Practical Application of Remote Sensing Physics in Mapping Flood-Prone Areas in the Lokoja Confluence Region

Lokoja, the capital of Kogi State in North Central Nigeria, lies at the confluence of the Niger and Benue Rivers and experiences recurrent severe flooding that displaces communities and destroys infrastructure. This study applies remote sensing physics principles to map flood-prone areas in the Lokoja confluence region using multi-temporal Landsat 8 Operational Land Imager and Sentinel-1 Synthetic Aperture Radar satellite data acquired during the 2022 flood season. Radiometric calibration, atmospheric correction using the Dark Object Subtraction method, and geometric correction were applied to optical imagery. Flood inundation extent was extracted from Sentinel-1 C-band SAR imagery using a threshold-based change detection algorithm applied to pre-flood and peak-flood image pairs. A Digital Elevation Model derived from SRTM data was used to generate slope, flow accumulation, and topographic wetness index layers. These physical parameters were integrated in a weighted multi-criteria flood vulnerability assessment framework calibrated against surveyed inundation ground truth points. The modeled flood extent achieved an overall classification accuracy of 88.4 percent when validated against Kogi State Emergency Management Agency field survey records. The study produces flood hazard zoning maps at 30-meter spatial resolution and identifies communities and infrastructure assets in each hazard tier. Professional recommendations are made for integrating the produced flood maps into Lokoja's urban planning and early warning systems. Keywords: remote sensing, flood mapping, Lokoja, synthetic aperture radar, flood hazard