Operational Prediction of Crop Yields Using Modis Data and Products

Official crop progress, condition and production estimates for the United States are responsibilities of the U.S. Department of Agriculture’s, National Agricultural Statistics Service (NASS). In addition to weekly and monthly survey-based data, biweekly composite maps of the normalized difference vegetation index (NDVI) from the NOAA AVHRR sensor (1 km resolution) are produced by NASS’s Research and Development Division (RDD) for monitoring vegetative change. This provides a qualitative assessment of differences in crop condition that may be an indication of potential yields. There is need for a more quantitative assessment of crop yields and spatial variability. Currently, NASS acquires crop yield indications via ground-based sample surveys (objective plant and fruit counts, fruit weights and farmer reports) which are collectively used to develop tools for its decision support system to assess weekly crop progress, monthly crop yield estimates for each state and the U.S, and annual county yield estimates. This paper describes the joint research between RDD and the Agricultural Research Service (ARS) of USDA for the development of simplified process models and algorithms to supplement the NASS field data collection. Potential advantages to using remote sensing include integration of spatial variability into county yields, enhanced timeliness, and efficient use of resources. In the preliminary phase, MODIS data and products for the states of Iowa and Illinois were used to develop an operational assessment of crop yield forecasts for corn and soybeans. Spatial estimates of crop yields at county and sub-county levels offer a major improvement of current capabilities. The timeliness in producing these estimates is a vast improvement over the present assessment capability at the county level. Potential use of the estimates will supplement current tools and improve NASS’ crop condition and yield decisions. Results of the pre-harvest forecasts developed for the 2005 and 2006 crop seasons are presented.