An essential component of post disaster planning and preparation is the identification and selection of temporary disaster debris management sites (DMS). However, because DMS identification is a complex process, many regional, county and municipal jurisdictions initiate this process during the disaster response and recovery phases, typically a period of severely stressed resources. The combination of available geospatial datasets, GIS and cluster analysis applications offers a consistent, scalable, flexible and adaptable procedure to support pre-disaster identification of potential DMS.
This study investigates the utility of cluster analysis associated with GIS based geospatial data to accomplish an identification of temporary disaster debris management sites for the post-disaster environment. Parcels locations are assessed for land use, ingress/egress, wetlands, soil suitability, floodplains, threatened species, seismic activity, unstable areas, and proximity to airports, historical/archaeological sites, locales, populated places, medical facilities, parks, schools, religious facilities, and cemeteries. A binomial cluster analysis is performed on constraint augmented parcel data to provide a preliminary assessment of each parcel's suitability as a temporary disaster debris management site. The approach enhances the identification of candidate site selection for post-disaster response and recovery efforts.
|Advisor:||Sarkani, Shahram, Mazzuchi, Thomas A.|
|Commitee:||Eisner, Howard, Holzer, Thomas, Murphree, Lile|
|School:||The George Washington University|
|Department:||Engineering Mgt and Systems Engineering|
|School Location:||United States -- District of Columbia|
|Source:||DAI-B 73/08(E), Dissertation Abstracts International|
|Subjects:||Geography, Operations research|
|Keywords:||Binomial clusters, Cluster analysis, Disaster debris, Disaster management|
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