GIS for Search & Rescue Strategies & Concepts

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Presented by Don Ferguson at 2012 WVAGP Membership Meeting.

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  • The search area is often times quite large and each task is a significant investment in time and resources so we need to have methodology for prioritizing areas to be searched. In addition while the majority of search tasks assigned over the course of a search mission do not result in the subject being found it is important to quantify the outcome in order to obtain feedback on the the search strategy be followed and as well as evaluating the overall progress.Operations Research which grew out of practices developed by the US and Britain during WWII to assist in the search for enemy submarines by the navy and resource allocation in support of the ground war has been adapted for use in wilderness SAR to assist with decision making.This includes Bayesian probability Theory which consists of assigning a probability to a hypothesis and adjusting the probability through testing without fully resolving hypothesis
  • Once we have been notified that we have a SAR mission we then need to identify where to search. There are actually a collection of methodologies that are used to define the search area. Once we have an initial planning point (or IPP), often times being the point where the subject was last seen or the last known location of the subject when can begin by considering the theoretical distance that person could of traveled in the period of time they have been missing. Historically, this would result in a circle drawn on the map the radius of which would be the product of the estimated travel speed and the time they have been missing irrespective of variations in terrain, vegetation and geographical features. Now we can develop a Least-Cost Surface Model around the IPP that incorporates Tobler’s travel speeds, vegetation and Strahler stream order.We continue to refine the search area by considering historical data related to the behaviors of lost subjects that full under a similar category or situation. I imagine Bob will speak to this more fully.And finally through the generation of behavioral and geographic profiles specific to the lost subject we formulate scenarios of where the person may be. This is a continuous process as new information is obtained. So let’s explore this idea a bit further.
  • GIS for Search & Rescue Strategies & Concepts

    1. 1. Geospatial Modeling for the Optimizationof Search and Rescue Strategies Don Ferguson, PhD Mountaineer Area Rescue Group A member of Appalachian Search and Rescue Conference WVAGP Membership Meeting November 27, 2012 Sutton, WVAppalachian Search and Rescue Mountaineer Area Rescue GroupConference
    2. 2. Where Do We Start Looking? “Search” for a missing subject could be considered the proverbial “needle in a haystack” Time is limited - Search is an emergency Subject may be injured / will not survive indefinitely Clues deteriorate over time Weather Improve PSR by Availability of resources reducing the Goal of search management is to search area maximize the probability of success at the greatest rate possible. Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    3. 3. Improving the Success Rate Majority of searches are resolved within a few hours Only about 1% – 3% required Extended Planning of operations Extended searches typically encompass relatively large geographical areas Two options for improving the Success Rate Reduce the search area Search in most likely areas first Increase the rate of detection Proper resource allocation Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    4. 4. Application of Operational Research to SAR Need a systematic method to prioritize regions within the search area and evaluate progress. SAR operations typically time and resource limited OR provides framework to aid in decision-making and improve efficiency. Developed during WWII to search for enemy submarines and improve resource allocation1 Bayesian Probability Theory Assigning a probability to a hypothesis and adjusting the probability through testing without needing to fully resolving the hypothesis a1, a2, …, ak are mutually exclusive events (hypothesis), of which none has a zero probability. b is any event (data used to test the hypothesis). 1. Koopman, B.O., “Search and Screening: General Principles with Historical Applications”, Pergamon Press, New York, 1980., 2003. Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    5. 5. Defining the Search Area Search area is defined by a collection of methodologies Theoretical Distance traveled Historical/Categorical mobility data Statistical Historical/categorical search 25% data 50% Subjective-Deductive 75% Subject and environment specific Autistic Distance from IPP (km) Theoretical and n 20 Statistical Search 25% 0.6 Area 50% 1.6 ISRID Data 75% 3.7 Appalachian Search and Rescue Conference Mountaineer Area Rescue Group 95% 15.2
