Global surface temperatures are projected to escalate in intensity, duration, and frequency, particularly in urban areas, which are dominated by landscapes of imperviousness, accelerating the Urban Heat Island Phenomena (UHI). Geographies of thermal inequality emerge engendered by disproportionality in socioeconomic and demographic characteristics and variances in the magnitude of heat exposure. This study integrated the biophysical exposure index and the socioeconomic index to generate composite heat vulnerability indices at multiple time scales and applying different weighting mechanics. Outputs of the raster-based and vector-based approaches were compared. Remote sensing indices measuring vegetation health, surface water content, urban imperviousness, and bareness were used to characterize the biophysical metric. The objective was to visualize areas most susceptible accurately and precisely to the Urban Heat Island phenomena while ensuring both scientific and policy applications of the spatial representations.