A GIS-enabled AHP approach for mapping urban flood susceptibility in Bhubaneswar city

Urban floods are among the most devastating natural disasters, causing severe damage to human life, property, and the economy. In this study, we focused on mapping Urban Flood Susceptibility Zones (UFSZ) within the Bhubaneswar Municipal Corporation (BMC), as it used a GIS-based Analytical Hierarchy Process (AHP) model integrated via Remote Sensing (RS) with Multi-Criteria Decision-Making (MCDM) techniques. Twelve flood-inducing factors were given weight by the model. Elevation had 25%, Land Use and Land Cover had 19%, and Distance to River received 15%, marking these as critical parameters. We analyzed 130 flood event locations collected through field surveys conducted between June and September 2023, validating flood-prone zones using the Google Earth Engine (GEE). A Consistency Ratio (CR) of 0.06 (