Determining forest structural attributes using an inverted geometric-optical model in mixed eucalypt forests, Southeast Queensland, Australia

Scarth, P. and Phinn, S. R. (2000) Determining forest structural attributes using an inverted geometric-optical model in mixed eucalypt forests, Southeast Queensland, Australia. Remote Sensing of Environment, 71 2: 141-157. doi:10.1016/S0034-4257(99)00066-8


Author Scarth, P.
Phinn, S. R.
Title Determining forest structural attributes using an inverted geometric-optical model in mixed eucalypt forests, Southeast Queensland, Australia
Journal name Remote Sensing of Environment   Check publisher's open access policy
ISSN 0034-4257
Publication date 2000-02-01
Year available 2000
Sub-type Article (original research)
DOI 10.1016/S0034-4257(99)00066-8
Open Access Status DOI
Volume 71
Issue 2
Start page 141
End page 157
Total pages 17
Place of publication New York, USA
Publisher Elsevier
Language eng
Subject C1
291003 Photogrammetry and Remote Sensing
779902 Land and water management
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 age indicators at a regional scale using Landsat Thematic 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, 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 fron 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. (C) Elsevier Science Inc., 2000.
Keyword Environmental Sciences
Remote Sensing
Imaging Science & Photographic Technology
Bidirectional Reflectance
Vegetation Structure
Canopy
Imagery
Woodlands
Q-Index Code C1
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
School of Architecture Publications
 
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Created: Mon, 13 Aug 2007, 21:35:19 EST