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This Integrated Systems Solution project responds directly to the national priority application of agricultural efficiency. Specifically, the project employs innovative approaches to integrate Earth Science results to improve the timeliness and accuracy of the acreage estimation decision support system (DSS) run by USDA's National Agricultural Statistics Service (NASS). This will be achieved by incorporating data from the MODIS (MODerate Resolution Imaging Spectroradiometer) sensors on the Terra and Aqua spacecrafts and applying MODIS Land Science Team cover characterization methods and products to fulfill the goals of the NASS-DSS. Time-series MODIS data have the potential to improve current NASS crop classification capabilities in numerous ways, including the abilities to implement operational crop type characterizations, to produce crop cover products at earlier dates than currently possible, and to be integrated into higher spatial resolution data streams in a fusion approach. The NASS-DSS currently delivers Cropland Data Layers (CDL) and acreage indications of major commodities per state and county from multitemporal Indian Remote Sensing Advanced Wide Field Sensor (AWiFS) data calibrated by training data from the USDA/Farm Service Agency¿s Common Land Unit (CLU) vector data sets. An intercomparison of the current AWiFS/CLU trained methodology will be made with four alternative products: MODIS operational crop type maps, MODIS/CLU trained maps, integrated MODIS/AWiFS/CLU trained maps and MODIS-normalized AWiFS/CLU trained maps. Successful completion of the project will provide a necessary proof of concept for the use of remotely sensed data in a highly sensitive and extremely important operational environment by meeting the scope, timeliness, accuracy, and dependability required at the national level. Improvements in these areas will enhance a host of public, private and civil society decisions and applications worldwide that rely upon accurate and timely U.S. agricultural data.