NDLI: Detection likelihood maps for wilderness search and rescue

Content Provider	IEEE Xplore Digital Library
Author	Roscheck, M. Goodrich, M.A.
Copyright Year	2012
Description	Author affiliation: Computer Science Department, Brigham Young University, Provo, USA (Roscheck, M.; Goodrich, M.A.)
Abstract	Every year there are numerous cases of individuals becoming lost in remote wilderness environments. Principles of search theory have become a foundation for developing more efficient and successful search and rescue methods. Measurements can be taken that describe how easily a search object is to detect. These estimates allow the calculation of the probability of detection—the probability that an object would have been detected if in the area. This value only provides information about the search area as a whole; it does not provide details about which portions were searched more thoroughly than others. Ground searchers often carry portable GPS devices and their resulting GPS track logs have recently been used to fill in part of this knowledge gap. We created a system that provides a detection likelihood map that estimates the probability that each point in a search area was seen well enough to detect the search object if it was there. This map will be used to aid ground searchers as they search an assigned area, providing real time feedback of what has been “seen.” The maps will also assist incident commanders as they assess previous searches and plan future ones by providing more detail than is available by viewing GPS track logs.
Starting Page	327
Ending Page	332
File Size	326724
Page Count	6
File Format	PDF
ISBN	9781467317139
e-ISBN	9781467317146
e-ISBN	9781467317122
DOI	10.1109/ICSMC.2012.6377722
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-14
Publisher Place	Korea (South)
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Search problems Global Positioning System Equations Mathematical model Observers Vegetation mapping Computer simulation effective sweep width search and rescue probability of detection
Content Type	Text
Resource Type	Article

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