Evaluating Flood Vulnerability with Remote Sensing and GIS: Urban Development Challenges in Chennai City Region, Tamil Nadu, India

This study evaluates flood vulnerability in the Chennai City Region, Tamil Nadu, using remote sensing and GIS techniques to guide urban development planning. With rapid urbanization and recurrent flooding, Chennai faces heightened risks from heavy monsoon rains, inadequate drainage, and encroachment on natural floodplains. Sentinel-2 and Landsat satellite imagery, combined with GIS data such as digital elevation models (DEM) and land-use maps, were used to classify land cover, map flood extents, and assess flood vulnerability. A multi-criteria evaluation using Analytical Hierarchy Process (AHP) identified key vulnerability factors, including population density, elevation, land use, and proximity to water bodies and drainage infrastructure. The study also conducted sensitivity analyses, including map-removal sensitivity analyses, to quantify the impact of individual parameters on flood vulnerability mapping. The findings reveal significant urban expansion (85% of the area) and widespread impermeable surfaces contributing to high surface runoff and limited infiltration. Topographic Wetness Index (TWI), drainage density, slope, and distance from streams were used to assess flood-prone zones further. The Normalized Difference Vegetation Index (NDVI) was calculated to evaluate the extent and health of vegetation affected by flooding. At the same time, DEMs and terrain analysis provided insights into low-lying areas with higher flood vulnerability. The research identified flood-prone zones classified into low, medium, and high-risk areas, covering 24.4%, 50.2%, and 25.4% of the study region, respectively. These results underscore the need for sustainable land-use management, improved drainage infrastructure, and climate-resilient urban development strategies to mitigate flood vulnerability in Chennai. The comprehensive assessment aims to support flood vulnerability management efforts and urban resilience planning in the region.