Local impact of tree volume on nocturnal urban heat island: A case study in Amsterdam

The aim of this research is to quantify the local impacts of tree volumes on the nocturnal urban heat island intensity (UHI). Volume of each individual tree is estimated through a 3D tree model dataset derived from LIDAR data and modelled with geospatial technology. Air temperature is measured on 103 different locations of the city on a relatively warm summer night. We tested an empirical model, using multi-linear regression analysis, to explain the contribution of tree volume to UHI while also taking into account urbanization degree and sky view factor at each location. We also explored the scale effect by testing variant radii for the aggregated tree volume to uncover the highest impact on UHI. The results of this study indicate that, in our case study area, tree volume has the highest impact on UHI within 40 m and that a one degree temperature reduction is predicted for an increase of 60,000 m3 tree canopy volume in this 40 m buffer. In addition, we present how geospatial technology is used in automating data extraction procedures to enable scalability (data availability for large extents) for efficient analysis of the UHI relation with urban elements.