A graph-based optimization framework for firebreak planning in wildfire-prone landscapes
Firebreaks and fuel treatments are critical means for the reduction of wildfire threat and damage to human infrastructure in forest landscapes. However, the uncertain behavior of wildfires makes the planning of firebreaks challenging, especially when available resources are insufficient to treat all...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-12-01
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| Series: | Ecological Informatics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1574954125003486 |
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| author | Denys Yemshanov Ning Liu Eric W. Neilson Daniel Thompson Frank H. Koch |
| author_facet | Denys Yemshanov Ning Liu Eric W. Neilson Daniel Thompson Frank H. Koch |
| author_sort | Denys Yemshanov |
| collection | DOAJ |
| description | Firebreaks and fuel treatments are critical means for the reduction of wildfire threat and damage to human infrastructure in forest landscapes. However, the uncertain behavior of wildfires makes the planning of firebreaks challenging, especially when available resources are insufficient to treat all locations under wildfire threat. We present a fire propagation graph approach that utilizes directed acyclic graphs to track the possible spread of wildfires from their ignition locations and estimate the impacts of firebreak placement on the possible burn area. The fire propagation graphs depict plausible fire spread within the fire footprints created with a spatial fire growth model. We integrated the fire propagation graph concept into an optimization model that allocates firebreaks in a complex landscape. We compared two firebreak planning strategies. The first strategy reduces the overall connectivity between patches with fuel and minimizes the number of location pairs between which wildfire spread is possible. The second strategy minimizes the possible burn area across the landscape by tracking the impact of firebreaks on the potential fire spread through a large set of fire propagation graphs that depict plausible fire scenarios. We also evaluated the problem that combines both strategies.We illustrated the approach with the planning of wildfire mitigation measures in the Red Rock-Prairie Creek area of Canada, a complex fire-prone landscape. The firebreak solutions were effectively able to reduce both the potential burn area and the connectivity between locations with fuel. The graph-based depiction of the uncertain wildfire spread helped assess the landscape-level impacts of local firebreak allocation decisions and uncover the tradeoffs between different firebreak planning strategies. The approach could assist wildfire mitigation planning in other regions. |
| format | Article |
| id | doaj-art-dc7775f224a049b19c2310bb29eeb1cd |
| institution | Kabale University |
| issn | 1574-9541 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Informatics |
| spelling | doaj-art-dc7775f224a049b19c2310bb29eeb1cd2025-08-20T05:05:52ZengElsevierEcological Informatics1574-95412025-12-019010333910.1016/j.ecoinf.2025.103339A graph-based optimization framework for firebreak planning in wildfire-prone landscapesDenys Yemshanov0Ning Liu1Eric W. Neilson2Daniel Thompson3Frank H. Koch4Natural Resources Canada, Canadian Forest Service, Great Lakes Forestry Centre, 1219 Queen Street East, Sault Ste. Marie, ON, Canada; Corresponding author.Natural Resources Canada, Canadian Forest Service, Great Lakes Forestry Centre, 1219 Queen Street East, Sault Ste. Marie, ON, CanadaNatural Resources Canada, Canadian Forest Service, Northern Forestry Centre, 5320 122 Street, Northwest Edmonton, AB, CanadaNatural Resources Canada, Canadian Forest Service, Great Lakes Forestry Centre, 1219 Queen Street East, Sault Ste. Marie, ON, CanadaUSDA Forest Service, Southern Research Station, Eastern Forest Environmental Threat Assessment Center, Research Triangle Park, NC, USAFirebreaks and fuel treatments are critical means for the reduction of wildfire threat and damage to human infrastructure in forest landscapes. However, the uncertain behavior of wildfires makes the planning of firebreaks challenging, especially when available resources are insufficient to treat all locations under wildfire threat. We present a fire propagation graph approach that utilizes directed acyclic graphs to track the possible spread of wildfires from their ignition locations and estimate the impacts of firebreak placement on the possible burn area. The fire propagation graphs depict plausible fire spread within the fire footprints created with a spatial fire growth model. We integrated the fire propagation graph concept into an optimization model that allocates firebreaks in a complex landscape. We compared two firebreak planning strategies. The first strategy reduces the overall connectivity between patches with fuel and minimizes the number of location pairs between which wildfire spread is possible. The second strategy minimizes the possible burn area across the landscape by tracking the impact of firebreaks on the potential fire spread through a large set of fire propagation graphs that depict plausible fire scenarios. We also evaluated the problem that combines both strategies.We illustrated the approach with the planning of wildfire mitigation measures in the Red Rock-Prairie Creek area of Canada, a complex fire-prone landscape. The firebreak solutions were effectively able to reduce both the potential burn area and the connectivity between locations with fuel. The graph-based depiction of the uncertain wildfire spread helped assess the landscape-level impacts of local firebreak allocation decisions and uncover the tradeoffs between different firebreak planning strategies. The approach could assist wildfire mitigation planning in other regions.http://www.sciencedirect.com/science/article/pii/S1574954125003486Fire propagation treeFireplainFirebreaksWildfire spreadCritical node removalFire growth model |
| spellingShingle | Denys Yemshanov Ning Liu Eric W. Neilson Daniel Thompson Frank H. Koch A graph-based optimization framework for firebreak planning in wildfire-prone landscapes Ecological Informatics Fire propagation tree Fireplain Firebreaks Wildfire spread Critical node removal Fire growth model |
| title | A graph-based optimization framework for firebreak planning in wildfire-prone landscapes |
| title_full | A graph-based optimization framework for firebreak planning in wildfire-prone landscapes |
| title_fullStr | A graph-based optimization framework for firebreak planning in wildfire-prone landscapes |
| title_full_unstemmed | A graph-based optimization framework for firebreak planning in wildfire-prone landscapes |
| title_short | A graph-based optimization framework for firebreak planning in wildfire-prone landscapes |
| title_sort | graph based optimization framework for firebreak planning in wildfire prone landscapes |
| topic | Fire propagation tree Fireplain Firebreaks Wildfire spread Critical node removal Fire growth model |
| url | http://www.sciencedirect.com/science/article/pii/S1574954125003486 |
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