Spatiotemporal dynamics of urbanisation induced environmental quality in arid city using a grid-based analysis in Jodhpur India from 2001 to 2021

Rapid urbanisation in arid regions intensifies heat exposure, vegetation loss, and particulate pollution, yet medium-sized desert cities remain underrepresented in integrated environmental assessments. We quantified spatiotemporal changes in environmental quality in Jodhpur, India, from 2001 to 2021 using a novel grid-based Environmental Quality Index (EQI). Methodological innovation lies in three elements: incorporation of nighttime land surface temperature (LST) to capture urban heat retention relevant to population exposure; application of a uniform 32-grid intra-urban framework to detect micro-spatial heterogeneity; and integration of satellite-derived PM 2.5 with vegetation–thermal dynamics using a geometric mean to minimise compensatory bias. Indicators, LST (land degradation), NDVI-derived vegetation cover (ecosystem regulation), and PM 2.5 (atmospheric quality), were selected for direct biophysical relevance, long-term satellite consistency, and exposure sensitivity, rather than proxy measures such as built-up indices or population density. Annual MODIS, Landsat, and satellite model fused PM 2.5 datasets (1 km) were standardised (0–100); trends were analysed using Mann–Kendall and Sen’s slope estimators; interrelationships were assessed via multiple linear regression. Land-use classification from Landsat achieved > 85% overall accuracy. Seventy-one percent of grids showed significant nighttime warming ( p < 0·05), with hotspots reaching + 1·36 °C. Core urban areas recorded vegetation decline (mean ΔVC − 0·02), whereas peri-urban grids showed moderate greening (ΔVC up to + 0·07). Mean PM 2.5 ranged 4–7 μg/m 3 and was strongly associated with vegetation loss (R 2 = 0·66) and elevated LST (R 2 = 0·49). The proportion of city area classified as poor or very poor EQI increased from 15·1% (2001) to 41·5% (2021). Vegetation decline was the dominant predictor of PM 2.5 increase (β = − 0·44; p = 0·01). These findings indicate substantial environmental deterioration and provide a scalable framework for climate-resilient urban planning in arid cities.