Aspen Bibliography

Title

Integrating spectral, spatial, and terrain variables for forest ecosystem classification

Document Type

Article

Journal/Book Title/Conference

Photogrammetric Engineering and Remote Sensing

Volume

66

Issue

3

First Page

305

Last Page

317

Publication Date

2000

Abstract

Sets of spectral, spectral-spatial, textural, and geomor- phometric variables derived fram 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-scaleforest ecosystem classes. Second, texture features, using second-order spatial statistics, significantly improved discrimination of the classes over the originalreflectance 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 discrim- ination of forest ecosystem classes.