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Data and code for remote spectral detection of biodiversity effects on forest biomass

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DataCite Commons2022-03-08 更新2025-04-09 收录
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http://hdl.handle.net/11299/215251
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资源简介:
Quantifying how biodiversity affects ecosystem functions through time over large spatial extents is needed to meet global biodiversity goals yet is infeasible with field-based approaches alone. Imaging spectroscopy is a tool with potential to help address this challenge. In this study, we demonstrated a spectral approach to assess biodiversity effects in young forests that provides insight into its underlying drivers and could potentially be applied at large spatial scales. Using airborne imaging (NASA AVIRIS-NG) of a tree diversity experiment (IDENT-Cloquet in Cloquet, MN), spectral differences among plots enabled us to quantify net biodiversity effects on stem biomass and canopy nitrogen. In this repository, we present the spectral data and field data along with spectral model coefficients and example code for fitting and applying spectral models to calculate spectral biodiversity effects.
提供机构:
Data Repository for the University of Minnesota (DRUM)
创建时间:
2020-09-04
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