Abstract:
Urbanization is rapidly increasing, particularly in developing countries. As cities expand, they often encroach upon natural areas like forests to construct roads and infrastructure. Studies indicate that by 2030, approximately 70% of the world's population will reside in cities. While cities are crucial for job opportunities and economic activities, they also pose significant environmental challenges. As a result, there is increasing global concern about the negative impacts of urban expansion, leading to the need for the creation of urban environments that are more sustainable to support the growing population influx. Urbanization influences local weather and climate, with one major consequence being the urban heat island effect, where cities tend to be hotter than surrounding rural areas due to the absorption and retention of heat by buildings and roads.
Understand why cities, experience higher temperatures compared to their surroundings, it is essential to quantify the extent of this temperature difference and how it changes over time. By doing so, we can examine how urban form and layout contribute to heat accumulation and devise strategies to mitigate it. One approach to study this phenomenon is through the analysis of data collected from satellites and other remote sensing techniques.
This thesis aims to investigate Land Surface Temperature (LST) over the Gurugram municipal area, commonly known as the Millennium City, which is experiencing rapid development and population growth. The city has undergone significant land use changes and observed changes in land surface temperature due to its expansion. Therefore, there is a need to explore the role of urbanization in increasing the Land Surface Temperature of the city.
For this study, Urban Heat Island intensity maps of the Gurugram municipal area have been generated for three years: 2003, 2013, and 2023, using Landsat 7, Landsat 8, and Landsat 9 satellite data with a spatial resolution of 30m. The Urban Thermal Field Variance Index has been employed for mapping purposes, and the mono-window algorithm has been utilized to retrieve land surface temperature from Landsat thermal band data.
Based on the analysis, the formation of heat islands is identified, and adaptive and mitigating strategies are proposed for our study area.
