Optimizing building spatial morphology to alleviate human thermal stress

Achieving urban cooling from a sustainable perspective requires strategic planning of building area (S) and height (H). However, there is a lack of human thermal stress assessment and it is not clear how to optimize the layout of building spatial morphology to alleviate human thermal stress. We simulated the Universal Thermal Climate Index (UTCI), a high spatial resolution human comfort data, by machine learning, and analyzed the relationship between building spatial morphology and UTCI to determine the feasible layout of building spatial morphology. Our findings indicate that the study area experiences poor human thermal comfort, with residents facing higher thermal stress (average UTCI of 36°C). Zoning analysis reveals that an increase in S results in a simultaneous rise in UTCI, while an increase in H leads to a trend in UTCI that initially rises and then declines. An increase in S-rating has a more pronounced impact on elevating UTCI (0.29°C on average) compared to an increase in H-rating (0.11°C on average). To maintain UTCI within the UTCI threshold that characterizes ideal human comfort, a trade-off relationship between S and H should generally be maintained. It is influenced by the stationary and plunge intervals in the relationship curve between the two. The findings have the potential to provide valuable insights for policymakers and stakeholders, aiding them in making more informed decisions in urban planning to alleviate human thermal stress.