Assessing fire risk using Monte Carlo simulations of fire spread

Carmel, Yohay; Paz, Shlomit; Jahashan, Faris; Shoshany, Maxim

doi:10.1016/j.foreco.2008.09.039

Cited by 146 publications

(103 citation statements)

References 32 publications

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“…This is a concept similar to FLAMMAP, which computes various potential fire characteristics (Finney, 2006). A more comprehensive approach to fire risk would need to also involve the probability of fire in any given location, similar to in, e.g., the Wildland Fire Decision Support System (WFDSS, http://wfdss.usgs.gov), or Carmel et al (2009).…”

Section: Mapping the Severity Of A Potential Firementioning

confidence: 99%

“…The third source is the US Geological Survey (USGS) 1 km resolution vegetation map, which pads the missing data around the Israeli border and inside the Palestinian authority. Since Rothermel's rate of spread model was not developed for Mediterranean conditions, the system supports rate of spread correction factors in order to enable applying the modified rates of spread, as suggested by Carmel et al (2009). Specifically, the rates of spread are reduced by a factor of 2 for Anderson (1982) fuel models 1 and 4, and by a factor of 4 for fuel model 10.…”

Section: Operational Use In Israelmentioning

confidence: 99%

See 1 more Smart Citation

Recent advances and applications of WRF–SFIRE

Mandel

Amram

Beezley

et al. 2014

Nat. Hazards Earth Syst. Sci.

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Abstract. Coupled atmosphere-fire models can now generate forecasts in real time, owing to recent advances in computational capabilities. WRF-SFIRE consists of the Weather Research and Forecasting (WRF) model coupled with the fire-spread model SFIRE. This paper presents new developments, which were introduced as a response to the needs of the community interested in operational testing of WRF-SFIRE. These developments include a fuel-moisture model and a fuel-moisture-data-assimilation system based on the Remote Automated Weather Stations (RAWS) observations, allowing for fire simulations across landscapes and time scales of varying fuel-moisture conditions. The paper also describes the implementation of a coupling with the atmospheric chemistry and aerosol schemes in WRF-Chem, which allows for a simulation of smoke dispersion and effects of fires on air quality. There is also a data-assimilation method, which provides the capability of starting the fire simulations from an observed fire perimeter, instead of an ignition point. Finally, an example of operational deployment in Israel, utilizing some of the new visualization and datamanagement tools, is presented.

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Section: Mapping the Severity Of A Potential Firementioning

confidence: 99%

Section: Operational Use In Israelmentioning

confidence: 99%

Recent advances and applications of WRF–SFIRE

Mandel

Amram

Beezley

et al. 2014

Nat. Hazards Earth Syst. Sci.

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show abstract

“…Modeling fire spread allows the computation of fire travel pathways and fire size distributions, and a robust characterization of the spatial process. Simulating fire growth across heterogeneous landscapes can identify emergent behavioral properties that may not be predictable and may not be captured with localized estimates of fire behavior (Carmel et al, 2009;Parisien et al, 2007). Modeling fire www.intechopen.com spread also allows for estimates of fireline intensity as a function of fire spread direction (flanking, heading, or backing).…”

Section: Wildfire Hazardmentioning

confidence: 99%

The Science and Opportunity of Wildfire Risk Assessment

Thompson¹,

Ager²,

Finney³

et al. 2012

Novel Approaches and Their Applications in Risk Assessment

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“…Forest fire risk mainly depends on various factors such as forest vegetation structures, topographic features, and climatic parameters (Carmel et al, 2009). Forest vegetation structures such as tree species, crown closure, and tree stage are separate factors that influences forest fire ignition and fire severity (Gao et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…Geographical Information System (GIS) techniques integrated with Multi-Criteria Decision Analysis (MCDA) method provides quick and effective solutions to such complex spatial problems (Jaiswal et al, 2002;Carmel et al, 2009). Analytical Hierarchy Process (AHP) is one of the widely used multi-criteria decision-support methods used in the field of forestry (Coulter et al, 2006;Gülci, 2014).…”

Section: Introductionmentioning

confidence: 99%

Gis-Based Multi-Criteria Decision Analysis for Forest Fire Risk Mapping

Akay

ERDOĞAN

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The forested areas along the coastal zone of the Mediterranean region in Turkey are classified as first-degree fire sensitive areas. Forest fires are major environmental disaster that affects the sustainability of forest ecosystems. Besides, forest fires result in important economic losses and even threaten human lives. Thus, it is critical to determine the forested areas with fire risks and thereby minimize the damages on forest resources by taking necessary precaution measures in these areas. The risk of forest fire can be assessed based on various factors such as forest vegetation structures (tree species, crown closure, tree stage), topographic features (slope and aspect), and climatic parameters (temperature, wind). In this study, GIS-based Multi-Criteria Decision Analysis (MCDA) method was used to generate forest fire risk map. The study was implemented in the forested areas within Yayla Forest Enterprise Chiefs at Dursunbey Forest Enterprise Directorate which is classified as first degree fire sensitive area. In the solution process, "extAhp 2.0" plug-in running Analytic Hierarchy Process (AHP) method in ArcGIS 10.4.1 was used to categorize study area under five fire risk classes: extreme risk, high risk, moderate risk, and low risk,. The results indicated that 23.81% of the area was of extreme risk, while 25.81% was of high risk. The result indicated that the most effective criterion was tree species, followed by tree stages. The aspect had the least effective criterion on forest fire risk. It was revealed that GIS techniques integrated with MCDA methods are effective tools to quickly estimate forest fire risk at low cost. The integration of these factors into GIS can be very useful to determine forested areas with high fire risk and also to plan forestry management after fire.

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Assessing fire risk using Monte Carlo simulations of fire spread

Cited by 146 publications

References 32 publications

Recent advances and applications of WRF–SFIRE

Recent advances and applications of WRF–SFIRE

The Science and Opportunity of Wildfire Risk Assessment

Gis-Based Multi-Criteria Decision Analysis for Forest Fire Risk Mapping

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