Energy crop mapping with enhanced TM/MODIS time series in the BCAP agricultural lands

摘要

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 estab-lished. 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 bio-mass 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. (C) 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.