Spatiotemporal Dynamics of Air Pollution and Its Linkages with Land Use and Surface Temperature Using GIS and Remote Sensing: A Case Study of Dehradun, India

Abstract

Urbanization and industrial expansion have significantly altered land use and land cover (LULC) patterns, leading to de- teriorating air quality and rising land surface temperatures (LST), particularly in rapidly growing cities. This study investigates the spa- tiotemporal dynamics of air pollutants nitrogen dioxide (NO₂), carbon monoxide (CO), formaldehyde (HCHO), and tropospheric ozone (O₃) in relation to LULC changes and LST variations in Dehradun, India, between 2003 and 2023. Multi-temporal satellite datasets from Landsat and TROPOMI sensors were integrated with geospatial techniques to assess urban expansion, pollutant distribution, and surface thermal regimes. The key innovation of this study lies in the integrated multi-source framework combining long-term satellite observa- tions, ground-based validation, and advanced statistical techniques (Mann-Kendall test, Sen’s slope, and Principal Component Analysis) to comprehensively evaluate both trends and driving mechanisms of air pollution. Additionally, the study uniquely links seasonal vari- ability, urban expansion, and thermal characteristics (LST) with pollutant behavior, providing a holistic understanding of urban envi- ronmental dynamics in a Himalayan foothill region. The findings reveal a significant increase in built-up areas (by approximately 204%) and a corresponding decline in vegetation cover, resulting in elevated LST across the district. Spatial analyses show a strong association between densely built-up zones and higher concentrations of NO₂ and CO, while seasonal variability further accentuates pollutant accu- mulation, particularly during winter months. The study also demonstrates a positive correlation between impervious surface area and pollutant concentration, highlighting the role of LULC transitions in exacerbating urban environmental stress. The results underscore the utility of remote sensing and GIS in air quality monitoring and provide critical insights for sustainable urban planning and mitigation strategies in ecologically sensitive regions like the Himalayan foothills.

Keywords: air pollution, urban spaces, LULC, Climate Action (SDG 13), LST, formaldehyde, NO₂, CO, O₃