Paper
1 September 1990 Large scale ecosystem modeling using parameters derived from imaging spectrometer data
Carol A. Wessman, Brian Curtiss, Susan L. Ustin
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Abstract
The capability to predict the response of ecosystems to change relies on our ability to understand and model the effective functioning of biotic processes at large scales and the transport functions of the atmospheric/hydrospheric processes. To successfully evaluate changes in ecological processes at the required spatial and temporal scales remote sensing technology and ecosystem theory must be considered jointly. A review of developments in remote sensing analysis using high spectral resolution sensors has led to the selection of a potential set ofparameters to be used in ecosystem models. These parameters quantify the light interception properties that scale from leaf to landscape. Spectral mixture analysis forms a framework for the systematic separation of both vegetative and non-vegetative components at sub-pixel spatial resolution. The spectral concentrations of the vegetative components defined by the spectral mixture analysis are then used to drive canopy radiative transfer models from which the ecosystem parameters are inferred. 1.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Carol A. Wessman, Brian Curtiss, and Susan L. Ustin "Large scale ecosystem modeling using parameters derived from imaging spectrometer data", Proc. SPIE 1298, Imaging Spectroscopy of the Terrestrial Environment, (1 September 1990); https://doi.org/10.1117/12.21347
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Cited by 5 scholarly publications.
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KEYWORDS
Ecosystems

Data modeling

Biological research

Atmospheric modeling

Process modeling

Sensors

Remote sensing

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