Flood Vulnerability and Risk Assessment of Onitsha, Anambra State Using Remote Sensing and GIS: AHP Method

Flooding remains one of the most devastating natural hazards affecting both rural and urban communities in Nigeria, resulting in the loss of lives, destruction of property, disruption of socioeconomic activities, and environmental degradation. Onitsha, Anambra State, is particularly vulnerable to recurrent flooding due to its low-lying terrain, rapid urbanization, proximity to the River Niger, inadequate drainage infrastructure, and poor waste management practices that obstruct natural drainage channels. This study assessed the flood vulnerability of Onitsha using Remote Sensing and Geographic Information Systems (GIS) integrated with the Analytic Hierarchy Process (AHP) and Multi-Criteria Decision Analysis (MCDA). Spatial datasets including Digital Elevation Model (DEM), Topographic Wetness Index (TWI), slope, rainfall, land use/land cover (LULC), Normalized Difference Vegetation Index (NDVI), and Euclidean distance from water bodies were processed, reclassified, weighted, and integrated using weighted overlay analysis to generate a flood vulnerability map. The results revealed that topography, proximity to water bodies, land cover characteristics, and surface wetness were the major factors influencing flood susceptibility within the study area. The final flood vulnerability map classified the area into three vulnerability zones, with approximately 8.45% (18,054 m²) identified as highly vulnerable, 90.40% (193,141 m²) as moderately vulnerable, and 1.15% (2,454 m²) as having low vulnerability to flooding. The predominance of the moderate vulnerability class indicates that a substantial proportion of Onitsha remains susceptible to flooding, particularly during periods of intense rainfall and River Niger overflow. The study demonstrates the effectiveness of integrating GIS and AHP for flood vulnerability assessment and provides valuable spatial information to support flood risk reduction, sustainable urban planning, disaster preparedness, and evidence-based decision-making by government agencies and environmental managers.