Spatial optimisation of Local Climate Zones in Kuala Lumpur for Surface Urban Heat Island mitigation using ResNet and Evolutionary Algorithms - Study Data

Land Use & Land Cover (LULC) optimisation is critical for mitigation of Urban Heat Island (UHI) effects. We use the Local Climate Zones (LCZ) classification system to optimise LULC as it has achieved very strong results in Surface UHI intensity (SUHII) modelling. two evolutionary algorithms are employed to minimise extreme SUHII in Greater Kuala Lumpur: Genetic Algorithm, and Particle Swarm Optimisation, with total population and GDP set as constraints that should not decrease. Eight local administrative areas LCZ spatial layouts’ were each optimised using a trained ResNet model as the objective function to simulate the resulting SUHII patterns. The process was repeated for 1500 iterations, providing an optimal LCZ spatial layout of each area using each algorithm. Genetic Algorithm results showed an average reduction in extreme SUHII of 2.75℃ and a total altered area of 18.2% of the total area, while Particle Swarm showed a slightly better reduction of 3.00℃ and a much smaller altered area of 7.7% indicating better efficiency. Biggest reduction in SUHII happened in Gombak whole the smallest reduction happened in Sepang. three-dimensional urban morphology blocks were generated based on the optimised LCZ layouts using a generative adversarial network illustrating the differences between the original and optimised layouts for two representative areas. These findings are instrumental to local governments with insights on where and how to modify land planning maps for a sustainable future vision focused on UHI mitigation.