Paper
23 January 2001 Quantifying environmental change from high-resolution remotely sensed imagery using a composite ecosystem degradation index
Mark W. Jackson, John R. Jensen
Author Affiliations +
Abstract
The objective of this study was to evaluate environmental impacts surrounding a freshwater reservoir in South Carolina using landscape ecology pattern and structure metrics calculated from high-resolution optical/infrared imagery. In preparation for satellite-based studies using platforms such as SPOT-5, IRS-P5, Orbview 3 & 4, and Ikonos satelites, digital high-altitude color infrared (NAPP) and Airborne Terrestrial Applications Sensor (ATLAS) data were analyzed for a shoreline surrounding a freshwater reservoir in South Carolina subject to degradation from urban encroachment. An index was developed using a genetic learning neural network to mimic the impact rating given each section of the shoreline by experts in the field. It is hoped that this index can be extended on global scale by using high resolution satellites to allow for a standard index that would reduce the often subjective nature of shoreline degradation evaluations.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark W. Jackson and John R. Jensen "Quantifying environmental change from high-resolution remotely sensed imagery using a composite ecosystem degradation index", Proc. SPIE 4171, Remote Sensing for Agriculture, Ecosystems, and Hydrology II, (23 January 2001); https://doi.org/10.1117/12.413947
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Cited by 1 scholarly publication.
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KEYWORDS
Neural networks

Ecology

Ecosystems

Factor analysis

Environmental sensing

Genetics

Remote sensing

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