Forest Fire Risk Analysis

Bonazountas, Marc; Kallidromitou, Despina; Kassomenos, Pavlos; Passas, Nikos

doi:10.1080/10807030590949717

Cited by 61 publications

(31 citation statements)

References 5 publications

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“…Catastrophic forest fire causes the destruction of large areas in many countries in Europe, America and Australia (Bonazountas et al 2005). Though the impacts are relatively low compared with other major disasters, like floods, landslides and earthquakes, forest fires have direct and indirect impacts that include death, and damage to buildings and infrastructures, as well as an adverse effect on people's health (Kochi et al 2010;Stephenson et al 2013;Doerr and Santín 2016;Martin 2016).…”

Section: Introductionmentioning

confidence: 99%

Understanding forest fire patterns and risk in Nepal using remote sensing, geographic information system and historical fire data

Matin

Chitale

Murthy

et al. 2017

Int. J. Wildland Fire

148

100

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Abstract. Forest fire is one of the key drivers of forest degradation in Nepal. Most of the forest fires are human-induced and occur during the dry season, with ,89% occurring in March, April and May. The inaccessible mountainous terrain and narrow time window of occurrence complicate suppression efforts. In this paper, forest fire patterns are analysed based on historical fire incidence data to explore the spatial and temporal patterns of forest fires in Nepal. Three main factors are involved in the ignition and spread of forest fires, namely fuel availability, temperature and ignition potential. Using these factors a spatially distributed fire risk index was calculated for Nepal based on a linear model using weights and ratings. The input parameters for the risk assessment model were generated using remote sensing based land cover, temperature and active fire data, and topographic data. A relative risk ranking was also calculated for districts and village development committees (VDCs). In total, 18 out of 75 districts were found with high risk of forest fires. The district and VDC level fire risk ranking could be utilised by the Department of Forest for prioritisation, preparedness and resource allocation for fire control and mitigation.Additional keywords: fire behaviour, fire danger, fire management, fire risk.

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Section: Introductionmentioning

confidence: 99%

Understanding forest fire patterns and risk in Nepal using remote sensing, geographic information system and historical fire data

Matin

Chitale

Murthy

et al. 2017

Int. J. Wildland Fire

148

100

View full text Add to dashboard Cite

show abstract

“…The more complex fire models require spatial information that is furnished by remote sensing and Geographic Information Systems (GIS) (Bonazountas et al 2005). Additionally, integration of multicriteria decision-making (MCDM) methods in spatial domain provides a novel framework for addressing several environmental problems, including quantifying "fire risk."…”

Section: Introductionmentioning

confidence: 99%

Fire risk evaluation using multicriteria analysis—a case study

Vadrevu

Eaturu

Badarinath

2009

Environ Monit Assess

160

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Forest fires are one of the major causes of ecological disturbance and environmental concerns in tropical deciduous forests of south India. In this study, we use fuzzy set theory integrated with decision-making algorithm in a Geographic Information Systems (GIS) framework to map forest fire risk. Fuzzy set theory implements classes or groupings of data with boundaries that are not sharply defined (i.e., fuzzy) and consists of a rule base, membership functions, and an inference procedure. We used satellite remote sensing datasets in conjunction with topographic, vegetation, climate, and socioeconomic datasets to infer the causative factors of fires. Spatial-level data on these biophysical and socioeconomic parameters have been aggregated at the district level and have been organized in a GIS framework. A participatory multicriteria decision-making approach involving Analytical Hierarchy Process has been designed to arrive at a decision matrix that identified the important causative factors of fires. These expert judgments were then integrated using spatial fuzzy decision-making algorithm to map the forest fire risk. Results from this study were quite useful in identifying potential "hotspots" of fire risk, where forest fire protection measures can be taken in advance. Further, this study also demonstrates the potential of multicriteria analysis integrated with GIS as an effective tool in assessing "where and when" forest fires will most likely occur.

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“…Visibility analysis is often used to determine areas that are visible from a specific location, and its applications range from the military field [7] to modelling of environmental changes [8,9] generated an integrated geospatial system, which provides a series of software tools for the assessment of the propagation and combating of forest fires. The interface integrates GIS technologies under the same data environment that would serve as a useful tool for forest fire prevention, planning and management.…”

Section: Introductionmentioning

confidence: 99%

Viewshed Analysis for Improving the Effectiveness of Watchtowers, in the North of Mexico~!2010-03-06~!2010-06-14~!2010-07-26~!

Pompa-García¹

2010

TOFSCIJ

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Abstract:The forests in Mexico have been seriously affected by forest fires, and thus detection of fires from watchtowers is essential. The current numbers of watchtowers and effectiveness of their distribution is unknown. The aim of the present study was to determine the current and potential area visible from the watchtowers, and to propose a new network to maximize its effectiveness. Visibility analysis in ArcGis were developed by integrating a digital model of elevation and a vegetation cover map, to determine visibility on a surface from point to point along a given line of sight or across the entire surface in a viewshed. It was found that existing watchtowers provide an overall visibility effectiveness (43%) very low compared with the recommended level. We suggest relocating one of the watchtowers and constructing another, which would increase the overall visibility effectiveness up to 81%.

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Forest Fire Risk Analysis

Cited by 61 publications

References 5 publications

Understanding forest fire patterns and risk in Nepal using remote sensing, geographic information system and historical fire data

Understanding forest fire patterns and risk in Nepal using remote sensing, geographic information system and historical fire data

Fire risk evaluation using multicriteria analysis—a case study

Viewshed Analysis for Improving the Effectiveness of Watchtowers, in the North of Mexico~!2010-03-06~!2010-06-14~!2010-07-26~!

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