ANALYSIS OF URBAN SPRAWL OF DEHRADUN FROM 1993 TO 2023 USING 3 DIFFERENT URBAN GROWTH MODELS

Abstract

Urbanization is a transformative force that significantly influences socio-economic structures, environmental systems as well as urban landscapes. This rapid urban growth, driven by financial opportunities, infrastructural development, and migration, introduces numerous challenges for urban planners and policymakers. This thesis examines the urban sprawl of Dehradun, India, from 1993 to 2023 utilizing Landsat images in 3-year intervals, i.e., 1993, 1996, 1999, 2002, 2005, 2008, 2011, 2014, 2017, 2020, and 2023 utilizing three advanced urban growth models: Random Forest (RF), Support Vector Machine (SVM), and Classification and Regression Trees (CART). These models are used to assess urban expansion, employing Geographic Information Systems (GIS) and remote sensing technologies for a comprehensive analysis of spatial and temporal patterns of urban growth. The processing and analysis were done using the Google Earth Engine, and the maps were generated through QGis. Dehradun, the capital city of Uttarakhand, has undergone substantial transformation over the past three decades, evolving from a small town into a bustling urban agglomeration that has gained an extremely vigorous expansion after this city gained the capital city status after Uttarakhand separated from Uttar Pradesh. This growth, driven by economic development, population increase, and infrastructural improvements, has also led to environmental degradation, unplanned expansion, and pressure on public services. Dehradun's exceptional geographic location in the ecologically sensitive Doon Valley, flanked by the Ganges and Yamuna rivers, necessitates cautious urban planning to balance development with environmental conservation.