A Comparative Analysis of Global Cropping Systems Models and Maps
44 Pages Posted: 26 Mar 2014
Date Written: February 1, 2014
Agricultural practices have dramatically altered the Earth’s land cover, but the spatial extent and intensity of these practices is often difficult to catalogue. Cropland accounts for nearly 15 million square kilometers of Earth’s land cover — amounting to 12 percent of the planet’s ice-free land surface — yet information on the distribution and performance of specific crops is often available only through national or subnational statistics. Although remote-sensing products offer spatially disaggregated information, those currently available on a global scale are ill suited for many applications due to the limited separation of crop types within the area classified as cropland. Recently, however, the field has seen multiple independent efforts to incorporate the detailed information available from statistical surveys with supplemental spatial information to produce a spatially explicit global dataset specific to individual crops for the year 2000. Although these datasets provide analysts and decision makers with improved information on global cropping systems, the final global cropping maps differ from one another substantially. This study aims to explore and quantify systematic similarities and differences between four major global cropping systems products: the dataset of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000), the spatial production allocation model (SPAM), the global agroecological zone (GAEZ) dataset, and the M3 dataset developed by Monfreda, Ramankutty, and Foley. The analysis explores not only the final cropping systems maps but also the interdependencies of each product, methodological differences, and modeling assumptions, which will provide users with information vital for discerning between datasets in selecting a product appropriate for each intended application.
Keywords: farmland, cropping systems, yield, cartography, global cropland, harvested area, downscaling
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