Energy crop mapping with enhanced TM/MODIS time series in the BCAP agricultural lands
Abstract Since the mid-2000s, agricultural lands in the United States have been undergoing rapid change to meet the increasing bioenergy demand. In 2009 the USDA Biomass Crop Assistance Program (BCAP) was established. In its Project Area 1, land owners are financially supported to grow perennial prairie grasses (switchgrass) in their row-crop lands. To promote the program, this study tested the feasibility of biomass crop mapping based on unique timings of crop development. With a previously published data fusion algorithm - the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), a 10-day normalized difference vegetation index (NDVI) time series in 2007 was established by fusing MODIS reflectance into TM image series. Two critical dates - peak growing (PG) and peak drying (PD) - were extracted and a unique “PG-0-PD” timing sequence was defined for each crop. With a knowledge-based decision tree approach, the classification of enhanced TM/MODIS time series reached an overall accuracy of 76% against the USDA Crop Data layer (CDL). Especially, our results showed that winter wheat single cropping and wheat-soybean double cropping were much better classified, which may provide additional information for the CDL product. More importantly, this study extracted the first spatial layer of warm-season prairie grasses that have not been published in any national land cover products, which could serve as a base map for decision making of bioenergy land use in BCAP land.
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