Title of article :
Determining Forest Structural Attributes Using an Inverted Geometric-Optical Model in Mixed Eucalypt Forests, Southeast Queensland, Australia
Author/Authors :
Scarth، نويسنده , , Peter and Phinn، نويسنده , , Stuart، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2000
Pages :
17
From page :
141
To page :
157
Abstract :
The Montreal Process indicators are intended to provide a common framework for assessing and reviewing progress toward sustainable forest management. The potential of a combined geometrical-optical/spectral mixture analysis model was assessed for mapping the Montreal Process age class and successional stage indicators at a regional scale using Landsat Thematic Mapper data. The project location is an area of eucalyptus forest in Emu Creek State Forest, Southeast Queensland, Australia. A quantitative model relating the spectral reflectance of a forest to the illumination geometry, slope, and aspect of the terrain surface and the size, shape, and density of the trees was developed. In the model estimates were derived for crown cover projection, tree density, and canopy size. Inversion of this model necessitated the use of spectral mixture analysis to recover subpixel information on the fractional extent of ground scene elements (such as sunlit canopy, shaded canopy, sunlit background, and shaded background). Results obtained from a sensitivity analysis allowed improved allocation of resources to maximize the predictive accuracy of the model. It was found that modeled estimates of crown cover projection, canopy size, and tree densities had significant agreement with field and air photo-interpreted estimates. However, the accuracy of the successional stage classification was limited. The results obtained highlight the potential for future integration of high and moderate spatial resolution-imaging sensors for monitoring forest structure and condition.
Journal title :
Remote Sensing of Environment
Serial Year :
2000
Journal title :
Remote Sensing of Environment
Record number :
1573209
Link To Document :
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