I had never thought about modeling tree canopy volume in 3D before. I’ve played around with simple algorithms to place trees on a map, assume a mature canopy area per tree, and estimate the total canopy area. This is useful because cities sometimes set targets and metrics in terms of number of trees, and sometimes in terms of tree canopy. The latter is better because it is more relatable to other goals a city might have related to the hydrologic cycle, carbon, heat, air quality, aesthetics and property values, biodiversity and habitat, and the financial cost to public offers of achieving these goals. Once you have an algorithm relating number of trees to canopy area, you can add more variables like type of tree, growth over time, and some assumed attrition rate or half life. Come to think of it, I have played around with leaf area index which is a quasi-3D concept. Anyway, without further ado here is the article that prompted my line of thought:

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 meters and that a one degree temperature reduction is predicted for an increase of 60,000 m3 tree canopy volume in this 40 meter 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.