Monitoring tree canopy dynamics across heterogeneous urban habitats: A longitudinal study using multi-source remote
1Department of Geography, The University of Hong Kong, Hong Kong, China.
Abstract:
Urban trees have attracted increasing attention to serve as a green prescription for addressing various challenges facing human society like climate change and environmental deterioration. However, without healthy growth of urban trees, they cannot service any environmental, social, and economic benefits in a sustainable manner. By monitoring the canopy development, the tree growth dynamics in different urban habitats can be detected and appropriate management approaches can be executed. Using the Kowloon Peninsula, Hong Kong, as a case, this study explores how remote sensing data can help monitor and understand the impacts of heterogeneous urban habitats on tree canopy dynamics. Four algorithms based on WorldView-2 satellite image are compared to optimize the canopy segmentation. Then the individual tree canopy is integrated with Sentinel-2 satellite data to obtain canopy growth dynamics for each season from 2016 to 2020. Three indicators are applied to reflect tree canopy status, including the fluorescence correction vegetation index (FCVI, tracking leaf chlorophyll density), the soil adjusted total vegetation index (SATVI, measuring the density of woody branches and twigs), and the normalised difference phenology index (NDPI, capturing canopy water content). And four heterogeneous habitats where urban trees stand are specified. The results revealed that urban trees show varying canopy growth status, in a descending order from natural terrains, parks, residential lands, to road verges, suggesting that urban habitats curtail trees' growth significantly. Additionally, two super-typhoons in 2017 and 2018, respectively, caused serious damages to tree canopy. Relevant resiliency of tree varies, echoing the sequence of canopy growth status with those in road verges the least resilient. This study shows how remote sensing data can be used to provide a better understanding of long-term tree canopy dynamics across large-scale heterogeneous urban habitats, which is key to monitoring and maintaining the health and growth of urban trees.
