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- Publisher Website: 10.1016/j.cor.2021.105252
- Scopus: eid_2-s2.0-85102058115
- WOS: WOS:000674263400006
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Article: Downstream protection value: Detecting critical zones for effective fuel-treatment under wildfire risk
Title | Downstream protection value: Detecting critical zones for effective fuel-treatment under wildfire risk |
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Authors | |
Keywords | Fuel-treatment Wildfire susceptibility Optimization Simulation Decision support system |
Issue Date | 2021 |
Publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/cor |
Citation | Computers & Operations Research, 2021, v. 131, p. article no. 105252 How to Cite? |
Abstract | The destructive potential of wildfires has been exacerbated by climate change, causing their frequencies and intensities to continuously increase globally. Generating fire-resilient landscapes via efficient and calculated fuel-treatment plans is critical to protecting native forests, agricultural resources, biodiversity, and human communities. To tackle this challenge, we propose a framework that integrates fire spread, optimization, and simulation models. We introduce the concept of Downstream Protection Value (DPV), a flexible metric that assays and ranks the impact of treating a unit of the landscape, by modeling a forest as a network and the fire propagation as a tree graph. Using our open-source decision support system, custom performance metrics can be optimized to minimize wildfire losses, obtaining effective treatment plans. Experiments with real forests show that our model is able to consistently outperform alternative methods and accurately detect high-risk and potential ignition areas, focusing the treatment on the most critical zones. Results indicate that our methodology is able to decrease the expected area burned and fire propagation rate by more than half in comparison to alternative methods under ignition and weather uncertainty. |
Persistent Identifier | http://hdl.handle.net/10722/310171 |
ISSN | 2023 Impact Factor: 4.1 2023 SCImago Journal Rankings: 1.574 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Pais, C | - |
dc.contributor.author | Carrasco, J | - |
dc.contributor.author | Elimbi Moudio, P | - |
dc.contributor.author | Shen, ZJM | - |
dc.date.accessioned | 2022-01-24T02:24:54Z | - |
dc.date.available | 2022-01-24T02:24:54Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Computers & Operations Research, 2021, v. 131, p. article no. 105252 | - |
dc.identifier.issn | 0305-0548 | - |
dc.identifier.uri | http://hdl.handle.net/10722/310171 | - |
dc.description.abstract | The destructive potential of wildfires has been exacerbated by climate change, causing their frequencies and intensities to continuously increase globally. Generating fire-resilient landscapes via efficient and calculated fuel-treatment plans is critical to protecting native forests, agricultural resources, biodiversity, and human communities. To tackle this challenge, we propose a framework that integrates fire spread, optimization, and simulation models. We introduce the concept of Downstream Protection Value (DPV), a flexible metric that assays and ranks the impact of treating a unit of the landscape, by modeling a forest as a network and the fire propagation as a tree graph. Using our open-source decision support system, custom performance metrics can be optimized to minimize wildfire losses, obtaining effective treatment plans. Experiments with real forests show that our model is able to consistently outperform alternative methods and accurately detect high-risk and potential ignition areas, focusing the treatment on the most critical zones. Results indicate that our methodology is able to decrease the expected area burned and fire propagation rate by more than half in comparison to alternative methods under ignition and weather uncertainty. | - |
dc.language | eng | - |
dc.publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/cor | - |
dc.relation.ispartof | Computers & Operations Research | - |
dc.subject | Fuel-treatment | - |
dc.subject | Wildfire susceptibility | - |
dc.subject | Optimization | - |
dc.subject | Simulation | - |
dc.subject | Decision support system | - |
dc.title | Downstream protection value: Detecting critical zones for effective fuel-treatment under wildfire risk | - |
dc.type | Article | - |
dc.identifier.email | Shen, ZJM: maxshen@hku.hk | - |
dc.identifier.authority | Shen, ZJM=rp02779 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.cor.2021.105252 | - |
dc.identifier.scopus | eid_2-s2.0-85102058115 | - |
dc.identifier.hkuros | 331480 | - |
dc.identifier.volume | 131 | - |
dc.identifier.spage | article no. 105252 | - |
dc.identifier.epage | article no. 105252 | - |
dc.identifier.isi | WOS:000674263400006 | - |
dc.publisher.place | United Kingdom | - |