A Comparative Analysis of Global Cropping Systems Models and Maps
Abstract
Agricultural practices have dramatically altered the land cover of the Earth, but the spatial extent and intensity of these practices is often difficult to catalogue. Cropland accounts for nearly 15 million km2 of the Earth's land cover - amounting to 12% of the Earth's ice-free land surface - yet information on the distribution and performance of specific crops is often available only through national or sub-national statistics. While 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, there have been 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 cropss for the year 2000. While 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 monthly irrigated and rainfed crop areas around the year 2000 (MIRAC2000) dataset, the spatial production allocation model (SPAM), the global agro-ecological zone (GAEZ) dataset, and the dataset developed by Monfreda et al., 2008. 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.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2013
- Bibcode:
- 2013AGUFM.B41A0386A
- Keywords:
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- 0434 BIOGEOSCIENCES Data sets;
- 0466 BIOGEOSCIENCES Modeling;
- 0402 BIOGEOSCIENCES Agricultural systems;
- 0480 BIOGEOSCIENCES Remote sensing