Location Analytics to Support Wildfire Response Prepositioning

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dc.contributor.author Baik, Jiwon
dc.contributor.author Murray, Alan
dc.date.accessioned 2023-12-26T18:47:35Z
dc.date.available 2023-12-26T18:47:35Z
dc.date.issued 2024-01-03
dc.identifier.isbn 978-0-9981331-7-1
dc.identifier.other 520a356a-33d7-4fda-a91d-99664c810303
dc.identifier.uri https://hdl.handle.net/10125/107069
dc.language.iso eng
dc.relation.ispartof Proceedings of the 57th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Location Intelligence Research in System Sciences
dc.subject geographic information science
dc.subject location analytics
dc.subject spatial optimization
dc.subject wildfire risk management
dc.title Location Analytics to Support Wildfire Response Prepositioning
dc.type Conference Paper
dc.type.dcmi Text
dcterms.abstract This study addresses wildfire resource prepositioning in a region. Location analytics is utilized for prepositioning decision-making, relying on bi-objective spatial optimization to identify a strategic location for monitoring and response that considers two objectives: optimizing the visibility of potential ignition sites and optimizing response access. The study broadens the conventional definition of coverage by incorporating visibility from the preposition. Despite the inherent complexity of the problem, the proposed solution approach guarantees the identification of the complete set of Pareto optimal solutions in an efficient manner, supporting real-time decision-making. This research contributes significantly to spatial decision-making by integrating viewshed analysis into location analytics. Additionally, the approach has broad applications in various domains, including facility location planning, wireless network design, environmental monitoring, and urban planning. To facilitate decision-making, an interactive web application (www.wri-ucsb.com:8000) is developed, allowing the selection of specific regions of interest and model parameter refinement.
dcterms.extent 10 pages
prism.startingpage 5681
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