Simulation-Based Optimization of the Urban Thermal Environment through Local Climate Zones Reorganization in Changsha City, China with the FLUS Model

Urbanization leads to changes in surface landscapes, such as the increase in built-up areas and the decrease in natural elements, resulting in local changes in land surface temperature, which often create unusually hot weather and affect livability, especially for mid- and low-latitude cities. Therefore, optimizing urban landscapes and adjusting the thermal environment is especially important to improve comfort and to achieve sustainable urban development. Existing studies on optimizing landscapes have considered mainly horizontal land uses/land covers but ignored their elevation. This study considered local climate zones as basic units to describe three-dimensional landscapes; we measured the relationship between local climate zones and land surface temperature, based on which the research further used a genetic algorithm and future land-use simulation models to optimize the spatial layouts of local climate zones in Changsha, China, considering multiple objectives including adjusting land surface temperature without affecting population carrying capacity, economic development, watershed protection, and forest and grass protection. According to the optimization results, the area of open low-rise buildings increased by 5.98% after optimization, and dense trees decreased by 7.64%; open low-rise buildings were suggested to be newly built in the city center and sparsely buildings should be developed in the surrounding administrative district far away from the city center. The optimization results contributed to a −5.2 °C reduction of average land surface temperature, which could significantly improve the thermal environment under the premise of ensuring the population and economic development levels and thus serves as a novel solution for improving urban landscapes to implement sustainable city development.