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UBC Theses and Dissertations
Mapping the distributions of two invasive plant species in urban areas with advanced remote sensing data Chance, Curtis Matthew
Invasive plants are increasingly present in ecosystems, producing both positive and negative effects. Proactive management of plant invasions is critical to curbing their spreads, especially in urban areas which often act as centres of invasions. Therefore, municipalities require new tools to map invasions for both management and information. Remote sensing technologies provide opportunities to detect plant invasions over large areas at fine spatial resolutions. In Surrey, British Columbia, Canada, Himalayan blackberry (HB; Rubus armeniacus) and English ivy (EI; Hedera helix) are two understory invasive plants that can negatively influence native ecosystems and harm users of urban natural areas. Two remote sensing technologies, hyperspectral imagery and light detection and ranging (LiDAR) data, were utilized to map these two species across the entire area of Surrey. Analysis of spectral characteristics of HB and EI were used with hyperspectral imagery to examine the feasibility of spectrally detecting these species. Spectra were obtained from a ground-based handheld spectrometer from the two species and other common species in Surrey and processed through a spectral channel selection algorithm to identify key wavelengths for distinguishing these species. Once identified, a spectral classification routine used these wavelengths and training plots to detect HB and EI across open areas in Surrey. Results showed accuracies of 76.4% for HB and 80.0% for EI. Mapping HB and EI across all land covers of Surrey required detecting the two species in forested areas. Field plots, LiDAR-derived topographic and forest structure variables, hyperspectral data, a land cover classification, and a LiDAR-derived irradiance model were all used as inputs into random forest models to detect the species across the entire land base. Model accuracies ranged from 77.8% to 87.8%. Open areas were classified better than forested areas. EI was found more across the city than HB. The research in the thesis has advanced detection of invasive plants by demonstrating the feasibility of mapping understory invasions of EI and HB in urban areas at fine spatial resolutions and can form the basis for a future monitoring system using data acquired at regular intervals. Future work is recommended to enhance data collection and increase map specificity.
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