Modeling the spatial relation between urban morphology, land surface temperature and urban energy demand

Considering climate change and energy resource depletion under rapid urbanization trends in the urban environment, the relation between land-use, climate change, and urban energy demand is gaining attention. However, a limited number of studies are focusing on the effect of microclimate change, and more specifically, temperature change on energy demand at an urban scale. This study includes empirical spatial and temporal modeling to identify how urban morphology indicators (UMIs), land surface temperature (LST), and neighboring land-use compositions affect urban energy demand using an extensive data set for the case study of Eindhoven, the Netherlands. For this purpose, the ordinary least square regression (OLS) and geographically weighted regression (GWR) models are employed. The results show, there is a significant spatial relation between UMIs, neighboring land-use compositions, and urban energy demand. Furthermore, the impact of dwelling types on urban energy demand is discussed. The results can be applied to sustainable urban planning targeting energy reduction, climate adaptation, and help local authorities for implementing energy management strategies.