Mapping lightning/human-caused wildfires occurrence under ignition point location uncertainty

Amatulli, Giuseppe; Pérez‐Cabello, Fernando; Fernández, Juan Ramón de la Riva

doi:10.1016/j.ecolmodel.2006.08.001

Cited by 114 publications

(86 citation statements)

References 31 publications

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“…A consensus regarding the concept of wildfire risk does not exist. Bachmann and Allgöwer (1999) have already addressed that issue, pointing out that "the somewhat inconsiderate use of the various terms "danger", "hazard", and "risk" may result in misunderstandings that can have fatal consequences" (op.cit., p. 1). Indeed, if a common understanding of what is hazard and what is risk does not exist, we might end up using products in an erroneous way: wildfire risk maps, containing financial data, cannot be read as direct…”

Section: The Conceptual Frameworkmentioning

confidence: 99%

“…Some attempts have been made to model susceptibility by means of different methods, like nearest-neighbourhood. Such is the case of Amatulli et al (2007) who applied interpolation techniques to map lightning/human-caused wildfires, or Durão et al (2010) whose work, dealing with the Canadian FWI system, tried to assess the probability of fire in a given region by running simulations. Apart from the somewhat static approach of susceptibility assessments, other authors have explored the correlations of wildfires and weather conditions, such as in Pereira et al (2005), Trigo et al (2006) and Le Page et al (2008).…”

Section: Introductionmentioning

confidence: 99%

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Assessment and validation of wildfire susceptibility and hazard in Portugal

Verde

Zêzere

2010

Nat. Hazards Earth Syst. Sci.

105

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Abstract.A comprehensive methodology to assess forest fire susceptibility, that uses variables of strong spatial correlation, is presented and applied for the Portuguese mainland. Our study is based on a thirty-year chronological series of burnt areas. The first twenty years (1975)(1976)(1977)(1978)(1979)(1980)(1981)(1982)(1983)(1984)(1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994) are used for statistical modelling, and the last ten (1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004) are used for the independent validation of results. The wildfire affected areas are crossed with a set of independent layers that are assumed to be relevant wildfire conditioning factors: elevation, slope, land cover, rainfall and temperature. Moreover, the wildfire recurring pattern is also considered, as a proxy variable expressing the influence of human action in wildfire occurrence. A sensitivity analysis is performed to evaluate the weight of each individual theme within the susceptibility model. Validation of the wildfire susceptibility models is made through the computation of success rate and prediction rate curves. The results show that it is possible to have a good compromise between the number of variables within the model and the model predictive power. Additionally, it is shown that integration of climatic variables does not produce any relevant increase in the prediction capacity of wildfire susceptibility models. Finally, the prediction rate curves produced by the independent cross validation are used to assess the probabilistic wildfire hazard at a scenario basis, for the complete mainland Portuguese territory.

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Section: The Conceptual Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment and validation of wildfire susceptibility and hazard in Portugal

Verde

Zêzere

2010

Nat. Hazards Earth Syst. Sci.

105

View full text Add to dashboard Cite

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“…Although kernel estimates have been used previously to study the spatial distribution of forest fires incidence (Díaz-Avalos and Alvarado, 1998; Koutsias et al,2004; de la Riva et al, 2004; Amatulli et al;2004), those are only nonparametric estimators and are not useful for spatial prediction nor to asses the existence of association between wildfire incidence to suspected risk factors. Parametric models such as the ones fitted in our study besides providing predictive estimators for the association between the intensity function of wildfire incidence and are also useful to asses the effect of changes of those factors on such intensity function.…”

Section: Discussionmentioning

confidence: 99%

Spatial point process modeling applied to the assessment of risk factors associated with forest wildfires incidence in Castellón, Spain

et al. 2016

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During the last decades the mediterranean zone in Europe has experienced an increment in the incidence of forest wildfires. This increase is partly explained by higher mean temperature and lower relative humidity, whilst socio-economic change has lead to the abandonment of farms, resulting in an increase in an unusual accumulation of forest fuels, increasing the risk of wildfires. Mapping wildfire risk is highly important because wildfires are known to potentially lead to landscape changes and to modify fire regime by inducing potential changes in vegetation composition. Also, they pose a hazard to human property and life. Maps of wildfire risk based on statistical models are provide a measure of uncertainty for the inferences derived from such risk maps, leaving a quantitative error margin for managers and decision takers. Further, some of the model parameters often have a physical or a biological interpretation which can give ecologists and forest engineers answers In this paper we analyze the incidence of wildfires in the province of Castellón, in Spain in order to identify risk factors associated to wildfire incidences during the years [2001][2002][2003][2004][2005][2006]. We used the discrete nature of wildfire events to build such models using point process theory and methods and included information about elevation, slope, aspect, land use and distance to nearest road as covariates in our modeling process. Our results show that wildfire risk in Castellón is associated to all the covariates considered, and that three land use categories have the highest risk of wildfire incidence. Also,wildfire incidences are not independent and some degree of interaction exists, which indicates that the commonly used Poisson point process models are not applicable in this case, but instead Area-Interaction models should be considered.

