Discriminating Cropping Patterns for the U.s. Central Great Plains Region Using Time-series Modis 250-meter Ndvi Data – Preliminary Results

Agricultural practices are continually changing at various spatial and temporal scales in response to local management decisions and environmental factors. However, few regional scale land use/land cover (LULC) classifications have focused on characterizing the agricultural sector, particularly on a regular basis to reflect croprelated land use changes that occur from year to year. More detailed and timely LULC data sets are needed for the Central Great Plains region to better understand the role and consequences of cropping practices on climate change issues that potentially threaten the region’s long-term agriculturally sustainability. Time-series MODIS (Moderate Resolution Imaging Spectroradiometer) 250-meter NDVI (Normalized Difference Vegetation Index) was evaluated to determine if major crop types (alfalfa, corn, sorghum, soybeans, and winter wheat) and crop-related land use practices (irrigation, fallow, and double cropping) in the Central Great Plains could be discriminated based on spectral-temporal differences. Median time-series NDVI curves were calculated for each crop class based on hundreds of field sites and the class’ curves were compared for spectral-temporal differences. Specific crop types and irrigated and non-irrigated crops were discriminated based on differences in their median NDVI curves. Fallow, wheat-summer fallow, and double cropping practices were also identified based on their unique spectral-temporal characteristics. Regional differences in median NDVI curves were found for individual crop types. These regional curves appear to be related to differences in annual precipitation, growing season length, and planting dates. Timeseries MODIS’ 250-meter data appears to have the spatial, spectral, and temporal resolutions necessary to characterize relatively detailed regional-scale cropping practices on a repetitive basis.