Geography

A multi-criteria geographic information system screening approach for prioritizing response activities following a chemical, biological, or radiological incident

Document Type

Book Chapter

Abstract

This paper describes the development of a decision support tool, the Priority Response Environmental Screening Tool (PRESTO), that was designed to provide a framework for analyzing geospatial information. The objective of a PRESTO analysis is to assist the U.S. Environmental Protection Agency (EPA), in partnership with state and local decision-makers, in informing the prioritization of locations for initial cleanup operations aimed at reducing risks to public health and the environment after a natural disaster or chemical, biological, or radiological (CBR) incident. In the event of a natural disaster or release of CBR contaminants, for example, EPA and its partners would need to determine which locations should be prioritized to prevent the spread of contamination and mitigate long-term risks. Decision makers are often hampered by having too little or too much data, such that it is not obvious how relevant data can be incorporated into a decision-making framework. PRESTO provides a flexible and adaptable framework to address the challenges of aggregating data in a meaningful way to facilitate quickly identifying and understanding the resulting information to inform decisions. To demonstrate how PRESTO could inform disaster response planning following a hypothetical CBR release, a 10-mile radius study domain centered on Philadelphia, PA was analyzed. Nine data sets measuring a range of issues reflecting risks to human health and the environment were used for this demonstration. The demonstration showed that there were substantial differences in which locations would be prioritized for response by using data aggregation schemes available within PRESTO for determining priority locations compared to relying on more commonly used data aggregation schemes. This is because PRESTO allows data sets reflecting high risks at a given location to be emphasized, even if other data sets reflect low risks because they represent different issues. Specifically, this analysis showed that in some locations in the northwest of the study area and in center city Philadelphia, very high risks that emanate from exceedingly high population densities (so the possibility that many more people would be affected by contamination) and from large areas with impervious surfaces (which would allow rapid spread of contamination via stormwater) are captured by using PRESTO. However, simpler analyses would not prioritize any locations in the center of the city. PRESTO also makes the data sets and associated issues that drive specific prioritization decisions readily accessible, such that motivations for decisions are transparent via easily understood graphical displays. © 2025 by Information Age Publishing. All rights reserved.

Publication Title

Contemporary Perspectives in Data Mining

Publication Date

6-2025

First Page

101

Last Page

140

ISBN

9798887308548

Keywords

contamination, data aggregation, decision making, decision support systems, disaster prevention, emergency services, Environmental Protection Agency, health risks, information use, population statistics, risk assessment, screening

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