UHI_Equity_Atlas_Submission

Background: Urban heat islands (UHIs) exacerbate climate-related risks, disproportionately affecting vulnerable populations. Traditional assessments focus on physical temperature patterns, often neglecting the social and demographic dimensions that shape exposure and adaptive capacity. This study introduces the Intelligent Urban Heat & Equity Atlas, a machine learning\u2013driven framework that integrates climatic, socioeconomic, and demographic data to assess vulnerability-adjusted heat risk across U.S. urbanized areas.Methods: We combined satellite-derived land surface temperature (LST) data with social vulnerability indicators from the CDC Social Vulnerability Index (SVI) and population data for 55,871 census tracts. Data preprocessing included cleaning, imputation, and normalization. Derived metrics \u2014 including a vulnerability-adjusted UHI (VA-UHI) and a Heat Exposure Equity Index (HEEI) \u2014 were calculated. Correlation analyses, categorical comparisons, and geospatial visualization were used to explore patterns of exposure and inequity.Results: VA-UHI revealed significantly higher exposure levels in socioeconomically disadvantaged communities, with strong correlations to poverty (r = 0.63) and minority population share (r = 0.65). Per-capita exposure varied by several orders of magnitude, and \u201cExtreme\u201d exposure areas exhibited vulnerability indices 1.7 times higher than \u201cLow\u201d exposure areas.Conclusions: Our results highlight the need for equity-centered adaptation strategies that prioritize communities where physical heat exposure intersects with social vulnerability. The Intelligent Urban Heat & Equity Atlas offers a scalable, data-driven tool to support targeted interventions, equitable resource allocation, and climate-resilient urban planning.