Dieback classification modelling using high-resolution digital multispectral imagery and in situ assessments of crown condition

Quantifying dieback in forests is useful for land managers and decision makersseeking to explain spatial disturbances and understand the cyclic nature of for-est health. Crown condition is assessed as reference to dieback in terms of thedensity, transparency, extent and in-crown distribution of foliage. At 20 sites inthe Yalgorup National Park, Western Australia, a total of 80 Eucalyptus gompho-cephala crowns were assessed both in situ (2008) and using two acquisitions (2008and 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 modelledusing in situ canopy condition assessments resulting in a quantification of crown-condition change over time. Comparison of Normalized Difference VegetationIndex (NDVI), Soil-Adjusted Vegetation Index (SAVI) and a novel Red-EdgeExtrema Index (REEI) suggests that the latter is more suited to classificationapplications of this type.