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“…Logistic regression is one of the most frequently used methods (Andrews et al 2003, Vasconcelos et al 2001, Chuvieco et al 2003, Amatulli et al 2007, Brosofske et al 2007, Zhang et al 2010. It has been used to develop regional models with a large spatial extent (Chuvieco et al 1999, Martinez et al 2009) as well as for developing models on a local scale (Vega-Garcia et al 1995, Vasconcelos et al 2001.…”

Section: Parameter and Model Selectionmentioning

confidence: 99%

“…1 - Cardille et al 2001, Leone et al 2003, Chuvieco et al 2003, Vega-Garcia et al 1995, Brosofske et al 2007, Amatulli et al 2007, Vilar et al 2010. Based on the background of these studies, some 59 socio-economic parameters that were assumed to be characteristic for Austrian conditions were chosen as independent variables to model the potential influence on the fire danger.…”

Section: Parameter and Model Selectionmentioning

confidence: 99%

Modeling human-caused forest fire ignition for assessing forest fire danger in Austria

Arndt¹,

Vacik²,

Koch³

et al. 2013

iForest

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© iForest -Biogeosciences and Forestry IntroductionFire danger is generally understood as the likelihood of a fire to occur (Chuvieco & Congalton 1989). In fire danger assessments the evaluation of the chances of fire ignition is generally done by identifying the contributing factors and their integration into an index quantifying the level of danger (Chuvieco et al. 2003, Sebastián-López et al. 2008. For the probability of a fire to occur, two agents are identified: natural (predominantly lightning) and anthropogenic causes, which are mainly related to human activities. In this context, the probability of human-caused fire ignition is the result of the direct or indirect presence of human activity in the landscape (Martinez et al. 2009). International studies indicate that roughly 90% of forest fires are human-caused, whereas only a small percentage of forest fires have natural causes, i.e., lightning (Cardille et al. 2001, Grissino-Mayer et al. 2004, Mollicone et al. 2006, Vacik et al. 2011. In Europe, human activities account for the majority of fire ignition (Leone et al. 2002, Catry et al. 2009, Martinez et al. 2009).Various goods and services provided by forests such as water supply, carbon sinks, recreation and protection services are most likely to be impacted by wildfires (Wotton et al. 2003, Grissino-Mayer et al. 2004, Brown et al. 2004, Fried et al. 2004, Catry et al. 2009, Dumas et al. 2008, Weibel et al. 2009). Especially in the densely populated European mountain forests the danger of fire ignition is of high significance for the maintenance of its ecosystem goods and services as these ecosystems are very sensitive to environmental changes (Steininger & WeckHannemann 2002, Lindner et al. 2010. Additionally the economic value of goods and services of the alpine region experiences an increased recognition especially through sporting activities and outdoor recreation (Hall & Page 2009). Furthermore, the alpine region is crossed by important transit and trade routes. They aid in promoting tourism in the mountainous regions across Europe (Gambino & Romano 2003, Nordregio 2004, Brauchle 2006, which is leading to an increased development of touristic infrastructure besides the extensive use by naturebased tourism (Gambino & Romano 2003, Heinrichs et al. 2010). The herewith associated rise in pressure on forests through a growing number of tourists is potentially increasing danger of fire ignition. The increasing significance of transportation for the supply of living goods as well as for the provision of access to services potentially affects fire ignition as well. Several international studies have shown the significance of the distance of forest fires to roads, settlements and infrastructure, or specific land uses or even its abandonment as predisposition for fire ignition (Vega-Garcia et al. 1995, Goldammer 2003, Kalabokidis et al. 2002, Catry et al. 2009, Martinez et al. 2009).Although human factors are relatively important when analyzing forest fire ignition, little attention has been paid to their s...

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Mapping lightning/human-caused wildfires occurrence under ignition point location uncertainty

Cited by 114 publications

References 31 publications

Assessment and validation of wildfire susceptibility and hazard in Portugal

Assessment and validation of wildfire susceptibility and hazard in Portugal

Spatial point process modeling applied to the assessment of risk factors associated with forest wildfires incidence in Castellón, Spain

Modeling human-caused forest fire ignition for assessing forest fire danger in Austria

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