Remote sensing of biodiversity: Soil correction and data dimension reduction methods improve assessment of α-diversity (species richness) in prairie ecosystems

@inproceedings{Gholizadeh2018RemoteSO,
  title={Remote sensing of biodiversity: Soil correction and data dimension reduction methods improve assessment of α-diversity (species richness) in prairie ecosystems},
  author={Hamed Gholizadeh and John A. Gamon and Arthur I. Zygielbaum and Ran Wang and Anna K. Schweiger and Jeannine Cavender-Bares},
  year={2018}
}
Abstract Hyperspectral data, with their detailed spectral information at different wavelengths, offer multiple ways to assess biodiversity. One approach, known as the “spectral variation hypothesis” (SVH), proposes that biodiversity is linked to spectral diversity. However, SVH-based approaches, which we refer to as “spectral diversity metrics”, can be confounded by soil exposure and are sensitive to the spatial resolution of the data. To address these issues, we 1) investigated the impact of… CONTINUE READING
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