From green to gray: economic ramifications of vegetation loss and pollution in a growing urban landscape

Urban expansion and environmental degradation in arid regions pose significant challenges for sustainable development and public health. This study presents a comprehensive spatiotemporal analysis of air quality, vegetation dynamics, and land surface temperature (LST) patterns in Quetta district, Balochistan, Pakistan, using multi-temporal remote sensing data from 2016 to 2023. We employed Landsat-8 OLI/TIRS and Sentinel-5P TROPOMI datasets to extract key environmental indicators, including Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI), LST, and atmospheric pollutants (CO, NO 2 , SO 2 ). Land use/land cover (LULC) classification revealed distinct spatial patterns with built-up areas concentrated in the central region, while bare ground dominated the landscape across all study years. Correlation analysis demonstrated strong positive relationships between vegetation indices (NDVI-EVI: r=0.88-0.92) and negative correlations between vegetation and temperature (NDVI-LST: r=-0.61 to -0.73). Air pollutant concentrations showed temporal variations, with NO 2 exhibiting the highest spatial variability, particularly in urban areas. The study reveals critical environmental trends in this water-stressed region, providing valuable insights for urban planning, environmental management, and climate adaptation strategies in arid landscapes.