Multi Study Crop Mask (NASA EOSDIS, 2016)

This Global Food Security-support Analysis Data (GFSAD) at nominal 1 km result from a collaborative effort by the National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS), to provide global cropland data that contributes towards global food security in the twenty-first century. GCE 1 km Multi-study Crop Mask provides cropland extent, irrigated vs. rainfed. Note that the spatial distribution of a disaggregated five class global cropland extent map derived at nominal 1 km based on four major studies: Thenkabail et al. (2009a, 2011), Pittman et al. (2010), Yu et al. (2013), and Friedl et al. (2010). Classes 1 to Class 5 are cropland classes that are dominated by irrigated and rainfed agriculture. Class 4 to and Class 5 have minor/very minor fractions of croplands. Irrigation major: areas irrigated by large reservoirs created by large and medium dams, barrages, and even large ground water pumping. Irrigation minor: areas irrigated by small reservoirs, irrigation tanks, open wells, and other minor irrigation. However, it is very hard to draw a strict boundary between major and minor irrigations and in places, there can be significant mixing. For example, major irrigated areas such as the Ganges basin, California’s central valley, Nile basin, and other major command areas (e.g, several major and medium reservoirs for the Krishna basin in India, numerous major and medium irrigation in China), are clearly distinguishable. Input data used in these various products include remote sensing (e.g., Landsat, MODIS, AVHRR, SPOT vegetation), secondary (e.g., elevation), climate (e.g., 50-year precipitation, 20-year temperature), reference (e.g., sub-meter to 5-m imagery, ground data), and statistics (e.g., country statistics) data were used.

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Additional Info

Field Value
Source https://app.mapx.org/static.html?views=MX-2XM0K-EX0F6-Q43N8&zoomToViews=true#JAAc6
Author UNEP/GRID-Geneva
Maintainer UNEP/GRID-Geneva
Last Updated December 7, 2022, 08:06 (UTC)
Created December 7, 2022, 08:06 (UTC)
GUID MX-2XM0K-EX0F6-Q43N8
Issued 2018-05-29 18:03:56
Language EN
Modified 2021-09-06 11:01:23
Publisher email info@mapx.org
Publisher name UNEP/GRID-Geneva
Theme Web Map
data_type geospatial
keywords_m49 WLD
projects_description NEAT+ Global
projects_id MX-WJO-FOV-NNB-1BN-SZN
projects_title NEAT+ Global
range_end_at_year 2021
range_start_at_year 2007
source_abstract This Global Food Security-support Analysis Data (GFSAD) at nominal 1 km result from a collaborative effort by the National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS), to provide global cropland data that contributes towards global food security in the twenty-first century. GCE 1 km Multi-study Crop Mask provides cropland extent, irrigated vs. rainfed. Note that the spatial distribution of a disaggregated five class global cropland extent map derived at nominal 1 km based on four major studies: Thenkabail et al. (2009a, 2011), Pittman et al. (2010), Yu et al. (2013), and Friedl et al. (2010). Classes 1 to Class 5 are cropland classes that are dominated by irrigated and rainfed agriculture. Class 4 to and Class 5 have minor/very minor fractions of croplands. Irrigation major: areas irrigated by large reservoirs created by large and medium dams, barrages, and even large ground water pumping. Irrigation minor: areas irrigated by small reservoirs, irrigation tanks, open wells, and other minor irrigation. However, it is very hard to draw a strict boundary between major and minor irrigations and in places, there can be significant mixing. For example, major irrigated areas such as the Ganges basin, California’s central valley, Nile basin, and other major command areas (e.g, several major and medium reservoirs for the Krishna basin in India, numerous major and medium irrigation in China), are clearly distinguishable. Input data used in these various products include remote sensing (e.g., Landsat, MODIS, AVHRR, SPOT vegetation), secondary (e.g., elevation), climate (e.g., 50-year precipitation, 20-year temperature), reference (e.g., sub-meter to 5-m imagery, ground data), and statistics (e.g., country statistics) data were used.
source_title Multi Study Crop Mask (NASA EOSDIS, 2016)
spatial WLD