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Advanced Spatial Analysis of Accident Risks in Recreational Boating
Funded by a 2011 Boating Safety Grant from the USCG, Boating Safety Division
Collaborating Partners National Association of State Boating Law Administrators, United States Power Squadrons , Florida Fish and Wildlife Conservation Commission, the Ohio Department of Natural Resources, East Carolina University, Trimble, and GeoEye.
Principal Investigators
Ernest Marshburn, USPS and East Carolina University Richard Moore, Florida Fish and Wildlife Conservation Commission Rodger Norcross, Ohio Department of Natural Resources Tammy Terry, Ohio Department of Natural Resources
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Intellectual Merit
• Two or more boaters same area – why is one involved in an accident and the other is not?
• Accident theory can be used to statistically explain the spatial and temporal qualities of recreational boating accidents.
• Use advanced statistical techniques and GIS to research recreational boating accident data.
• These techniques enable key variables to be modeled using advanced regression approaches.
• Spatial Autocorrelation, Heterogeneity, and Multi-level Interactive Effects will be examined.
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Broader Impact
• Contemporary boating accident research focuses on fatalities. – A broader perspective concerning recreational boating
risk has not yet been attained.
– boating accident models also suffer from the severest forms of specification error; left out variables.
• Combined consideration of environmental, human, and technological factors is needed to:– fully investigate all significant variables influencing recreational
boating accidents
– Explore interrelationships involving multi-level interactive effects.
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Why Are We Conducting this Study?
To determine the:
1. effects of environmental factors on recreational boating accidentsand reveal any spatio-temporal patterns that emerge.
2. environmental conditions w/in which human factors influence the spatio-temporal distribution of recreational boating accidents.
3. environmental conditions w/in which technological factors influence the spatio-temporal distribution of recreational boating accidents.
4. if discrete categories of temporal variation involving recreational boating accidents can be statistically captured, and if so, their effects.
Where and When do recreational boating accidents occur … and … Why do they occur in those locations?
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Recreational Boating Accident Research Framework
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Recreational Boating Accident Reflections • Recreational Boating Accidents are routinely attributed to:
– most frequently human factors,
– less frequently technological factors, and
– rarely environmental factors.
– illustrate point with photo
• Research opportunity: exploring recreational boating accidents from an environmental (specifically spatial) perspective, using OWS data.
• Need on-water survey (OWS) non-accident data to normalize BARD.
OOPS …
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On-Water: Boating Safety Stop Survey
Trimble Nomad 800L(printer not shown)
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Satellite Imagery
Tampa Bay, Florida Research Site
Sandusky Bay, Ohio Research Site
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Research Site: Tampa Bay, FL
103.3 sq. km. research area
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Research Site: Sandusky Bay, OH
138.2 sq. km research area
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Satellite ImageryTampa Bay, Florida Research Site Sandusky Bay, Ohio Research Site
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Satellite ImageryTampa Bay, Florida Research Site
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Satellite ImageryTampa Bay, Florida Research Site
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Satellite ImageryTampa Bay, Florida Research Site
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Satellite ImagerySandusky Bay, Ohio Research Site
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Satellite ImagerySandusky Bay, Ohio Research Site
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Analytical Methods
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Analytical Methods
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Data Collection• Research operationalized through
boating accident report data (USCG), hi-resolution satellite imagery (GeoEye, Inc.), waterway characteristics, boat characteristics, boat operator demographics, and on-water survey data as illustrated in Table 1.
• The on-water survey data is being collected in collaboration with Florida Fish and Wildlife Conservation Commission (FWC) and Ohio Division of Natural Resources (ODNR) by law enforcement officers operating within the research site.
• Will be looking to include other states as we move forward.
Table 1: Independent Variable Matrix
Key Variables DS
-1D
S-2
DS
-3
Environmental variablesTraffic - - -
Speed - x xDensity - x -
Navigation Channel Variation - - -Width - x xDepth - x xOrientation - x xChannel Complexity - x x
Sea State - - -Current x x xWind x x xWaves x x xVisibility x x x
Technological variables - - -Boat Propulsion x - xBoat Length x - xBoat Type x - xNavigation Tools x - x
Human variables - - -Driver Age x - xBoater Education x - xBoater Experience x - xBoater Ethnicity x - xLife Jacket Wear x - x
Temporal variables - - -Peak Month x x xPeak Day of Week x x x
DB-1: BARD DataDB-2: Remotely Sensed Imagery/DataDB-3: On-Water-Survey
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Advanced data fusion techniques
Fused GIS DatabaseDataset 4
U.S. Coast Guard Boating Accident Report
Data (BARD)
Dataset 1
GeoEye Satellite Imagery,NWS Weather-Sea State Data, and NOAA Charts
Dataset 3
Fig. 3: Advanced Data Fusion Model & Database Structure
Dataset 2Florida Fish and Wildlife
Conservation Commission and Ohio Department of Natural Resources
On-Water Survey
– on-water survey enables normalization of the 2011-12 on-water boating population.
