Temporary disaster debris management site identification using binomial cluster analysis and GIS |
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Authors: | Stanislaw Grzeda Thomas A. Mazzuchi Shahram Sarkani |
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Affiliation: | 1. Program Manager at the National Geospatial‐Intelligence Agency, , Springfield, Virginia, United States;2. Professor of Engineering Management and Systems Engineering as well as Decision Sciences Chair in the Department of Engineering Management and Systems Engineering, School of Engineering and Applied Science, George Washington University, , Washington, DC, United States;3. Professor of Engineering Management and Systems Engineering (EMSE) as well as Faculty Advisor and Academic Director of EMSE Off‐Campus Programs, Department of Engineering Management and Systems Engineering, School of Engineering and Applied Science, George Washington University, , Washington, DC, United States |
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Abstract: | An essential component of disaster planning and preparation is the identification and selection of temporary disaster debris management sites (DMS). However, since DMS identification is a complex process involving numerous variable constraints, many regional, county and municipal jurisdictions initiate this process during the post‐disaster response and recovery phases, typically a period of severely stressed resources. Hence, a pre‐disaster approach in identifying the most likely sites based on the number of locational constraints would significantly contribute to disaster debris management planning. As disasters vary in their nature, location and extent, an effective approach must facilitate scalability, flexibility and adaptability to variable local requirements, while also being generalisable to other regions and geographical extents. This study demonstrates the use of binomial cluster analysis in potential DMS identification in a case study conducted in Hamilton County, Indiana. |
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Keywords: | cluster analysis disaster debris management DMS disaster preparedness GIS land use suitability mitigation response and recovery site identification |
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