Risk modelling for remote communities : an Inuit-driven Bayesian network approach to enhance search and rescue operations in Arctic Canada
Belton, Ian and Quigley, John and Rudman, Archie and Kikkert, Peter and Howick, Susan and Walls, Lesley; (2025) Risk modelling for remote communities : an Inuit-driven Bayesian network approach to enhance search and rescue operations in Arctic Canada. In: Proceedings of the 22nd ISCRAM Conference. ISCRAM, CAN. (https://doi.org/10.59297/bz4zhp86)
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Abstract
The Canadian Arctic's vast and unforgiving landscape presents unique challenges for Search and Rescue (SAR) operations, particularly in supporting the SAR volunteers in remote Inuit communities who face extreme conditions with limited resources. This study addresses the need for a culturally informed, probabilistic model that can enhance SAR effectiveness in Nunavut and Nunavik by enabling data-driven strategic planning and resource allocation. The paper introduces a novel Bayesian Network (BN) risk model that aims to capture the complexities involved in the Arctic ground SAR system. The model, developed through extensive community engagement, highlights the interdependencies between environmental conditions, resource availability, and SAR outcomes. By incorporating local knowledge and addressing systemic risks, the BN model offers a quantitative framework for SAR decision-making and policy development, aiming to improve the safety and resilience of Northern communities in the face of climate change and evolving geopolitical challenges. This work contributes to the wider SAR literature by offering a replicable approach for risk assessment and decision-making rooted in community expertise.
ORCID iDs
Belton, Ian
ORCID: https://orcid.org/0000-0002-2479-6563, Quigley, John
ORCID: https://orcid.org/0000-0002-7253-8470, Rudman, Archie
ORCID: https://orcid.org/0009-0003-7119-4498, Kikkert, Peter, Howick, Susan
ORCID: https://orcid.org/0000-0002-0796-7981 and Walls, Lesley
ORCID: https://orcid.org/0000-0001-7016-9141;
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Item type: Book Section ID code: 93050 Dates: DateEvent17 May 2025PublishedSubjects: Social Sciences > Industries. Land use. Labor > Risk Management
Science > Mathematics > Probabilities. Mathematical statisticsDepartment: Strathclyde Business School > Management Science
Faculty of Engineering > Civil and Environmental EngineeringDepositing user: Pure Administrator Date deposited: 09 Jun 2025 09:08 Last modified: 05 Apr 2026 00:27 URI: https://strathprints.strath.ac.uk/id/eprint/93050
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