2022 Global Land Cover Dataset (Adapted from GLC_FCS30D) - Dataset

Field	Value
Author	Natural Capital Project
Tags	LAND COVER LAND USE LAND COVER LULC
Places	GLOBAL
Last Updated	June 9, 2025, 22:04 (UTC)
Created	June 9, 2025, 22:04 (UTC)
Natcap Last Updated	2025-06-09T22:04:13.018465+00:00

Cite this dataset

Embed this layer into your website

<div id="map" style="width: 100%; height: 400px;"></div>

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<script src="https://unpkg.com/leaflet@1.9.4/dist/leaflet.js" integrity="sha256-20nQCchB9co0qIjJZRGuk2/Z9VM+kNiyxNV1lvTlZBo=" crossorigin=""></script>
<script>
  var map = L.map('map').setView([0, 0], 4);

  L.tileLayer('https://tile.openstreetmap.org/{z}/{x}/{y}.png', {
    attribution: '&copy; <a href="https://www.openstreetmap.org/copyright">OpenStreetMap</a> contributors'
  }).addTo(map);

L.tileLayer('https://titiler-897938321824.us-west1.run.app/cog/tiles/WebMercatorQuad/{z}/{x}/{y}@2x?colormap_name=viridis&bidx=1&url=https%3A%2F%2Fstorage.googleapis.com%2Fnatcap-data-cache%2Fnatcap-projects%2Flulc_glc_fcs30d%2Flulc_glc_fcs30d_2022_dh.tif&rescale=11.0%2C210.0').addTo(map);
</script>

Use this data in Python

from osgeo import gdal

raster = gdal.OpenEx('/vsicurl/https://storage.googleapis.com/natcap-data-cache/natcap-projects/lulc_glc_fcs30d/lulc_glc_fcs30d_2022_dh.tif')
band = raster.GetRasterBand(1)
array = band.ReadAsArray(
    xoff=my_window_x_offset,
    yoff=my_window_y_offset,
    win_xsize=my_window_width_in_pixels,
    win_ysize=my_window_height_in_pixels)