Skip to main content

Description

The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Food Security-support Analysis Data (GFSAD) data product provides cropland extent data over South Asia, Afghanistan, and Iran for nominal year 2015 at 30 meter resolution (GFSAD30SAAFGIRCE). The monitoring of global cropland extent is critical for policymaking and provides important baseline data that are used in many agricultural cropland studies pertaining to water sustainability and food security. The GFSAD30SAAFGIRCE data product uses the pixel-based supervised classifier, Random Forest (RF), to retrieve cropland extent from a combination of Landsat 8 Operational Land Imager (OLI) and elevation derived from the Shuttle Radar Topography Mission (SRTM) Version 3 data products. Each GFSAD30SAAFGIRCE GeoTIFF file contains a cropland extent layer that defines areas of cropland, non-cropland, and water bodies over a 10° by 10° area.

Known Issues

  • Known issues, including constraints and limitations, are provided on page 18 of the ATBD.

Product Summary

Platforms
LANDSAT-8 ,
LANDSAT-7 ,
DEM ,
LANDSAT-5
Instruments
OLI ,
ETM+ ,
TM
Spatial Extent

N: 40.10861 S: -10.038404 E: 100.001086 W: 39.998656

Spatial Resolution
30 Meters x 30 Meters
Location
AFGHANISTAN ,
IRAN ,
SOUTHERN ASIA
Coordinate System
CARTESIAN
Granule Spatial Representation
CARTESIAN
Temporal Extent
2013-01-01 to 2016-06-30
Temporal Resolution
4 Year
Data Partner
Land Processes Distributed Active Archive Center (LP DAAC) ,
Western Geographic Science Center, U.S. Geological Survey, U.S. Department of the Interior (DOI/USGS/WGSC)
Concept ID
C2763261689-LPCLOUD
Data State
COMPLETE
Number of Files/Granules
18
Processing Level
3
Published
Updated
Science Keywords
Crop/Plant Yields ,
Land Use Classes ,
Landscape Patterns ,
Cropland

Citation

Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.

Copy Citation

Gumma, M., Thenkabail, P., Teluguntla, P., Oliphant, A., Xiong, J., Congalton, R., Yadav, K., Phalke, A., & Smith, C. (2017). NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Food Security-support Analysis Data (GFSAD) Cropland Extent 2015 South Asia, Afghanistan, Iran 30 m V001 [Data set]. NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/MEASURES/GFSAD/GFSAD30SAAFGIRCE.001 Date Accessed: 2026-05-02

File Naming Convention

GFSAD30SAAFGIRCE_2015_N20E70_001_2017286103800.tif

File name begins with Product Short Name (GFSAD30SAAFGIRCE) followed by the Year of Acquisition (2015), the latitude and longitude of the lower left corner of the tile (N20E70), Version (001), Julian Date and Time of Processing as YYYYDDDHHMMSS (2017286103800), and the Data Format (tif).

