Open Access Open Access  Restricted Access Subscription Access

Flood Risk Mapping and Management in Coastal Communities of Lagos State, Nigeria


 

Coastal cities in African urban areas have high concentration of residential, industrial, commercial, military and educational facilities. The Nigerian coast is likely to experience severe effects from flooding which is due to low elevation and topography especially at high tides during rainy season. This study examined the factors responsible for flooding in Lagos State and its impacts in terms of social, economic and environmental consequences. The methodology for the study included downloading Landsat 7 image and classification in ArcGIS software using supervised image classification methods. This assisted in the identification of human activities contributing to flooding in the study area. Elevation data was obtained from SRTM data downloaded in earth explorer (http://earthexplorer.usgs.gov/), Digital Elevation Model (DEM), slope, aspect, river network, etc. were extracted. Slope, DEM and classified Landsat 7 image were further processed to identify areas vulnerable to flooding in the study area. The effects of flooding were clearly stated and recommendations made.


Keywords

Flooding, Digital Elevation Model (DEM), vulnerability, image classification, Geographic Information System (GIS)
User
Notifications
Font Size

Abstract Views: 126

PDF Views: 0




  • Flood Risk Mapping and Management in Coastal Communities of Lagos State, Nigeria

Abstract Views: 126  |  PDF Views: 0

Authors

Abstract


Coastal cities in African urban areas have high concentration of residential, industrial, commercial, military and educational facilities. The Nigerian coast is likely to experience severe effects from flooding which is due to low elevation and topography especially at high tides during rainy season. This study examined the factors responsible for flooding in Lagos State and its impacts in terms of social, economic and environmental consequences. The methodology for the study included downloading Landsat 7 image and classification in ArcGIS software using supervised image classification methods. This assisted in the identification of human activities contributing to flooding in the study area. Elevation data was obtained from SRTM data downloaded in earth explorer (http://earthexplorer.usgs.gov/), Digital Elevation Model (DEM), slope, aspect, river network, etc. were extracted. Slope, DEM and classified Landsat 7 image were further processed to identify areas vulnerable to flooding in the study area. The effects of flooding were clearly stated and recommendations made.


Keywords


Flooding, Digital Elevation Model (DEM), vulnerability, image classification, Geographic Information System (GIS)