Assessment of Crown Condition in Eucalypt Vegetation by Remotely Sensed Optical Indices

Abstract

Leaf and crown damage and discoloration characteristics are important variables when defining the health of eucalypt tree species and have been used as key indicators of environmental quality. These indicators can vary significantly over a few hectares, especially in mixed-species forests, making field-based environmental surveillance of crown condition an extremely expensive and logistically impractical task. Reflectance in narrow spectral wavelengths obtained from a field-based spectroradiometer and a Compact Airborne Spectrographic Imager 2 (CASI-2) were collected over eucalypt vegetation of varying condition in southeastern Australia and compared with leaf- and crown-based attributes including percent red foliage discoloration, percent leaf damage, and crown density and crown foliage condition. Of the leaf attributes sampled, percent leaf damage was well correlated with a red-green spectral index (r = 0.68, p < 0.01), and percent red discoloration was well correlated with the slope of the red-edge for selected species (r = 0.89, p < 0.001). Within-tree crown density was well correlated with the slope of the red-edge (r = 0.77, p < 0.001) and a previously published index of plant stress with crown foliage condition (r = 0.88, p < 0.01) for selected species. Despite evidence of strong interspecific variability, a set of narrow spectral wavelengths in the visible and near-infrared regions of the spectrum have been identified that will be useful in the development of forest ecosystem environmental quality indicators.

Crown‐scale evaluation of spectral indices for defoliated and discoloured eucalypts

“…It had a significant and strong relationship with percentage total leaf cover for E. grandis (table 4) but not for E. pilularis (table 3). Coops et al (2004) found that the slope of the total red edge was more strongly correlated to crown density than the lower red edge slope for some native eucalypt species, to a degree which is similar to results found here with E. grandis for correlation with total leaf cover (table 4). In our study of E. pilularis the lower red edge slope was not significantly different for stressed and healthy plants nor was it correlated to the percentage leaf cover data (table 3).…”

“…Curran (1990) found no relationship between the red edge and chlorophyll content of whole canopies, due to the influence of understorey vegetation. However, Coops et al (2004) found that the RE T and RE ls were well correlated with crown density when individual tree crowns were delineated in high resolution imagery and the reflectance data extracted for analysis. This agrees with results found here for E. globulus as the RE ls and RE T were very strongly correlated with leaf cover, as was the REP.…”

Remote Sensing and Reflectance Profiling in Entomology

“…That is, leaf reflectance profiles acquired with hand spectrometers or ground-based hyperspectral imaging cameras may vary from those obtained with airborne remote sensing systems (24,53,130,151). Such differences are attributed to a range of factors, including atmosphere, shadow pattern, background composition, and instrument noise (24).…”

“…Numerous methods have been used to classify entomological remote sensing data, including analysis of reflectance values of single spectral bands (93,98), spectral band indices (17,24,79,85,90,95), partial least square (PLS) (2,4,63), principal component analysis (PCA) (90,102), linear discriminant analysis (LDA) (94), decision trees (37), neural network (73), support vector machine (SVM) (111), variogram analysis (90-93, 95, 97, 100), and spatial pattern analysis (5-7). Sometimes reflectance values of spectral bands are transformed prior to classification, and the most common transformations include conversions of reflectance profiles into first-or second-order derivatives (26).…”

Enhancing a eucalypt crown condition indicator driven by high spatial and spectral resolution remote sensing imagery

“…[15][16][17] Land Monitor II, a Landsat-based vegetation trend product has been demonstrated to be useful in monitoring vegetation changes over time. 18,19 However, the spatial resolution (30 m) of the Landsat Thematic Mapper (TM) sensor limits the capacity to detect individual tree crowns and in-crown foliage variability.…”