Practical limits on hyperspectral vegetation discrimination in arid and semiarid environments

@inproceedings{Okina2001PracticalLO,
  title={Practical limits on hyperspectral vegetation discrimination in arid and semiarid environments},
  author={Gregory S. Okina and Dar A. Robertsb and Bruce Murraya and William J. Okinb},
  year={2001}
}
  • Gregory S. Okina, Dar A. Robertsb, +1 author William J. Okinb
  • Published 2001
Hyperspectral remote sensing is a promising tool for the analysis of vegetation and soils in remote sensing imagery. The purpose of this study is to ascertain how well hyperspectral remote sensing data can retrieve vegetation cover, vegetation type, and soil type in areas of low vegetation cover. We use multiple endmember spectral mixture analysis (MESMA), high-quality field spectra, and AVIRIS data to determine how well full-range spectral mixture analysis (SMA) techniques can retrieve… CONTINUE READING
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