A Decision Support System for forest fire management

Kaloudis, S.; Lorentzos, Nikos A.; Sideridis, Alexander B.; Yialouris, Constantine P.

doi:10.1007/bf02944167

Cited by 5 publications

(5 citation statements)

References 9 publications

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“…Forest fire risk has been included in forest planning in several ways (e.g. González et al, 2005;González-Olabarría et al, 2008;Hyytiainen and Haight, 2010;García-Gonzalo et al, 2011a;Ferreira et al, 2011Ferreira et al, , 2012, and in fact forest fire risk is one of the few examples where uncertainty and risk is considered in forestry DSSs (Kaloudis et al, 2005;Bonazountas et al, 2007). In Europe during 1950-2000, wind storms were responsible for 53% and forest fires for 16% of forest damages (Schelhaas et al, 2003).…”

Section: Methodsmentioning

confidence: 99%

“…Simulated Annealing). Examples of fire management DSSs these are Wildfire Destruction Danger Index WFDDI (Kaloudis et al, 2005), which utilizes fuzzy set theory and DSS for managing forest fire casualties (Bonazountas et al, 2007), where the uncertainty considerations are based on Monte Carlo simulation. Intensive and costly spruce budworm outbreaks in Eastern Canada led to the development of Spruce Budworm Decision Support System SBW DSS (MacLean et al, 2001), which calculates the marginal timber yield utilities for protecting against budworm outbreaks.…”

Section: Forestry Dsss Involving Uncertainty and Risk Considerationsmentioning

confidence: 99%

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Review. Assessing uncertainty and risk in forest planning and decision support systems: review of classical methods and introduction of new approaches

Pasalodos-Tato

Mäkinen²,

García-Gonzalo³

et al. 2013

For. syst.

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Aim: Since forest planning is characterized by long time horizon and it typically involves large areas of land and numerous stakeholders, uncertainty and risk should play an important role when developing forest management plans. The aim of this study is to review different methods to deal with risk and uncertainty in forest planning, listing problems that forest managers may face during the preparation of management plans and trying to give recommendations in regard to the application of each method according to the problem case. The inclusion of risk and uncertainty in decision support systems is also analyzed.Area: It covers the temporal and spatial scale of forest planning, the spatial context, the participation process, the objectives dimensions and the good and services addressed.Material and methods: Several hundreds of articles dealing with uncertainty and risk were identified regarding different forestry-related topics and approaches. Form them, around 170 articles were further reviewed, categorized and evaluated.Main results: The study presents a thorough review and classification of methods and approaches to consider risk and uncertainty in forest planning. Moreover, new approaches are introduced, showing the opportunities that their application present in forest planning.Research highlights: The study can aid forest managers in the decision making process when designing a forest management plan considering risk and uncertainty.Keywords: operations research; optimal alternative; stochastic risk; endogenous risk; stand level; forest level.

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Section: Methodsmentioning

confidence: 99%

Section: Forestry Dsss Involving Uncertainty and Risk Considerationsmentioning

confidence: 99%

Review. Assessing uncertainty and risk in forest planning and decision support systems: review of classical methods and introduction of new approaches

Pasalodos-Tato

Mäkinen²,

García-Gonzalo³

et al. 2013

For. syst.

View full text Add to dashboard Cite

show abstract

“…Although not required to mention in a detailed manner, OR has long been employed to provide elaborately designed and optimized solutions in every aspect of our daily life from agriculture (Galanopoulos et al 2004), forestry (Kaloudis et al 2005) and fisheries (Arabatzis and Kokkinakis 2005) to management of water resources (Babajimopoulos and Panoras 2005); from climate change (Skuras et al 2014) and global warming (Yang and Yeh 2016) to economy (Brauers 2008) and tourism (Vazakidis and Karagiannis 2011), etc. Together with the recent developments in computing technologies and available software, there has been an increasing trend in the implementation of modern methods of OR for estimating very complex physical processes in nature which are directly related with weather and climate change, global warming, and natural disasters (i.e., typhoon attacks, earthquakes, floods, or tsunamis). The quality of estimation process is at highest priority in order to take efficient measures to mitigate the negative effects of these earth sciences related challenges.…”

Section: Earth Sciences Data Within Operational Research Perspectivementioning

confidence: 99%

A progressive approach for processing satellite data by operational research

2016

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Satellite data, together with spatial technologies, have a vital importance in earth sciences to continuously monitor natural and physical processes. However, images taken by earth-observing satellites are often associated with uncertainties due to atmospheric effects (i.e., absorption and scattering by atmospheric gases and aerosols). In this paper, a more adaptable approach for the removal of atmospheric effects from satellite data is introduced within an operational research perspective by utilizing nonparametric regression splines. Regional atmospheric correction models via multivariate adaptive regression splines (MARS) are applied on a set of satellite images for Alps and Turkey to calculate surface reflectance values. A classical radiative transfer based atmospheric correction method is likewise employed on the same data set. The results are compared in terms of relative differences with respect to surface reflectance data. MARS provides significant improvement in the order of 40 and 37 % for Alps and Turkey, respectively.

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“…Both components are supported by nationally consistent databases providing fuels and weather data to drive fire models and critical infrastructure and occupied-structures data for values assessment. Potential exists for international collaboration and co-development, as similar wildfire decision-support systems are partially or fully implemented and subject to ongoing development in Greece (Kaloudis et al 2005), Australia (Tolhurst et al 2006) and Canada (de Groot 2010; Ohlson et al 2006).…”

Section: Framework For Risk-based Fire-effects Analysismentioning

confidence: 99%

Research and development supporting risk-based wildfire effects prediction for fuels and fire management: status and needs

Hyde

Dickinson

Bohrer

et al. 2013

Int. J. Wildland Fire

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Wildland fire management has moved beyond a singular focus on suppression, calling for wildfire management for ecological benefit where no critical human assets are at risk. Processes causing direct effects and indirect, long-term ecosystem changes are complex and multidimensional. Robust risk-assessment tools are required that account for highly variable effects on multiple values-at-risk and balance competing objectives, to support decision making. Providing wildland fire managers with risk-analysis tools requires a broad scientific foundation in fire behaviour and effects prediction as well as high quality computer-based tools and associated databases. We outline a wildfire riskassessment approach, highlight recent developments in fire effects science and associated research needs, and recommend developing a comprehensive plan for integrated advances in wildfire occurrence, behaviour and effects research leading to improved decision support tools for wildland fire managers. We find that the current state of development in fire behaviour and effects science imposes severe limits on the development of risk-assessment technology. In turn, the development of technology has been largely disconnected from the research enterprise, resulting in a confusing array of ad hoc tools that only partially meet decision-support needs for fuel and fire management. We make the case for defining a common riskbased analytic framework for fire-effects assessment across the range of fire-management activities and developing a research function to support the framework.

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A Decision Support System for forest fire management

Cited by 5 publications

References 9 publications

Review. Assessing uncertainty and risk in forest planning and decision support systems: review of classical methods and introduction of new approaches

Review. Assessing uncertainty and risk in forest planning and decision support systems: review of classical methods and introduction of new approaches

A progressive approach for processing satellite data by operational research

Research and development supporting risk-based wildfire effects prediction for fuels and fire management: status and needs

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