Thesis or dissertation
Date of this Version
Urban tree inventories typically require extensive field work for data collection, but a new software tool has been developed to remotely determine an urban forest’s features using publicly available online images. In this study, tree planting records from UC Green were processed for current features and environmental impacts using only remote data collection and data management tools. Trees in the organization’s planting record were first located geographically, identified by genus and species, and then algorithmically measured for diameter. After aggregating and verifying fifteen years of bi-annual planting records and processing them with the remote tools, the full record was entered into a live database to facilitate monitoring and maintenance, and then analyzed for its provision of ecosystem services. Out of 1485 street trees confirmed planted by the nonprofit, 1232 were found to be presently living with the most common species being Syringa reticulata (Japanese tree lilac), Acer rubrum (red maple), and Gleditsia triacanthos (Honey locust). Some key impacts of this work were determining the size and scope of the nonprofit’s planting accomplishments, as well as estimated ecosystem services, and the facilitation of future monitoring and planting operational performance assessment. The impacts of the UC Green’s tree plantings can be increased further as operations are augmented according to the suggested recommendations, which were based on the study’s results.
Urban Forestry, Tree Inventory, Remote Data Collection, Street-level imagery
Date Posted:26 January 2020