IDENTIFICATION OF TEMPORARY DISASTER DEBRIS MANAGEMENT SITES USING BINOMIAL CLUSTER ANALYSIS

Considerable research continues to be devoted to understanding the nature and extent of disasters, primarily in an effort to plan, manage, simulate and mitigate their effects. One critical aspect of disaster response and recovery research is into the pre-selection of temporary disaster debris management sites (DMS). In addition to the basic DMS factors of ownership, size and location, Federal guidance also notes the need to address special considerations associated with environmental and historic preservation. These considerations arise from a host of Federal acts, agency regulations, executive orders and directives which impose constraints on DMS locational requirements. States, counties, townships and municipalities also implement local laws, regulations and ordinances, typically derived off the United States Code (USC) and in many cases more restrictive, to reflect the specific needs of their citizens and local environment. These place further constraints on DMS.

As a result, the identification of potential debris management sites is a complex process requiring the analysis of all relevant environmental and historic preservation issues to assure compliance to Federal and local constraints while simultaneously assuring effective disaster preparedness. Physical site constraints include: land use, accessibility, wetlands, surface water, conservation areas, coastal boundary zones, soil suitability, floodplains, threatened species/habitats, seismic impact zones, unstable geology, and proximity to cultural point features. Because of this complexity, many regional, county and municipal emergency management plans leave DMS selection to the response and recovery phases, typically periods of severely stressed resources. Thus, a consistent scalable, flexible and adaptable procedure to identify potential disaster debris sites would enhance timely decision making, provide for more effective response and lead to more rapid stabilization for recovery activities.

The increased availability of geospatial, statistical and system engineering applications, large data storage capacities and respective county and Federal GIS datasets offers the capabilities of analyzing large amounts of combinatorial data to support identifying suitable DMS. A geospatial analysis can be conducted at the parcel level to determine each site’s characteristics on a constraint presence or absence basis. Binary cluster analysis of the data matrix results in a classification of all sites, supporting DMS decision making. The identification of temporary disaster debris management sites prior to a disaster facilitates narrowing the potential range and more rapid identification of optimal sites; effective advanced readiness contracting to ensure contracts are in place; modeling, testing and evaluating disaster debris scenarios to identify shortfalls; timely decision making, improving response timing; and more rapid management and containment, i.e., stabilization, of immediate disaster impacts on community systems enhancing recovery activities.