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dc.contributor.authorStoddard, Mark Andrew
dc.date.accessioned2024-08-02T14:38:02Z
dc.date.available2024-08-02T14:38:02Z
dc.date.issued2024-07-30
dc.identifier.urihttp://hdl.handle.net/10222/84377
dc.description.abstractMaritime traffic in the Arctic region is increasing as northern communities grow, tourism accelerates, and large resource development projects enter operation. Consequently, the number of vessels exposed to the navigational challenges and risks in the polar region will continue to rise. The situation is further complicated by fast-changing sea ice conditions due in part to climate change. This thesis explores the state of the art in sea ice risk assessment and transit time estimation in ice-covered waters, and presents a strategic route planning methodology that integrates several concepts from these two active areas of research. This methodology is used to enable the computation of innovative visual representations of marine-based search and rescue response time throughout the year in the Canadian Arctic. This is achieved by combining statistical methods, advanced geospatial data analysis, and network analysis techniques to overcome several computational challenges specific to route generation and transit time estimation in ice-covered waters. The results indicate that there is a statistical relationship between reported vessel speed from Automatic Information System (AIS) and the operational risk from sea ice determined at the time of reporting using the Polar Operational Limit Assessment Risk Indexing System (POLARIS). This relationship is used to specify the expected ship speed in different sea ice risk categories, which is then used to compute the fastest route and expected transit time between geographically separated locations in ice-covered waters. The model can generate the fastest route at different times of year and for different ship ice classes. This is achieved by exploiting the relationship that exists between vessel speed and the outcome of the POLARIS assessment. The methods and results presented in this thesis are shown to support a variety of strategic route analysis applications and provide the necessary computational toolset to apply advanced area-based management approaches to maritime search and rescue response planning.en_US
dc.language.isoenen_US
dc.subjectRisken_US
dc.subjectArcticen_US
dc.subjectOptimizationen_US
dc.subjectNavigationen_US
dc.subjectSearch and Rescueen_US
dc.titleEstimating Ship Transit Times in Ice-Covered Waters for Strategic Route Analysis and Search and Rescue Response Planningen_US
dc.date.defence2024-07-04
dc.contributor.departmentDepartment of Industrial Engineeringen_US
dc.contributor.degreeDoctor of Philosophyen_US
dc.contributor.external-examinerDr. Brian Veitchen_US
dc.contributor.thesis-readerDr. Alireza Ghasemien_US
dc.contributor.thesis-readerDr. Laurent Etienneen_US
dc.contributor.thesis-readerDr. Floris Goerlandten_US
dc.contributor.thesis-readerDr. Kevin Quigleyen_US
dc.contributor.thesis-supervisorDr. Ronald Peloten_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.manuscriptsYesen_US
dc.contributor.copyright-releaseYesen_US
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