Locating trees to mitigate outdoor radiant load of humans in urban areas using a metaheuristic hill climbing algorithm – Introducing TreePlanter v1.0

Abstract. Mean radiant temperature (Tmrt) is a frequently-used measure of outdoor radiant heat conditions. Excessive Tmrt, linked especially to clear and warm days, have negative effect on human well-being. Highest Tmrt on such days is found in sunlit areas, whereas shaded areas have significantly lower values. One way of alleviating high Tmrt is by planting trees to provide shade in exposed areas. To achieve the most efficient mitigation of excessive Tmrt by tree shade with multiple trees requires optimized positioning of the trees, which is a computationally extensive procedure. By utilizing metaheuristics, calculations can be reduced. Here, we present TreePlanter v1.0, which applies a metaheuristic hill climbing algorithm on input raster data of Tmrt and shadow patterns to position trees in complex urban areas. The hill climbing algorithm enables dynamic exploration of the input data to position trees, compared with very computationally demanding brute-force calculations. The results show that the algorithm, in relatively low model runtime, can find positions for several trees simultaneously that lowers Tmrt substantially. TreePlanter can assist in future research on optimization of tree planting in urban areas to increase thermal comfort. The current version can only position trees of equal tree characteristics (tree height, tree canopy and trunk height). Expected developments include positioning of trees with different tree characteristics.