Temporary disaster debris management site identification using binomial cluster analysis and GIS

Area of Science:

• Disaster Management
• Geographic Information Systems (GIS)
• Spatial Analysis

Background:

• Effective disaster planning requires timely identification of temporary disaster debris management sites (DMS).
• Current practices often delay DMS selection until after a disaster, during resource-strained recovery phases.
• A proactive, pre-disaster approach is needed to identify optimal DMS locations.

Purpose of the Study:

• To demonstrate a pre-disaster methodology for identifying potential temporary disaster debris management sites (DMS).
• To apply binomial cluster analysis for efficient DMS site selection.
• To develop a scalable and adaptable approach for diverse disaster scenarios.

Main Methods:

• Utilized binomial cluster analysis to identify potential DMS.
• Conducted a case study in Hamilton County, Indiana.
• Focused on incorporating locational constraints into the site identification process.

Main Results:

• The study successfully demonstrated the application of binomial cluster analysis for potential DMS identification.
• The methodology provides a framework for proactive disaster debris management planning.
• The approach is adaptable to various regional and geographical scales.

Conclusions:

• Pre-disaster identification of DMS using binomial cluster analysis is a viable strategy.
• This proactive approach enhances disaster preparedness and resource management.
• The methodology offers flexibility and generalizability for different jurisdictions.