A review of recent advances in risk analysis for wildfire management

Miller, Carol; Ager, Alan A.

doi:10.1071/wf11114

Cited by 211 publications

(128 citation statements)

References 86 publications

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“…This is similar to Scott (2006), who characterised wildfire hazard with burn probability, fireline intensity and a composite index. It is, however, in disagreement with the common approach of tying hazard only to the contribution of the forest fuels to fire danger (Hardy 2005;Miller and Ager 2013).…”

Section: Risk Assessment Frameworkmentioning

confidence: 96%

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Probabilistic prediction of wildfire economic losses to housing in Cyprus using Bayesian network analysis

Papakosta

Xanthopoulos²,

Straub

2017

Int. J. Wildland Fire

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Abstract. Loss prediction models are an important part of wildfire risk assessment, but have received only limited attention in the scientific literature. Such models can support decision-making on preventive measures targeting fuels or potential ignition sources, on fire suppression, on mitigation of consequences and on effective allocation of funds. This paper presents a probabilistic model for predicting wildfire housing loss at the mesoscale (1 km 2 ) using Bayesian network (BN) analysis. The BN enables the construction of an integrated model based on causal relationships among the influencing parameters jointly with the associated uncertainties. Input data and models are gathered from literature and expert knowledge to overcome the lack of housing loss data in the study area. Numerical investigations are carried out with spatiotemporal datasets for the Mediterranean island of Cyprus. The BN is coupled with a geographic information system (GIS) and the resulting estimated house damages for a given fire hazard are shown in maps. The BN model can be attached to a wildfire hazard model to determine wildfire risk in a spatially explicit manner. The developed model is specific to areas with house characteristics similar to those found in Cyprus, but the general methodology is transferable to any other area, as well as other damages.

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Section: Risk Assessment Frameworkmentioning

confidence: 96%

“…Wildfire risk is commonly defined as the expected net value loss in a particular geographic area and time period (Finney 2005). In recent years, significant effort has been devoted to fire risk analysis across wildlands, leading to methodological advances and the development of advanced tools (Finney 2006;Miller and Ager 2013).…”

Section: Introductionmentioning

confidence: 99%

Probabilistic prediction of wildfire economic losses to housing in Cyprus using Bayesian network analysis

Papakosta

Xanthopoulos²,

Straub

2017

Int. J. Wildland Fire

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“…Many of the recent advances in risk assessments are a result of improvements in computer software, systems integration, readily available spatial data and simulation modelling technology. Miller and Ager (2013) present a review of recent advances in risk analysis approaches to wildland fire management and planning, with a focus on advances in data, modelling and analyses. Fire likelihood is represented as either ignition probability or burn probability.…”

Section: Risk Analysis For Wildfire Managementmentioning

confidence: 99%

“…The need for model verification and validation was a common theme (e.g. Goodrick et al 2013;Hyde et al 2013;Miller and Ager 2013), and the Smoke and Model Intercomparison Project (SEMIP) was cited as an excellent example of this work. The need for improved decision support systems to integrate new knowledge for fire and fuel applications surfaced in several papers (Goodrick et al 2013;Hyde et al 2013;Miller and Ager 2013).…”

Section: Themesmentioning

confidence: 99%

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Advances in understanding and managing wildland fire: communicating wildland fire research to land-management practitioners

Mickler¹,

Cissel²,

Laurence³

2013

Int. J. Wildland Fire

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Abstract. The health and function of forest ecosystems throughout the world include periodic exposure to disturbances such as fire. Fire has been instrumental in the evolution of large segments of flora and fauna and in preventing fuel accumulations that resulted in extreme fire behaviour and ecosystem degradation. However, wildland fuels have been accumulating over several of the past decades because of suppression-orientated wildland fire policies, silvicultural and grazing practices, invasions of invasive species, increased density and range of flammable indigenous plants, landscape fragmentation, and related natural and anthropogenic causes. The additional fuels have contributed to increased severe fire behaviour, fire intensity, forest mortality, and post-fire soil damage and erosion. The aftermath of severe wildland fires include ecosystems degraded by extreme fire temperatures and duration, reductions in ecosystem function, altered forest structure, altered natural fire regimes, and increased wildfire risk and imminent threats to life and property from uncontrollable fires. We review 10 years of advances in fire science in the eight papers presented in this Special Issue. The studies and reviews are compiled to present the diverse disciplines of fire science that range from the social science of the public's perception of fire to basic research on the theory of fire spread.

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Low‐ and moderate‐severity fire offers key insights for landscape restoration in ponderosa pine forests

Cannon

Warnick

Elliott

et al. 2021

Ecological Applications

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Restoration goals in fire‐prone conifer forests include mitigating fire hazard while restoring forest structural components linked to disturbance resilience and ecological function. Restoration of overstory spatial pattern in forests often falls short of management objectives due to complexities in implementation, regulation, and available data. When historical data is available, it is often collected at plots too small to inform coarse‐scale metrics like gap size and structure of tree patches (e.g., 1 ha). Principles of ecological forestry typically emphasize overstory removal patterns that emulate those of natural disturbances. So, low‐ and moderate‐severity portions of contemporary wildfires may serve as a guide to restoration treatments where mixed‐severity fires occur. Here, we compare forest spatial pattern and configuration in 15 mechanical restoration treatments and low‐ and moderate‐severity portions of three wildfires in ponderosa pine‐dominated forests to determine how they differ in spatial pattern. We obtained satellite imagery of restoration treatments and wildfires and used supervised classification to differentiate canopy and openings. We assessed elements of landscape structure including canopy and gap cover, gap attributes, and landscape heterogeneity for each disturbance type. We found that both mechanical restoration treatments and low‐ and moderate‐severity portions of wildfires reduced forest cover, increased gap cover, and altered pattern and arrangement of gaps relative to undisturbed areas, though the magnitude of changes were greatest in the burned sites. Low‐ and moderate‐severity wildfire consistently increased landscape heterogeneity, but mechanical treatments did not. This suggests that a greater emphasis on increasing gap and patch spatial structure may make mechanical treatments more congruent with natural disturbances. Outcomes of low‐ and moderate‐severity portions of wildfires may provide important information upon which to base management prescriptions where reference data on landscape patterns is unavailable.

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A review of recent advances in risk analysis for wildfire management

Cited by 211 publications

References 86 publications

Probabilistic prediction of wildfire economic losses to housing in Cyprus using Bayesian network analysis

Probabilistic prediction of wildfire economic losses to housing in Cyprus using Bayesian network analysis

Advances in understanding and managing wildland fire: communicating wildland fire research to land-management practitioners

Low‐ and moderate‐severity fire offers key insights for landscape restoration in ponderosa pine forests

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