A Comparative Study on Various Water Index Methods Through Satellite Image Processing for Pre- and Post-flood Monitoring of 2021—A Case Study of Chengalpattu Taluk, India

Flood is the most hazardous, widespread, and significant natural disaster, leading to more damage to all resources, specifically the highly affected urbanized area. Remote sensing is a useful technique for studying flood-prone area detection. The purpose of this research is to delineate pre- and post-flooded areas in Chengalpattu taluk during 2021. In this research, various water index methods, like Water Ratio Index (WRI), Modified Normalized Difference Water Index (MNDWI), and Normalized Difference Water Index (NDWI), were computed using spectral bands from selected visible to SWIR wavelengths of satellite images. This spectral band-based index provides a better understanding of the identification of flooded areas. The results indicated that the pre-flood was estimated as 3.11 km2, 7.79 km2, and 4.91 km2 by NDWI, MNDWI, and WRI, respectively. Further, the post-flood area was estimated as 4.98 km2, 15.43 km2, and 6.15 km2 by NDWI, MNDWI, and WRI, respectively. Also, a comparative study of the results was conducted for the above various methods, and this approach could be very helpful to delineate in mapping flooded areas with better accuracy. Analysis and results show that the MNDWI method can be used for better water separation and flood area delineation compared to NDWI and WRI.