    6. 6. Theoretical Search AreaThis is the distance that the subject could have traveled in the time elapsed. How far, how fast? Subject can theoretically travel in any direction 3.14 * (1mile)2 = 3.14miles2 Identifying a clue or DOT could help to limit the search area 10 mile radius Could also alter theoretical distance by considering terrain and environmental impedance Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    7. 7. Theoretical Search Area…cont Cost Surface - High slope impassable - Reclassify NLCD Travel Time - Roads, Trails, Streams, Hours Utilities, Fenceline, 1 Water bodies 2 3-4 5-6 7-8 9 - 10 11 - 12 13 Tobler, W. 1993. Three presentations on geographical analysis and modeling. Technical report. 93-1, National center for geographic information and Analysis, University of California, Santa Barbara. Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    8. 8. Subjective / Deductive Area Formulate a series of hypotheses based on all available information (geospatial, subject profile, etc). Compare hypotheses to determine most likely scenario (Analysis of Competing Hypotheses) Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    9. 9. Subjective / Deductive Area: Probability Regions A Region is a defined subset of the Search Area within which there is a uniform distribution of the likelihood of containing the search object1 – Probability of Containment (POC) Assign “a priori” probability of the subject being in a location Based on scenarios comprised of Theoretical Search Area Statistical Search Area Surrounding geography Natural and man-made features Physical and Behavioral profiles of the missing subject Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    10. 10. Develop Searchable Segments Sub-divisions of Probability Regions based on logistical and operational issues associated with conducting the search itself Resource capabilities / availability Well defined field recognizable boundaries Segment POC Area-weighted POC associated with the Region POC. Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    11. 11. Tracking Success Segments are assigned based on POC with most likely locations being searched first. Goal is to reduce (minimize) the POC of a segment to zero Hopefully locate the subject sooner Update POC after search of each segment Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    12. 12. Statistical Search Area Statistical data from previous searches involving persons that could be considered categorically similar could provide valuable insight in defining the search area Doherty, P., Guo, Q., Liu, Y., Wieczorek, J., and Doke, J., “Georeferencing Incidents from Locality Descriptions and its Applications: a Case Study from Yosemite National Park Seach and Rescue”, Transactions in GIS, 15(6): 775-793, 2011.. Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    13. 13. Statistical Search Area Assume you are the administrator for a regional park. The park consists of a series of trails with 11 different trailheads. This park is used primarily by day hikers Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    14. 14. Statistical Search Area Other the course of the previous year you had 100 SAR incidents occur within your park. Limited the dataset to only subjects reported as missing. Although your subjects ranged in age from 15 – 85 they all reported being in the park to hike. As a result of good record keeping you had coordinates for both the find and the IPP. In 100% of the cases the IPP was a subject’s vehicle parked at one of the trailheads. Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    15. 15. Statistical Search Area Although you did not have data reporting the actual distance the subject had traveled from the IPP to the point that they were found, you can measure the straight-line (crow-flies) distance between the IPP and the find location. Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    16. 16. Statistical Search Area With the IPP-Find Distance from IPP to Find (km) distances plotted 16 we can easily see 14 the min and max values (Range) 12 Distance (km) Min = 0.4 km 10 Max = 14.5 km 8 6 Also may be 4 interested in the 2 mean or average distance recorded 0 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 1 5 9 Mean = 5.8 Incidents in Chronological Order While interesting, the distances could contain “outliers” that could impact the value of the statistics. Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    17. 17. Statistical Search Area If however, the Distance from IPP to Find (km) distances are 16 sorted by length 14 we can obtain the “median” value 12 Middle value of an Distance (km) 10 ordered set of 8 numbers Median = 5.2 km 6 4 2 0 0 20 40 60 80 100 120 Incidents Sorted by Distance (low - high) Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    18. 18. Statistical Search Area If however, the Distance from IPP to Find (km) distances are 16 sorted by length 14 we can obtain the 12.0 km “median” value 12 75% Distance (km) Middle value of an 10 ordered set of 95% numbers 8 50% 8.0 km Median = 5.2 km 6 25% 4 5.2 km Quartiles 2 3.23 km Divide the 0 distances into four 0 20 40 60 80 100 120 equal groups Incidents Sorted by Distance (low - high) 25%, 50%, 75% and 100% Due to outliers, the 100% distance may not be of interest so limit the data to 95%. Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    19. 19. Statistical Search Area…Application Return to the original IPP and find locations. Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    20. 20. Statistical Search Area…Application Let’s consider only the IPP for a moment. Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    21. 21. Statistical Search Area…Application Let’s collapse all of the IPP’s to a single virtual IPP as shown on the map. Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    22. 22. Statistical Search Area…Application If we now re-plot virtual find locations at the same distances of our actual IPP-Find distances we would end up with a distribution that looks similar to this Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    23. 23. Statistical Search Area…Application If we divide up the 100 find locations into groups of 25 Draw a ring around the closest 25 Draw a second ring around the next closest 25…and so on If we assume that behaviors of “hikers” within the park is similar then we would expect other lost hikers within the park to be found at similar distances. However, we are not always just looking for lost More data is better hikers and sometimes we need to look for subjects outside of our own park. Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    24. 24. Statistical Search Area…Find Locations What if you also had collected data on the find location and categorized it by a predominate feature. Feature Percent Road 3% Find features for “Hikers” Fields 4% Woods 88% Using readily available geospatial data to “reclassify” spatial data to coincide with Find Locations Koester, R.J., “Lost Person Behavior: A search and rescue guide on where to look - for land, air and water”, dbS Productions LLC, 2008. Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    25. 25. Statistical Search Area…Find Locations Utilize: roads, trails and drainage layers along with land cover data (from National Land Cover Database) Roads, Trails and Drainages Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    26. 26. Statistical Search Area…Find Locations Identify features where finds are made. These features may or may not represent attractants for the subject category Find Locations Roads – 3% Fields – 4% Woods – 88% Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    27. 27. Statistical Search Area…Track OffsetConsider the shortest distancebetween a linear feature(roads, trails, drainages, powerline ROWs, etc) and where thesubject was found. Track Offset (meters) 25% 70 50% 126 75% 254 100% 964 Feature (0-20 m) 25% (21-70 m) 50% (71-126 m) 75% (127-254 m) Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    28. 28. Statistical Search Area…ElevationConsider the differencein elevation betweenthe IPP and where thesubjects were found. Elevation (meters) 3% +/-20 42% +21 : 1701 55% -1606 : -21 +/- 20 m +31 : 1701 m -1606 : -21 m Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    29. 29. Statistical Search Area…Mobility  Similar to the Theoretical Search Area, data is collected from subjects regarding the length of time they were mobile. Because we can predict travel time from spatial data (land cover, terrain, travel aides, etc) we can estimate travel time within the search area. Mobility (hrs) 25% <3 Mobility (hours) 50% <5 1 100% 9 2Note: Steep slopes inhibit 3access within this area. In 4this hypothetical situation the 5IPP (orange symbol) was 6adjusted due to its originallocation being position on a 7steep slope. 8 >8 Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    30. 30. Statistical Search AreaInternational Search and Rescue Database ISRID project began in 2002 focused on the collection of information from missing/lost person incidents for the purpose of understanding lost person behavior Currently contains over 50,000 missing/lost person incidents 41 subject categories Statistical Search Area defined as the straight line distance (“Crow Flies”) from the Initial Planning Point (IPP – typically the last known location of the subject) to the find location. Additional analysis provided on the nature of the find location (structure, water, woods, etc). Koester, R., “Lost Person Behavior”, dbS Productions, Charlottesville, VA, 2008 Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    31. 31. Statistical Search Area Utilize historical data to predict location of current missing subject. We are all a creature of habit even when we are lost. Results from ISRID have been published in “Lost Person Behavior” Data from various eco-regions and includes 41 different subject categories Appalachian Search and Rescue Conference Mountaineer Area Rescue Group
    32. 32. Modeling Lost Person Behavior Statistical Search Mobility Model Elevation Find Location Area Difference Model Model Track Offset Hazardous Model Terrain Model Operational Appalachian Search and Rescue Conference Map Mountaineer Area Rescue Group
    33. 33. Questions? Contact information: Don Ferguson Mountaineer Area Rescue Group dferguso@mix.wvu.edu (304) 290-9118Appalachian Search and Rescue Conference Mountaineer Area Rescue Group

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