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The applications of GISystems to wilderness search and rescue, an overview within a GIScience context and examples from Yosemite National Park.

  • Author(s): Doherty, Paul James
  • Advisor(s): Guo, Qinghua
  • et al.
Abstract

The process of searching for and rescuing people in distress provides an appealing spatial problem for geographers to support and for testing theoretical developments in the real-world. Essentially, the fundamental goals of wildland search and rescue (WiSAR) are to locate persons in need and extract them from dangerous situations. More recently, WiSAR researchers and professionals have also cited a need for proactive incident prevention as a critical responsibility, known as preventative search and rescue (PSAR). This research draws on my recently completed case-studies in Yosemite National Park and community development amongst GISystem and WiSAR professionals. Each of these components of WiSAR are inherently spatial and should be evaluated in light of emerging technology and theoretical advances in spatial sciences. Of particular interest are the real-world implications of time geography and probabilistic modeling of objects in space.

This dissertation is formatted using standalone chapters for publication. In the first chapter I discuss the overall need for GIS related research in search and rescue as well as a conceptual framework for doing so. In Chapter II I present research related to preventing incidents. This chapter features two papers with first describing methods for georeferencing text based locality descriptions and preliminary findings on spatial patterns of incident. The second paper presents a spatiotemporal method for mapping the probability of WiSAR in Yosemite National Park by month. Chapter III presents research related to searching for missing persons. I present a paper that describes two probability of area methods and findings related to applying global versus local models.

Finally, Chapter IV pertains to the rescue phase of WiSAR. Here I present a paper that compares an expert (weighted overlay) versus machine-learning technique for mapping suitability of helicopter landing areas. Following this I conclude the dissertation with final remarks and recommendations.

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