Title page for ETD etd-05102011-113526


Type of Document Master's Thesis
Author Muza, Matej
URN etd-05102011-113526
Title Development of a Spatial Decision Support System for Emergency Medical Service Facility Siting
Degree Master of Science
Department Geography
Advisory Committee
Advisor Name Title
Carstensen, Laurence William Jr. Committee Chair
Dymond, Randel L. Committee Member
Kolivras, Korine N. Committee Member
Keywords
  • Spatial Decision Support Systems (SDSS)
  • GIS
  • EMS
  • Facility Siting Analysis
Date of Defense 2011-05-02
Availability restricted
Abstract
Improved strategic location of an Emergency Medical Service (EMS) facility can significantly increase EMS efficiency. Urban planners need to consider a location that satisfies multiple criteria in order to make an informed decision about a future EMS facility site. Apart from basic criteria such as parcel value and size, decision-makers need to consider area and population coverage from potential parcels. Geographic Information Systems (GIS) provide an adequate analysis environment for EMS facility siting as many considered criteria are of a spatial nature. However, urban planners making decisions about an EMS facility site often lack the necessary expertise to make full use of challenging GIS tools.

In order to help urban planners in the analysis process, this research developed a Spatial Decision Support System (SDSS) for EMS facility siting. The system was developed in ESRI ArcGIS (9.3) using the Visual Basic for Applications (VBA) programming environment. The objective of the system was to integrate spatial data, analysis, and visualization in a single system to help users evaluate a facility siting problem. The system’s performance was tested using data for the Town of Blacksburg, VA. In addition, the system was evaluated by local planners and GIS staff with experience in EMS facility siting. Planners agreed the system enables more comprehensive and straightforward use of GIS for EMS facility siting analysis than other available siting tools. Potential improvements include a simpler user interface, synthesis of geoprocessing techniques, reduction of analysis time through automation, and better decision-making by improved visualization of results.

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