Spatio-temporal dynamics and mitigation of urban heat Islands: a case study of Jaipur

Abstract

Urban Heat Islands (UHIs) represent a critical challenge for rapidly urbanizing cities, where impervious surfaces and built-environment morphology trap and re-emit solar energy, driving surface and air temperatures above those of surrounding rural areas. This thesis investigates the spatio-temporal dynamics of both Surface UHI (SUHI) and Atmospheric UHI (AUHI) within Jaipur Municipal Corporation (JMC) from 2000 to 2024, identifies current and projected hotspots for 2030 and 2035, and evaluates the efficacy of targeted mitigation strategies at neighborhood scales. A comprehensive suite of land cover, urban morphology, and climatic variables was assembled: Landsat-derived LULC, NDVI, NDWI, NDMI, albedo, emissivity, Land Surface Temperature (LST); Global Human Settlement Layer (GHSL) building and population densities; sky view factor and Normalized Difference Built-up Index (NDBI); and IMD-sourced air temperature, relative humidity, wind speed/direction, and solar irradiation. Google Earth Engine facilitated retrieval and trend analysis of these raster and tabular datasets at five representative weather station locations. Spatio-temporal trends reveal a range of surface temperatures (30.4 °C to 60.5 °C) and air temperatures (28.4 °C to 51.3 °C) over the 24-year period, with highly urbanized wards (e.g., Transport Nagar) exhibiting the steepest increases. A Random Forest Regression model—trained on 80% of data and tested on 20%—demonstrated strong predictive performance (R² = 0.806; RMSE = 0.059), enabling projection of UHI intensity for 2030 and 2035. Hotspot analysis identifies Wards 88 (Transport Nagar) and 111 (Budhsinghpura/Airport) as persistent high-intensity zones in both SUHI and AUHI. Mitigation scenarios were simulated at the neighborhood level using ENVI-Met: green roofs, increased tree canopy, and optimized parking layouts reduced peak daytime SUHI by up to 3 °C in the densest wards, with synergistic benefits for nocturnal cooling and wind flow enhancement. Key findings underscore the primacy of built-environment factors—building density, impervious surface fraction, and sky view factor—in driving localized heat retention, while vegetation indices and albedo modulate cooling potential. Scenario simulations illustrate that strategic urban greening and reflective surfaces can measurably attenuate UHI intensity, informing design guidelines for Jaipur’s Development Control Regulations. The integration of spatio-temporal modeling with microclimate simulation offers a transferable framework for UHI assessment and mitigation in other fast-growing cities. This research contributes to urban planning policy by furnishing data-driven insights into UHI formation, equipping stakeholders with predictive tools, and demonstrating the efficacy of neighborhood-scale interventions to enhance thermal comfort, public health, and climate resilience in Jaipur’s urban core. Keywords: Urban Heat Island (UHI), Spatio-Temporal Analysis, Random Forest Regression, Microclimate Simulation (ENVI-Met), Mitigation Strategies