Spatiotemporal Analysis of Urban Heat Island and Air Pollution Interactions across Indian Cities Using Multi-Source Remote Sensing Observations and Regression Model

Rapid urbanization, industrial growth, and increasing energy consumption across India have intensified the combined impacts of air pollution and urban heat, posing significant challenges to environmental sustainability and public health. Despite growing concerns across major cities of India, the spatial relationship between atmospheric pollutants and Urban Heat Island (UHI) intensity remains inadequately understood. This study investigates the association of UHI and pollution indices across major urban and industrial regions of India using multi-source satellite observations and spatial regression analysis. Several atmospheric pollutant products from TROPOMI and Land Surface Temperature (LST) datasets were utilized during 2004-2025 to characterize its spatiotemporal variability of air quality and urban heat index. The analysis identified persistent thermal and pollution hotspots over highly urbanized and industrialized regions in India, with elevated summer surface temperatures and increased UHI effects. CO and NO₂ exhibited the strongest positive relationship with UHI intensity, indicating that combustion-related emissions from transportation, industrial activities, and energy production. Methane (CH₄) and the UV Aerosol Index showed moderate associations with thermal conditions, whereas ozone (O₃) and sulfur dioxide (SO₂) displayed comparatively weaker and spatially heterogeneous relationships influenced by secondary atmospheric processes and localized emission sources. Geographically Weighted Regression (GWR) is applied to investigate the spatial variability in understanding pollutant-temperature interactions. This study highlights the potential of satellite remote sensing and spatial modeling for supporting sustainable urban planning and climate-resilient environmental management in India.