffalse = FALSE),
+  msg = "GDAL processing didn't work correctly"
+)
+
+# Finished
+message("Done!")

data/.gitkeep

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+