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UBC Theses and Dissertations

Assessing and analyzing urban tree condition using airborne remote sensing Plowright, Andrew Alexander


Though urban forests play a key role in the sustainable development of cities, the environmental stressors faced by urban trees are numerous. City managers rarely have access to information on the condition of urban trees, which impedes both their management and the study of environmental factors that affect their vitality, such as landscape imperviousness. The research presented in this thesis aims to bridge this gap in information. The capacity of airborne light detection and ranging (LiDAR) and hyperspectral imagery to evaluate tree condition in the city of Surrey, British Columbia, Canada, is explored, and its relationship with impervious land cover is investigated. LiDAR was used to estimate two indicators of tree condition: crown density and tree height. Tree heights estimated by LiDAR were well correlated with field measurements (Pearson’s r = 0.927, p < 0.001), while the coefficient of variation of return height was able to predict crown density with an r2 = 0.617 for trees over 8 m. The heights of 1,914 trees across the city were then estimated using LiDAR. To account for the effects of age, species-specific height models were fitted using planting dates recorded by city authorities. The residuals from these models were then used as indicators of tree condition. A 1.0 m resolution classified land cover map (accuracy of 88.6%) was produced for the city, from which landscape imperviousness was then derived. When aggregated to broad-scale 0.5 km2 spatial units, negative relationships (r2 between 0.292 and 0.753) were found between height model residuals and land cover imperviousness. However, this relationship was found to be non-significant when examined at the individual tree level. We conclude that imperviousness does not appear to be a significant driver of tree height variation, with negative broad-scale relationships likely due to correlations with other unmeasured environmental variables associated with the urban-rural gradient. Hyperspectral and LiDAR data proved to be a powerful tool for mapping land cover and imperviousness. The results of this research show that airborne remote sensing is a promising tool for assessing the condition of urban trees and studying the environmental factors that impact their development.

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