Surface Urban Heat Island Dynamics in Urban Regeneration Areas: A Multi-Temporal Remote Sensing Analysis of Istanbul, Türkiye

Urban regeneration interventions extend beyond the renewal of physical building stock and the improvement of living conditions, as they also reshape local microclimatic conditions. This study examines changes in Surface Urban Heat Island (SUHI) patterns within an urban regeneration area in Istanbul, Türkiye, using multi-temporal remote sensing data. Landsat imagery from 2019, 2020, 2022, and 2023 was used to derive Land Surface Temperature (LST), the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Built-up Index (NDBI), and SUHI intensity. Pearson correlation analysis, Getis–Ord Gi* hot spot analysis, and zonal statistics were applied to evaluate statistical relationships, spatial clustering, and local thermal changes within the regeneration areas. The findings show that urban regeneration did not produce a uniform thermal response. Demolition reduced built-up intensity, whereas redevelopment of previously vegetated or open parcels increased impervious surface cover and limited vegetation recovery. Correlation results revealed strong negative associations between NDVI and both LST and SUHI, while NDBI was positively associated with these thermal variables, indicating that land-cover composition was strongly associated with local thermal conditions. Overall, the study demonstrates that renewing building stock alone may not be sufficient to ensure improvement in the urban thermal environment. Strengthening green infrastructure, expanding permeable surfaces, and embedding climate-responsive planning measures into regeneration strategies are therefore critical. The results also indicate that multi-temporal remote sensing, combined with spatial statistics and zonal assessment, provides an effective decision-support framework for monitoring SUHI dynamics and evaluating the environmental performance of urban regeneration initiatives.