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- Title
Integrating spectral, spatial, and terrain variables for forest ecosystem classification
- Authors
Treitz, Paul; Howarth, Philip
- Abstract
Sets of spectral, spectral-spatial, textural, and geomorphometric variables derived from high spatial resolution Compact Airborne Spectrographic Imager (CASI) and elevation data are tested to determine their ability to discriminate landscape-scale forest ecosystem classes for a study area in northern Ontario, Canada. First, linear discriminant analysis for various spectral and spectral-spatial variables indicated that a spatial resolution of approximately 6 m was optimal for discriminating six landscape-scale forest ecosystem classes. Second, texture features, using second-order spatial statistics, significantly improved discrimination of the classes over the original reflectance data. Finally, addition of terrain descriptors improved discrimination of the six forest ecosystem classes. It has been demonstrated that,in a low- to moderate-relief boreal environment, addition of textural and terrain variables to high-resolution CASI reflectance data provides improved discrimination of forest ecosystem classes.
- Subjects
ONTARIO; CANADA; BIOTIC communities; FOREST ecology; REMOTE sensing
- Publication
Photogrammetric Engineering & Remote Sensing, 2000, Vol 66, Issue 3, p305
- ISSN
0099-1112
- Publication type
Article