– better representation of independent accident domain variables achieved.
– 0.5 to 0.8m resolution satellite imagerywill provide sufficient optical clarity to ground truth key attributes.
– GIS data fusion techniques combined with federal, state, and commercial data will assure proper data synthesis and model development.
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Analytical MethodsThe primary problem is to relate the space-time array (ijt) to the factors representing the environmental, human, and technological dimensions. This function is represented as:
ijtA f , ,ijt ijt ijtenvironmental human technological
Fig. 5: Recreational Boat Accident Research Model
Cell = Unit of Observation (100m x 100m)
Boating Accident (BARD data)
Density measured as the number of boats within 400m of any cell centroid
ijtA
where A represents the presence or absence of a recreational boating accident in cell (ij) at time (t).
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Table 1: Project TimelineAdvanced Spatial Analysis of Accident Risks in Recreational Boating
FY Prj TL Month#
DaysMo.
Observation Classification
(data collection)
Paper OWS
Electronic OWS
Satellite Imagery
BARD Data
NOAA Data
Cumul OWS
Obs.(1)
Cumul OWS
Obs.(1)
USCG Prog. Rept.
FL OH2011 1 Apr test/impl
2 May 31 Peak x x x x 93 933 Jun 30 Peak x x x x x 183 183
Y1 4 Jul 31 Peak x x x x x 276 276 15 Aug 31 Peak x x x x 369 3696 Sept 30 Off-Peak x x x x x 459 4597 Oct 31 Off-Peak x x x x x 552 5528 Nov 30 Off-Peak x x x x 642 642 29 Dec 31 Off-Peak x x x x 735 735
2012 10 Jan 31 Off-Peak x x x x 828 82811 Feb 28 Off-Peak x x x x 912 91212 Mar 31 Off-Peak x x x x x 1005 1005 313 Apr 30 Off-Peak x x x x x 1095 109514 May 31 Peak x x x x 1188 118815 Jun 30 Peak x x x x x 1278 1278
Y2 16 Jul 31 Peak x x x x x 1371 1371 417 Aug 31 Peak x x x x 1464 146418 Sept Analytics19 Oct Analytics20 Nov Analytics 521 Dec Analytics
2013 22 Jan Analytics23 Feb Analytics24 Mar 625 Apr
Preliminary Findings: Presented to USCG @ NASBLA Spring Conf.Final Report: USCG, USACoE, NASBLA, FWC, & ODNR leadership
Research Data Collection
Presented @ Spring NASBLA Workshop
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General Observations - Lessons Learned• Participating officers need time to adapt to electronic data collection technology
but that once implemented and applied as part of the patrol routine, the point and click method for collecting recreational boating data is effective and efficient.
• Data completeness reinforcement and encouragement need to be inserted into supervisory briefings at regular intervals to ensure that data capture requirements are fully met.
• Participating officers are more enthusiastic about and more likely to meet daily capture benchmarks (a minimum of 3 observations per day) using electronic data capture tools rather than paper-based tools.
• It is important to involve all agency staff in the project, not just BLAs and data analysts, enabling better definition of problem areas, issues, and previously unrecognized project details.
• The ODNR team reported that many of the technology issues have been eliminated as a result of project work during this quarter.
• Any additional states that join this project should still be aware of the need for a local project “Coordinator” to provide daily project management and coordination for the participating officers.
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General Observations - Lessons Learned• The use of electronic data capture technologies was observed to have the
additional benefit of creating a safer direct boat operator contact (boating safety stop) for enforcement officers, e.g., officers can generally maintain eye contact with the boat operator without the awkwardness of being in a head-down mode to record observations on paper.
• Sharing project details has helped excite other officers and in fact states about the nature of this project. It has also had the added benefit of promoting creative thinking by both NASBLA and state boating law enforcement groups about how they could employ this technology in ways that advance their missions.
• It is noted that the use of technology requires continuous maintenance to ensure that it is current with respect to officer needs and routines.
• The total number of recreational boat operator observations collected per day by officers, should be allowed for seasonal fluctuations in officer duties which may include enhanced focus on accident investigation and/or OUI contacts during the peak season, taking time away from their ability to collect survey data.
• The potential for collecting warning and/or citation data electronically is recognized as a “value-added” program benefit.
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Project Summary• Questions
• Will go into more detail on Friday during the ERAC meeting
• If you are interested in joining this project in the future, feel free to contact me at:
Ernest G. Marshburn, Director Research DevelopmentOffice of the Vice Chancellor, Research & Graduate Studies2200 South Charles Blvd., Greenville Center, Rm. 1504East Carolina UniversityGreenville NC 27858-4353•Office: 252.328.9014•Cell: 252.714.5170•Fax: 252.328.2769