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

Content Provider	IEEE Xplore Digital Library
Author	Bannari, A. Staenz, K. Khurshid, K.S.
Copyright Year	2007
Description	Author affiliation: Univ. of Ottawa, Ottawa (Bannari, A.)
Abstract	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, $R^{2}$ of 0.73 and RMSE of 8.7%) and soil percent cover (D of 0.91, $R^{2}$ of 0.70 and RMSE of 10.03%).
Starting Page	2795
Ending Page	2799
File Size	483377
Page Count	5
File Format	PDF
ISBN	9781424412112
DOI	10.1109/IGARSS.2007.4423423
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-07-23
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Remote sensing Crops Soil measurements Data mining Hyperspectral sensors Hyperspectral imaging Spectral analysis Image sensors Noise reduction Reflectivity precision agriculture crop residue hyperspectral remote sensing Hyperion Soil and Erosion Unmixing
Content Type	Text
Resource Type	Article

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