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Dieback classification modelling using high-resolution digital multispectral imagery andin situassessments of crown condition

Evans, B., Lyons, T.J., Barber, P.A., Stone, C. and Hardy, G. (2012) Dieback classification modelling using high-resolution digital multispectral imagery andin situassessments of crown condition. Remote Sensing Letters, 3 (6). pp. 541-550.

Link to Published Version: http://dx.doi.org/10.1080/01431161.2011.639400
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Abstract

Quantifying dieback in forests is useful for land managers and decision makers seeking to explain spatial disturbances and understand the cyclic nature of forest health. Crown condition is assessed as reference to dieback in terms of the density, transparency, extent and in-crown distribution of foliage. At 20 sites in the Yalgorup National Park, Western Australia, a total of 80 Eucalyptus gomphocephala crowns were assessed both in situ (2008) and using two acquisitions (2008 and 2010) of airborne imagery. Each tree was assessed using four crown-condition indices: Crown Density, Foliage Transparency, the Crown Dieback Ratio and Epicormic Index combined into a single index called the Total Crown Health Index (TCHI). The airborne imagery is like value calibrated then classified and modelled using in situ canopy condition assessments resulting in a quantification of crown-condition change over time. Comparison of Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI) and a novel Red-Edge Extrema Index (REEI) suggests that the latter is more suited to classification applications of this type.

Publication Type: Journal Article
Murdoch Affiliation: Centre of Excellence for Climate Change and Forest and Woodland Health
School of Biological Sciences and Biotechnology
Publisher: Taylor & Francis
URI: http://researchrepository.murdoch.edu.au/id/eprint/8290
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