Upload
sidney
View
63
Download
0
Embed Size (px)
DESCRIPTION
Spatial Analyses in Wilderness Search and Rescue. Paul James Doherty Park Ranger / GIS Specialist / Graduate Student. What will be researched?. Objective 1: Describe where Search and Rescue incidents (SARs) occur and predict future events - PowerPoint PPT Presentation
Citation preview
Paul James Doherty
Park Ranger / GIS Specialist
/ Graduate Student
Spatial Analyses in Wilderness Search and Rescue
Objective 1: Describe where Search and Rescue incidents (SARs) occur and predict future events
Objective 2: Increase the “probability of area” (POA -predicting where a lost person is or is going to be)
Objective 3: Increase the “probability of detection” (POD -detecting a lost person if in the search area)
What will be researched?
Use geo-referencing techniques to compute uncertainty measurements for incident location with a large unique (n = approx 4,000) dataset (Guo et al 2007)
Test and evaluate spatial-temporal risk modeling procedures to describe where incidents have occurred and predict where they will occur (Kelly et al 2006)
Intellectual Contribution – Objective 1
Finding a missing person/object is the classic mysteryProbability of Success (POS)
Probability of Area (POA)Probability of Detection (POD)POA x POD = POS
How can integrating GISystems and GIScience increase overall POS?Human foot-travel modeling (work with Liz Sarow Fall
2009)
Dynamic vector design (how do vector inputs improve predictive model accuracy?)
More objective approach to finding missing persons
Intellectual Contribution- Objective 2/3
Yosemite Search and Rescue Background
Case Study: Yosemite National Park• Sierra Nevada, CA• Size
• 1,200 sq. miles• 95% wilderness• 800 trail miles
• Annually• +3.5 million
people• Search and
Rescues: 200
Hung et al 2007 (1990 – 1999)
Searching for Missing Persons in Yosemite National Park
Search TheorySimplified
POA x POD = POSOverall POS = [(POA1 x POD1) +(POA2 x POD2)
….] Where 1,2,3,…. are search segments
Basically, where is the person most likely to be (based off of search model) and how are we most likely to find them (based off of search technique)
The Search for A Missing Person
Objective 1Georeference SAR data
SpatialdistributionMajority of
SARs described are referenced by distance from placenames
Data is in report format, needs to be compiled
What causes clustering?
Geo-reference points from text (occasional GPS)Classify incidents by type (trauma vs. medical
etc.)Evaluate uncertainty of geo-reference
Characteristics of where incidents have occurredEcological Niche Factor Analysis?
Develop new protocols to plot incident locations
Objective 1 - Methods
Methods
Objective 2Probability of Area
What is the current Search Model for determining POA?POA = Theoretical + Statistical + Subjective +
ReasoningHow can we use Spatial Analyses to increase
accuracy of POA?
Objective 2: Increase the probability of area
Establishing Probability of Area (POA)Theoretical
Distance subject could have traveled in the amount of time elapsed (objective, geography)
StatisticalData which reflects the distance other subjects
have traveled under similar conditions (objective, human behavior)
SubjectiveEvaluation of limiting factors (objective,
geography)Reasoning
Systematic analysis of circumstances surrounding the disappearance of missing person (subjective, human behavior)
Objective 2: Increase the probability of area
Construct and evaluate speed models for missing hikersCost-distance modeling
Generate areas of high probabilityRefine data for distance from PLS (CALEMA
data?)Hazards from Objective 1 (20 year dataset)Attractions from viewshed analysesDynamic probability mapping when clues are
detected
Objective 2 - Methods
A function of:TerrainBehavioral Profile
(Koester and Stooksbury 1995)
Time
Cost-Distance modeling
Courtesy of Liz Sarow - ESRI
Objective 3Probability of Detection
What is the current Search Model for determining POD?[Effective Sweep Width]1 + [Clue Detection]1
+ [Coverage of Assignment]1 POD1a *Extremely subjective process
POD1a + POD1b + POD1c = cumPOD1 * Law of diminishing returns applies
Objective 3: Increase the probability of detection
How can we use Spatial Analyses to increase accuracy of POD?Search assignment generation (unified
cartography)Identifying “holes” in search (using GPS)Determine optimal sweep width (ground-truth)
How do we know when we have reached our point of diminishing return?When to stop searching?Search Area vs. Rest of World (ROW)
Objective 3 - Methods
Objective 3: Increase the probability of detection
Objective 1: Georeference SAR dataGeo-referencing 4,000 points will require
significant effort, difficult to do with accuracy/ high resolution
Data quality? N = ~4000 points n = ~2,000 points
Concentration of points around popular hiking areas
Factor significance may vary across the type of incident
Objective 2: Probability of AreaTerrain model will need ground-truth and will
not apply in other habitatsObjective 3: Probability of Detection
Balancing GIS Application vs. GIScience
Challenges…
Novel research topicIncrease overall preparedness for incident
occurrencePreventative Search and Rescue initiativesHelp find missing persons (Searches are
emergencies!) Allow GIS students and Search and Rescue
personnel to collaborate and elevate collective knowledge
Technique testingGeo-referencing/ spatial uncertaintyEcological Niche Factor Analysis Predictive models
Broader Impact
National Park ServiceESRICalifornia Emergency Management AgencyNational Association for Search and RescueWilderness Medical SocietyYosemite Leadership Program at UC MercedYosemite FundYosemite Search and Rescue
Potential Collaborators
ESRIFeature article
in ArcUser Magazine
YOSAR wins Special Achievement in GIS award
Any Questions?