Simpler Spatial Model for Hyperlocal Mapping of Urban Tree Canopy Cover

Abstract

Climate change cause challenges and increased risks in cities, necessitating urgent adaptation without leading to path-dependency. Therefore, nature-based approaches are gaining attention where urban trees hold great potential by providing climate-regulating ecosystem services. However, available hyperlocal geodata and maps on urban tree canopy (UTC) cover are currently insufficient and promising AI-based mapping approaches are often complex and require special skills. Together, that pose challenges specifically for small cities that often hold fewer resources.

This study demonstrates for the smaller Danish city, Randers, how UTC cover effectively can be mapped from Danish geodata using simple GIS-techniques as a simpler alternative to AI-based models. The developed model shows promising performance with high geospatial accuracy, thus providing valuable spatial information and local UTC baselines communicated visually through maps.