Strategic tree placement for urban cooling: A novel optimisation approach for desired microclimate outcomes

Abstract

Trees are crucial elements for improving urban microclimates by providing cooling through shading, evapotranspiration, and windbreaks. To maximise their cooling effects, it is essential to strategically position the trees in optimal locations. However, research on optimising tree location and its impact on microclimates is limited owing to computational challenges and costs. This study introduces a novel method that employs three optimisation algorithms—i.e., Non-dominated Sorting Genetic Algorithm II (NSGA-II), Particle Swarm Optimisation (PSO), and Ant Colony Optimisation (ACO)—to identify the optimal locations for trees in urban environments to enhance urban thermal comfort. The research methodology involves simulating microclimate responses to tree placements optimised by each algorithm and assessing the results based on urban thermal comfort. The results underscore the efficacy of optimised tree locations, demonstrating that optimising tree locations can significantly reduce the Universal Thermal Comfort Index (UTCI) in urban areas. Furthermore, the findings suggest that the clustering of tree canopies has a compounding impact on these cooling benefits in urban areas. Notably, all three algorithms significantly improved UTCI. PSO demonstrated the rapid identification of effective tree configurations. However, ACO provided the most substantial reduction in air temperature, highlighting its potential as an effective tool for urban cooling. While efficient, NSGA-II plateaued earlier, suggesting its utility in scenarios where timely solutions are crucial.