Rapid urbanisation has intensified the Urban Heat Island (UHI) effect in Indian metropolitan cities, exacerbating environmental and thermal stress. This study investigates the spatiotemporal dynamics and key drivers of UHI in Bengaluru Urban District, India, from 2017 to 2023 using satellite-derived environmental and socio-economic indicators. Land Surface Temperature (LST) was analysed in relation to the Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Normalized Difference Water Index (NDWI), night-time light intensity, PM₂.₅ concentration, and population density to assess urban–rural thermal contrasts and seasonal variability. Pearson correlation analysis was employed to examine relationships between LST and the explanatory variables, while Principal Component Analysis (PCA) was used to identify the dominant factors influencing UHI patterns. Multiple Linear Regression (MLR) models were developed separately for winter and summer seasons to quantify the relative contribution of selected variables to surface temperature variations. The results reveal a consistently strong negative relationship between LST and both NDVI and NDWI, confirming the cooling influence of vegetation cover and surface moisture. In contrast, NDBI and night-time light intensity exhibit strong positive correlations with LST, underscoring the role of built-up surfaces and urban activity in heat accumulation. Seasonal analysis indicates that these relationships are more pronounced during summer, with a clear intensification of UHI observed in recent years. Overall, the study demonstrates that land-cover characteristics are the primary determinants of UHI intensity in Bengaluru. The findings highlight the urgent need for climate-sensitive urban planning, including the expansion of green and blue infrastructure and the adoption of nature-based solutions, to mitigate urban heat stress and enhance long-term urban sustainability.
K et al. (2026) studied this question.