Flooding is one of the most devastating natural disasters in Nigeria. The impact of flooding on human activities cannot be overemphasized. It can threaten human lives, their property, environment and the economy. Different techniques exist to manage and analyze the impact of flooding. Some of these techniques have not been effective in management of flood disaster. Remote sensing technique presents itself as an effective and efficient means of managing flood disaster. In this study, SPOT 10 image was used to perform land cover/ land use classification of the study area. Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) image of 2010 was used to generate the Digital Elevation Model (DEM). The image focal statistics were generated using the Spatial Analyst/ Neighborhood/Focal Statistics Tool in ArcMap. The contour map was produced using the Spatial Analyst/ Surface/ Contour Tools. The DEM generated from the focal statistics was reclassified into different risk levels based on variation of elevation values. The depression in the DEM was filled and used to create the flow direction map. The flow accumulation map was produced using the flow direction data as input image. The stream network and watershed were equally generated and the stream vectorized. The reclassified DEM, stream network and vectorized land cover classes were integrated and used to analyze the impact of flood on the classes. The result shows that 27.86% of the area studied will be affected at very high risk flood level, 35.63% at high risk, 17.90% at moderate risk, 10.72% at low risk, and 7.89% at no risk flood level. Built up area class will be mostly affected at very high risk flood level while farmland will be affected at high risk flood level. Oshoro, Imhekpeme, and Weppa communities will be affected at very high risk flood inundation while Ivighe, Uneme, Igoide and Iviari communities will be at risk at high risk flood inundation level. It is recommended among others that buildings that fall within the Very High Risk area should be identified and occupants possibly relocated to other areas such as the No Risk area.