Global Food Security-Support Analysis Data at 30 m (GFSAD)

The spatial distribution of global cropland areas (~1.5 billion hectares) and five dominant crop types (wheat, rice, maize, barley and soybeans). This composite map was produced by Thenkabail and Gumma through spatial modeling involving remote sensing derived global irrigated and rainfed croplands (Thenkabail et al., 2011, 2009a, 2009b) and five dominant global crop types from other sources (Ramankutty et al. (2008), Monfreda et al. (2008), and Portman et al. (2009)). The 5 crops constitute about 60% of all global cropland areas. 

Cover page credits: Dr. Prasad S. Thenkabail, U.S. Geological Survey (USGS) and Dr. Murali Krishna Gumma, International Rice Research Institute (IRRI) with inputs from the USGS Powell Center working group on global croplands (WGGC) team members (http://powellcenter.usgs.gov/current_projects.php#GlobalCroplandMembers). For more information contact: pthenkabail@usgs.gov or thenkabail@gmail.com. The image was produced for the PE&RS Special issue on global croplands, Vol. 78, No.8; August 2012

Global cropland water use. Country-wise agricultural crop water use in km3/yr. In India, China, and Pakistan as a result of double and triple cropping that are irrigated, the water use is dominated by irrigated croplands (blue water use). In USA, the water use is dominated by rainfed croplands (green water use). Data source: Gleick (2011).

Hyperspectral signature bank of world’s major crops. The initial goal of a global cropland monitoring system should consist of developing hyperspectral signature bank of major world crops (e.g., this figure) along with crop phonologies (e.g., Figure 4) in order to: (a) establish improved models of crop biophysical and biochemical quantities, (b) increase crop classification accuracies, and (c) produce accurate crop and water productivity models. The six leading world crops (Table 1) cover 64% of the global cropland areas. Sample hyperspectral signatures of these six World crops are illustrated in the figure. The background image is irrigated and rainfed croplands of the world (Thenkabail et al., 2009a, 2009b, 2011).

Rice map of South Asia. Crop phenologies and intensities studied using time-series remotely sensed data illustrated for rice crop in South Asia. A clear and deep understanding of phenologies and intensities will require us to develop a temporal (e.g., this figure) and spectral knowledge base of each crop in different agro-ecosystems of the world leading to mapping distinct classes within a crop, which in turn will lead to accurate assessments of green water use (rainfed croplands) and blue water use (irrigated croplands).

Global croplands and other land use and land cover. This baseline product is derived based on AVHRR time-series, SPOT Vegetation, and a number of secondary data by using the Data published by Thenkabail et al. (2009, 2011; see publications).  [Credits: Prasad Thenkabail and Zhuoting Wu].

Key global cropland area products that will support food security analysis in the twenty-first century. [Credits: GFSAD30 project team]

An aggregated three class global cropland extent map 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). Class 1 is total cropland extent based on pixels with 100% cropland cover (2.3 billion hectares). Class2 and Class3 have minor fractions of croplands.

A disaggregated twelve 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 1-9 are cropland classes and show the dominance of irrigated and rainfed agriculture. Classes 10-12 have minor/very minor fractions of croplands.

Center image of global cropland (irrigated and rainfed) areas @ 1 km for year 2000 produced by overlying the remote sensing derived product of the International Water Management Institute (IWMI; Thenkabail et al., 2012, 2011, 2009a, 2009b; http://www.iwmigiam.org) over 5 dominant crops (wheat, rice, maize, barley and soybeans) of the world produced by Ramankutty et al. (2008). The 5 crops constitute about 60% of all global cropland areas. The IWMI remote sensing product is derived using remotely sensed data fusion (e.g., NOAA AVHRR, SPOT VGT, JERS SAR), secondary data (e.g., elevation, temperature, and precipitation), and in-situ data. Total area of croplands is 1.53 billion hectares of which 399 million hectares is total area available for irrigation (without considering cropping intensity) and 467 million hectares is annualized irrigated areas (considering cropping intensity). Surrounding NDVI images of irrigated areas: The January to December irrigated area NDVI dynamics is produced using NOAA AVHRR NDVI. The irrigated areas were determined by Thenkabail et al. (2011, 2009a, b).

Global agricultural dynamics over 2 decades (1982-2000) illustrated here for some of the most significant agricultural areas of the World. The baseline data is the global irrigated and rainfed croplands of the world for nominal year 2000 produced by Thenkabail et al. (2012). The time-series graphics is derived from AVHRR 8-km NDVI monthly data from 1982-2000.

Available field data points from various sources. The IWMI, Gumma, and Thenkabail collections are collected by this team or the former teams as in publications Thenkabail et al. (2009, 2011). These have detailed ground data at every point with coordinates, photos, and land cover types. The Geo_wiki_validation, Geo_wiki_competetion, and USAID_Project collections are sourced from various people from around the world as part of the Geo-Wiki Project (www.geo-wiki.org) which aims to improve the quality of global land cover maps. The project is currently adding more data through field visits during the period of the project as well as data sourced from various sources. (Credits for organizing the data: Mutlu Ozdogan and Matthew Bougie).

Disclaimer: This data, compiled from various sources, is not for distribution at this stage. When we decide to disseminate this, that will be done through this website.