Modeling Impact of Urbanization on Land Surface Temperature and Assessment of Urban Heat Island Effect using Landsat: A Case Study of Rawalpindi

Abstract

Unplanned urbanization is an escalating issue in Pakistan, particularly in cities like Karachi, Lahore, Faisalabad, and Rawalpindi. With the highest urbanization rate in South Asia, Pakistan is projected to have 50% of its population in cities. This study focuses on the impact of increasing urbanization on Land Surface Temperature (LST) and examines the effects of surface urban heat island formation in Rawalpindi. Land use changes were analyzed through supervised image classification of satellite imagery, and LST was calculated using machine learning and cloud-based computing in Google Earth Engine. The results indicate that the built-up area in Rawalpindi expanded from 74.5 km² in 2003 to 227.7 km² in 2023, reflecting a 206% increase over 20 years. The LST trends show a significant rise, with the mean LST increasing from 34°C in 2003 to 39°C in 2023. The correlation analysis between LST and spectral indices—NDVI (Normalized Difference Vegetation Index) and NDBI (Normalized Difference Built-up Index)—revealed a positive relationship between LST and NDBI, and a negative relationship between LST and NDVI. This suggests that LST rises with increasing built-up areas and barren land while it decreases in densely vegetated regions. Additionally, the Urban Thermal Field Variance Index (UTFVI) for Rawalpindi showed that most built-up areas fall under the severe UTFVI effect category. Survey results further indicate that residents perceive the severity of summer months to have worsened over time, adversely affecting population health and resource availability. Heat-related illnesses, including heat exhaustion, heat stroke, gastric issues, and dehydration, have become more common with rising LST levels. This study provides critical insights into land use and land cover (LULC) changes and UTFVI, offering valuable information for urban planners to understand the urban climate better and implement effective mitigation strategies.