Land surface temperature (LST) estimates often serve as urban heat islands maps and to infer human thermal comfort. Parallel to this, physiological heat balance calculations have been well documented to measure changes in body core temperature and measure risk of heat-related illness. However, there is a need for an improved spatially explicit method to assess human thermal comfort. Using spatial climate data measuring temperature, airflow, and humidity, we developed a geographic body heat storage (BHS) model based on heat exchange and evaporative heat loss from the human body. As proof of concept, we used heat-related illness emergency department visits in two Arizona metropolitan areas to demonstrate that BHS can improve LST's shortcomings, with its increased explanatory power of and linear fit to emergency records. The BHS model can support decision making for public health outcomes as heat risk increases with climate change and urban overheating to more closely approximate the human heat experience. BHS allows can be implemented in different climate regions and with investigations of additional physiological and community variables to better describe risk of heat-related illness.
