Utilization of Open Source Spatial Data for Landslide Susceptibility Mapping at Chittagong District of Bangladesh—An Appraisal for Disaster Risk Reduction and Mitigation Approach — Oak Academic Publishing
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Utilization of Open Source Spatial Data for Landslide Susceptibility Mapping at Chittagong District of Bangladesh—An Appraisal for Disaster Risk Reduction and Mitigation Approach
Department of Geology, University of Dhaka, Dhaka, Bangladesh
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Department of Geology, University of Dhaka, Dhaka, Bangladesh
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Department of Geology, University of Dhaka, Dhaka, Bangladesh
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Department of Geology and Mining, University of Barisal, Barisal, Bangladesh
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Department of Geology, University of Dhaka, Dhaka, Bangladesh
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Department of Geology, University of Dhaka, Dhaka, Bangladesh
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Department of Geology, University of Dhaka, Dhaka, Bangladesh
1 Department of Geology, University of Dhaka, Dhaka, Bangladesh
2 Department of Geology, University of Dhaka, Dhaka, Bangladesh
3 Department of Geology, University of Dhaka, Dhaka, Bangladesh
4 Department of Geology and Mining, University of Barisal, Barisal, Bangladesh
5 Department of Geology, University of Dhaka, Dhaka, Bangladesh
6 Department of Geology, University of Dhaka, Dhaka, Bangladesh
7 Department of Geology, University of Dhaka, Dhaka, Bangladesh
Since creation of spatial data is a costly and time consuming process, researchers, in this domain, in most of the cases rely on open source spatial attributes for their specific purpose. Likewise, the present research aims at mapping landslide susceptibility at the metropolitan area of Chittagong district of Bangladesh utilizing obtainable open source spatial data from various web portals. In this regard, we targeted a study region where rainfall induced landslides reportedly causes causalities as well as property damage each year. In this study, however, we employed multi-criteria evaluation (MCE) technique i.e. , heuristic, a knowledge driven approach based on expert opinions from various discipline for landslide susceptibility mapping combining nine causative factors—geomorphology, geology, land use/land cover (LULC), slope, aspect, plan curvature, drainage distance, relative relief and vegetation in geographic information system (GIS) environment. The final susceptibility map was devised into five hazard classes viz., very low, low, moderate, high, and very high, representing 22 km 2 (13%), 90 km 2 (53%); 24 km 2 (15%); 22 km 2 (13%) and 10 km 2 (6%) areas respectively. This particular study might be beneficial to the local authorities and other stake-holders, concerned in disaster risk reduction and mitigation activities. Moreover this study can also be advantageous for risk sensitive land use planning in the study area.
KeywordsSusceptibility MappingOpen Source Spatial DataHeuristic ModelChittagong Metropolitan AreaGeographic Information System (GIS)Disaster Risk Reduction
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