Abstract
Forest ecosystems are our priceless natural resource and are a key component of the global carbon budget. Forest fires can be a hazard to the viability and sustainable management of forests with consequences for natural and cultural environments, economies, and the life quality of local and regional populations. Thus, the selection of strategies to manage forest fires, while considering both functional and economic efficiency, is of primary importance. The use of decision support systems (DSSs) by managers of forest fires has rapidly increased. This has strengthened capacity to prevent and suppress forest fires while protecting human lives and property. DSSs are a tool that can benefit incident management and decision making and policy, especially for emergencies such as natural disasters. In this study we reviewed state-of-the-art DSSs that use: database management systems and mathematical/economic algorithms for spatial optimization of firefighting forces; forest fire simulators and satellite technology for immediate detection and prediction of evolution of forest fires; GIS platforms that incorporate several tools to manipulate, process and analyze geographic data and develop strategic and operational plans.
Highlights
Forest ecosystems are our priceless natural resource and are fundamental to the global carbon budget (IPCC 2007)
In this study we reviewed state-of-the-art decision support systems (DSSs) that use: database management systems and mathematical/ economic algorithms for spatial optimization of firefighting forces; forest fire simulators and satellite technology for Project funding: Significant part of this research was co-financed by the European Union (European Social Fund-ESF) and Greek national funds through the Operational Program ‘‘Education and Lifelong Learning’’ of the National Strategic Reference Framework (NSRF)— Research Funding Program: Thales
In Greece, natural causes account for 2.2% of all wildfires, whereas anthropogenic causes account for 95%
Summary
Forest ecosystems are our priceless natural resource and are fundamental to the global carbon budget (IPCC 2007). In addition to the burn probability (number of times each pixel affected by fire divided by the total number of fire simulations), Burn-P3 can produce supplementary outputs such as the size of the fires which took place at the simulation process; the ignition point geographically determined; the season; the number of spread-event days, as well as the area and the corresponding fuels burned (Western Partnership for Wildland Fire Science 2014). The first three components represent the index of fire ignition and, when the latter is paired with the index of fire behavior, produce the final fire risk index which incorporates the basic elements of fire environment in any area The product of this procedure consists of six separate thematic maps and one integrated map, which is a valuable tool for the simulation process as well as for operational vigilance, effective prevention, and timely suppression of forest fires (Kalabokidis et al 2012). The significance is apparent when natural barriers (cloudy weather) or technical restrictions preclude retrieval of satellite images and
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