Mapping heat vulnerability in Esenler, Istanbul using equal and entropy weighting: A multi-dimensional GIS approach

Urban heat vulnerability is an emerging challenge for rapidly densifying cities, where socioeconomic inequalities intersect with physical exposure.This study assesses neighborhoodlevel heat vulnerability in Esenler District, Istanbul, by integrating environmental and socio-demographic indicators within a composite Heat Vulnerability Index (HVI).Using satellite-derived indicators, including Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-up Index (NDBI), combined with socio-economic and adaptive capacity measures, the analysis applies both Equal Weighting and Entropy Weighting Methods to evaluate spatial variability and methodological robustness.Results reveal significant intra-district disparities, with HVI values ranging from 0.15 to 0.69 (Δ = 0.54).The majority of neighborhoods (15 of 17) fall within the high-vulnerability category, representing approximately 96% of the population, while only one neighborhood exhibits low vulnerability and one shows moderate vulnerability.The strong correlation (r = 0.94) between Equal and Entropy-weighted results confirms the index's methodological stability.Spatial clustering of high vulnerability in central Esenler underscores how dense urban morphology and social disadvantage co-produce climatic risk.This study addresses a critical gap in Istanbul's urban climate literature by providing one of the first data-driven, neighborhood-scale HVI applications.A Heat Vulnerability-Adaptive Capacity matrix translates results into a neighborhood-level prioritization scheme, identifying critical hotspots (N3, N7, N10) for immediate adaptation.Integrating entropy-based weighting enhances the interpretation of diverse environmental and social datasets, offering a replicable model for other contexts.The results emphasize targeted adaptation measures such as expanding green infrastructure, improving thermal comfort, and prioritizing vulnerable communities.