This project examined the environmental impacts of urbanization in Tamil Nadu, focusing on its contribution to various forms of pollution, including air, water, and land degradation. Utilizing remote sensing data and machine learning techniques, the study aimed to quantify urban sprawl and correlate it with pollution trends across the state. The analysis involved spatial and temporal mapping of urban growth using satellite data such as Sentinel-2 and Landsat, combined with pollution metrics from local and global sources.
The project sought to identify root causes of pollution linked to urbanization by leveraging machine learning models to uncover relationships between factors like population density, vehicular emissions, industrial activities, and reduced green cover. The findings highlighted key drivers of pollution and provided actionable recommendations for sustainable urban development, including enhanced green zoning and stricter industrial regulations.
By focusing on Tamil Nadu, a region experiencing rapid urban expansion, the project delivered localized insights to aid policymakers, environmental agencies, and urban planners in addressing the challenges of urbanization while ensuring environmental sustainability.