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The Bioindicators of Forest Condition Project: A physiological, remote sensing approach.

Authors :
Sampson, Paul H.
Mohammed, Gina H.
Zarco-Tejada, Pablo J.
Miller, John R.
Noland, Thomas L.
Irving, Denzil
Treitz, Paul M.
Colombo, Stephen J.
Freemantle, Jim
Source :
Forestry Chronicle; Nov/Dec2000, Vol. 76 Issue 6, p941, 12p, 1 Color Photograph, 1 Diagram, 2 Graphs
Publication Year :
2000

Abstract

Objective measures of forest ecosystem condition are needed to gauge the effects of management activities and natural phenomena on sustainability. The Bioindicators of Forest Condition Project seeks to develop a Forest Condition Rating (FCR) system using a physiological, remote sensing approach. In particular, the goal of the project is to test whether hyperspectral remote sensing may be used to infer stand-level information about pigment concentration, chlorophyll fluorescence, and other physiological features of condition. The project spans a four-year period of intensive sampling in tolerant hardwood forests in Ontario using the Compact Airborne Spectrographic Imager (CASI). For each airborne campaign, concurrent ground-based sampling for leaf physiological features was performed. Controlled laboratory and greenhouse studies were also conducted to derive relationships between leaf-based spectral measurements and physiology in the presence of environmental stresses. The project has identified several promising bioindicators of strain that are discernible from hyperspectral images and related to ground-based physiology. The most promising remote indicator for senti-operational testing is estimation of chlorophyll content, which can be used to classify maple stands on a five-stage scale of health. Chlorophyll fluorescence has also been discerned from spectral signatures, but our studies indicate it may be confounded by chlorophyll content. The intent here is to update the forestry community on progress made, insights gained, and the practical implications of the research. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
REMOTE sensing
FORESTS & forestry

Details

Language :
English
ISSN :
00157546
Volume :
76
Issue :
6
Database :
Supplemental Index
Journal :
Forestry Chronicle
Publication Type :
Academic Journal
Accession number :
8760008
Full Text :
https://doi.org/10.5558/tfc76941-6