Decision Support System For Search & Rescue Operations
Keywords:Decision Support System, SAR, GIS
AbstractSAR (Search and Rescue) operation is a complex process, often carried out in the absence of resources and time. Every single minute matters, as it puts the lost person in more danger. Therefore, it is really crucial to plan and coordinate SAR operation effectively. Because the search area is often very extensive, any leads about where to look first are invaluable. This can be achieved by modelling lost person’s behaviour based on the data from past operations. Generated results present probabilities of finding a subject in different segments of the search area, which might benefit the planning and the execution phases of the operation. The authors evaluate one of the commonly used modelling methods and propose several ways to improve it, together with some preliminary evaluation results and an already implemented system, which incorporates the described methodology.
Doherty P. J., Quinghua G., Doke J., Ferguson D.: An analysis of probability of area techniques for missing persons in Yosemite National Park. Applied Geography, pp. 99–110, February 2014.
Doherty P. J., Quinghua G., Wenkai L., Doke J.: Space-time analyses for forecasting future incident occurrence: a case study from Yosemite National Park using the presence and background learning algorithm. International Journal of Geographical Information Science, pp. 910–927, May 2014.
Durkee G., Glynn-Linaris V.: Using GIS for Wildland Search and Rescue. ESRI Press, Redcands, CA, USA, 2012.
Fortin F. A., De Rainville F. M., Gardner M. A., Parizeau M., Gagné C.: DEAP: Evolutionary Algorithms Made Easy. Journal of Machine Learning Research, pp. 2171–2175, July 2012.
Heth D. C., Cornell E. H.: Characteristics of Travel by Persons Lost in Albertan Wilderness Areas. Journal of Environmental Psychology, pp. 223–235, September 1998.
Hill K. A.: Lost person behavior, chap. The psychology of lost, pp. 1–16. National SAR Secretariat, Ottawa, Canada, 1998.
Koester R. J.: Lost Person Behavior. A search and rescue guide on where to look – for land, air and water. 1st ed. dbS Productions LLC, Charlottesville, VA, USA, 2008.
Lin L., Goodrich M. A.: A Bayesian approach to modeling lost person behaviors based on terrain features in Wilderness Search and Rescue. Computational Mathematical Organisation Theory, vol. 16(3), pp. 300–323, Springer US, 2010, http://dx.doi.org/10.1007/s10588-010-9066-2.
Norris J. R.: Markov Chains. Cambridge University Press, 1998.
Steinberg S. J., Steinberg S. L.: Geographic Information Systems for the Social Sciences. SAGE Publications, Thousand Oaks, CA, USA, 2006.
Syrotuck W. G., Syrotuck J. A.: Geographic Information Systems for the Social Sciences. Barkleigh Productions, Mechanicsburg, PA, USA, 2000.
Wysokiński M., Marcjan R., Dajda J.: Decision Support Software for Search & Rescue Operations. Procedia Computer Science, vol. 35, pp. 776–785, 2014.