Documents

Publications Citing This Dataset

Filters
Title Year Author Topic
Agricultural plastics as marine pollutants: Empirical evidence from inland and coastal field surveys Morales-Caselles, Carmen, Viejo, Josue, Montero, Enrique, Cozar, Andres Crop/Plant Yields, Land Use Classes, Landscape Patterns, Cropland
A new two-decade (20012019) high-resolution agricultural primary productivity dataset for India Gangopadhyay, Prasun K., Shirsath, Paresh B., Dadhwal, Vinay K., Aggarwal, Pramod K. Reflectance, Photosynthesis, Primary Production, VEGETATION PRODUCTIVITY, Crop/Plant Yields, Land Use Classes, Landscape Patterns, Cropland
Multiple agricultural cropland products of South Asia developed using Landsat-8 30 m and MODIS 250 m data using machine learning on the Google Earth Engine ... Gumma, Murali Krishna, Thenkabail, Prasad S, Panjala, Pranay, Teluguntla, Pardhasaradhi, Yamano, Takashi, Mohammed, Ismail Crop/Plant Yields, Land Use Classes, Landscape Patterns, Cropland
Global food-security-support-analysis data at 30-m resolution (GFSAD30) cropland-extent productsDownload Analysis Oliphant, Adam, Thenkabail, Prasad, Teluguntla, Pardhasaradhi Crop/Plant Yields, Land Use Classes, Landscape Patterns, Cropland, Vegetation Cover
A statistical evaluation of Earth-observation-based composite drought indices for a localized assessment of agricultural drought in Pakistan Schwartz, Caily, Ellenburg, W. Lee, Mishra, Vikalp, Mayer, Timothy, Griffin, Robert, Qamer, Faisal, Matin, Mir, Tadesse, Tsegaye Crop/Plant Yields, Land Use Classes, Landscape Patterns, Cropland
Global Cropland-Extent Product at 30-m Resolution (GCEP30) Derived from Landsat Satellite Time-Series Data for the Year 2015 Using Multiple Machine-Learning Algorithms on Google Earth Engine Cloud Thenkabail, Prasad S., Teluguntla, Pardhasaradhi G., Xiong, Jun, Oliphant, Adam, Congalton, Russell G., Ozdogan, Mutlu, Gumma, Murali Krishna, Tilton, James C., Giri, Chandra, Milesi, Cristina, Phalke, Aparna, Massey, Richard, Yadav, Kamini, Sankey, Temuulen, Zhong, Ying, Aneece, Itiya, Foley, Daniel Crop/Plant Yields, Land Use Classes, Landscape Patterns, Cropland, Terrain Elevation, Digital Elevation/Terrain Model (DEM), Topographical Relief Maps, Vegetation Cover
Croplands intensify regional and global warming according to satellite observations Zhou, Decheng, Xiao, Jingfeng, Frolking, Steve, Liu, Shuguang, Zhang, Liangxia, Cui, Yaoping, Zhou, Guoyi Crop/Plant Yields, Land Use Classes, Landscape Patterns, Cropland, Vegetation Cover
A new framework to map fine resolution cropping intensity across the globeAlgorithm, validation, and implication Liu, Chong, Zhang, Qi, Tao, Shiqi, Qi, Jiaguo, Ding, Mingjun, Guan, Qihui, Wu, Bingfang, Zhang, Miao, Nabil, Mohsen, Tian, Fuyou, Zeng, Hongwei, Zhang, Ning, Bavuudorj, Ganbat, Rukundo, Emmanuel, Liu, Wenjun, Bofana, Jose, Beyene, Awetahegn Niguse, Elnashar, Abdelrazek Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Crop/Plant Yields, Land Use Classes, Landscape Patterns, Cropland, Plant Phenology
Mapping crop types in southeast India with smartphone crowdsourcing and deep learning Wang, Sherrie, Di Tommaso, Stefania, Faulkner, Joey, Friedel, Thomas, Kennepohl, Alexander, Strey, Rob, Lobell, David B. Crop/Plant Yields, Land Use Classes, Landscape Patterns, Cropland
A Phenology-Based Method to Map Cropping Patterns under a Wheat-Maize Liu, Jianhong, Zhu, Wenquan, Atzberger, Clement, Zhao, Anzhou, Pan, Yaozhong, Huang, Xin Crop/Plant Yields, Land Use Classes, Landscape Patterns, Cropland
You're viewing 10 of 10

Variables

The table below lists the variables contained within a single granule for this dataset. Variables often contain observed or derived geophysical measurements collected from a variety of sources, including remote sensing instruments on satellite and airborne platforms, field campaigns, in situ measurements, and model outputs. The terms variable, parameter, scientific data set, layer, and band have been used across NASA’s Earth science disciplines; however, variable is the designated nomenclature in NASA’s Common Metadata Repository (CMR). Variable metadata attributes such as Name, Description, Units, Data Type, Fill Value, Valid Range, and Scale Factor allow users to efficiently process and analyze the data. The full range of attributes may not be applicable to all variables. Additional information on variable attributes is typically available in the data, user guide, and/or other product documentation.

For questions on a specific variable, please use the Earthdata Forum.

Name Description Units Data Type Fill Value Valid Range Scale Factor Offset
Band 1 Cropland Extent for South Asia, Afghanistan, and Iran defined with three classes N/A uint8 N/A 0 to 2 N/A N/A
You're viewing 1 of 1