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Remote sensing of crop residue using hyperion (EO-1) data

The goal of this research was to investigate the potential of hyperspectral Hyperion (EO-1) data and constrained linear spectral unmixing analysis (CLSMA) for percent crop residue cover estimation and mapping. The Hyperion image data was acquired at the beginning of the agricultural season, May 20 2002, as well as ground reference measurements for validation purposes. In this period, there is mainly only the presence of bare soil and crop residue before any crop cover development. The image data were corrected for the sensor artifacts: a spatial misregistration between the VNIR and SWIR data, and striping, and, in addition, the noise was reduced. The data were atmospherically corrected and then transformed to surface reflectance and, subsequently, corrected for sensor smile/frown and post-processed to remove residual errors. In order to extract the crop residue fraction (percent cover), the image was unmixed using the pure spectra (endmember) collected in the field simultaneously with Hyperion data from different targets (dry and wet wheat residue, and bright and dark soil) with a GER-3700 spectroradiometer. In order to represent the existing trees and all the photosynthetically targets in the scene, a vegetation endmember was selected from our spectral library. Correlation between ground references measurements and extracted fractions from Hyperion data using CLSMA showed that the method satisfactorily predicts crop residues percent cover (D of 0.94, R2 of 0.73 and RMSE of 8.7%) and soil percent cover (D of 0.91, R2 of 0.70 and RMSE of 10.03%).