Date
September 5-6, 2023
Submitted to
The Fourth Spatial Data Science Symposium
Author
David Pedley
Supervisors
Dr Justin Morgenroth (UC) and Dr Grant Pearse (Scion)
Abstract
Urban trees provide a multitude of environmental and amenity benefits for city occupants. In recognition of these benefits, many cities have developed strategies and plans seeking to protect and increase tree canopy cover. However, such objectives are in potential conflict with the housing needs of growing populations, with a recent emphasis on intensification to increase the density of housing within existing urban areas. The overall objective of this research is to evaluate the relationship between residential housing intensification and changes in urban tree cover in Christchurch, New Zealand between 2015 and 2021. The first stage of the research will test the potential for deep learning to detect changes in canopy cover over time using high resolution aerial imagery and LiDAR data, with a particular focus on private residential land. The outputs will be utilised to evaluate the relationship between recent urban intensification and observed tree loss, including an analysis of differing forms and densities of intensification. The latter stages of this research will employ a variety of methods to assess whether tree loss has been offset by new planting on public and private land and evaluate whether regulation is an effective approach for protecting urban trees from housing intensification.
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