Multi-objective method of selecting performance-based local climatic zones using binomial logistic regression in warm and humid climate

Urban agglomeration is a serious concern due to its high energy usage and impact on the local climate. Developing countries strive to determine the development path to optimize energy usage. The present study aims to examine the local climatic zones (LCZs) performance in warm and humid climate through a multi-objective approach for the residential sector. The performance is assessed by evaluating the urban microclimate and cooling load consumption for both summer and winter months using binomial logistic regression. The study concludes that LCZ $2_3$ (compact mid-rise with open low-rise) and LCZ $6_B$ (open low-rise with scattered trees) perform better for 80% and 50% of total hours in warm and humid climate. It also proves the presence of significant performance differences between mid-rise and low-rise zones. The intra-zonal differences between the climatic variables are higher than the inter-zonal differences due to the impact of land surface temperature (LST). The high aspect ratio and low sky view factor of LCZ $2_3$ help the residents in that morphology in enhancing better thermal comfort and reducing cooling load consumption. The present study contributes to building regulation policymakers by providing information on the suitable morphology for warm and humid climate.