Area estimation of croplands is a challenge, made difficult by the variety of cropping systems, including crop types, management practices and field sizes. The goal of this project is to work towards a standard method for estimating cultivated crop area at the global sacle. Two approaches, one employing sampling and another mapping, will be examined for application at the global scale. The sampling method will use MODIS data to target crop type at national scales fors stratified sampling of higher spatial resolution data to estimate cultivated area. This method, given appropriate data for area estimation at the higher spatial resolution represents an efficient and accurate approach for large area crop type estimation. This approach will be tested for major projection countries. For example, 93% of soybean cultivation is found within 5 countries: the United States, Argentina, Brazil, China and INdia. MODIS indicator mapping and high-spatial resolution samples can be applied annually at national scales for these countries to provide an internally consistent, satellite-based area estimation of global soybean cultivated area. The second approach will involve developing a method for cropland area estimation at the global scale. This approach is meant to be generic and to exploit the recently opened EROS Landsat archive. Time-series Landsat data will be analyzed to develop a generic multi-temporal signature for cropland identification. The method will be tested for a number of global sites in conjuction with the Joint Experiment on Crop Assessment and Monitoring (JECAM) of the GEOSS activity.