Review of state-of-the-art decision support systems (DSSs) for prevention and suppression of forest fires

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.

Determination of fire risk to assist fire management for insular areas: the case of a small Greek island

Forest fire risk estimation constitutes an essential process to prevent high-intensity fires which are associated with severe implications to the natural and cultural environment. The primary aim of this research was to determine fire risk levels based on the local features of an island,namely, the impact of fuel structures, slope, aspects, as well as the impact of the road network and inhabited regions. The contribution of all the involved factors to forest fires ignition and behavior highlight certain regions which are highly vulnerable. In addition, the influence of both natural and anthropogenic factors to forest fire phenomena is explored. In this study, natural factors play a dominant role compared to anthropogenic factors. Hence essential preventative measures must focus on specific areas and established immediately. Indicative measures may include: the optimal allocation of watchtowers as well as the spatial optimization of mobile firefighting vehicles;and, forest fuel treatments in areas characterized by extremely high fire risk. The added value of this fire prediction tool is that it is highly flexible and could be adopted elsewhere with the necessary adjustments to local characteristics.

Territorial Resilience Through Visibility Analysis for Immediate Detection of Wildfires Integrating Fire Susceptibility,Geographical Features,and Optimization Methods

Climate change effects tend to reinforce the frequency and severity of wildfires worldwide,and early detection of wildfire events is considered of crucial importance.The primary aim of this study was the spatial optimization of fire resources(that is,watchtowers)considering the interplay of geographical features(that is,simulated burn probability to delimit fire vulnerability;topography effects;and accessibility to candidate watchtower locations)and geo-optimization techniques(exact programming methods)to find both an effective and financially feasible solution in terms of visibility coverage in Chalkidiki Prefecture of northern Greece.The integration of all geographical features through the Analytical Hierarchy Process indicated the most appropriate territory for the installment of watchtowers.Terrain analysis guaranteed the independence and proximity of location options(applying spatial systematic sampling to avoid first order redundancy)across the ridges.The conjunction of the above processes yielded 654 candidate watchtower positions in 151,890 ha of forests.The algorithm was designed to maximize the joint visible area and simultaneously minimize the number of candidate locations and overlapping effects(avoiding second order redundancy).The results indicate four differentiated location options in the study area:(1)75locations can cover 90%of the forests(maximum visible area);(2)47 locations can cover 85%of the forests;(3)31locations can cover 80.2%of the forests;and(4)16 locations can cover 70.6%of the forests.The last option is an e fficient solution because it covers about 71%of the forests with just half the number of watchtowers that would be required for the third option with only about 10%additional forest coverage.However,the final choice of any location scheme is subject to agency priorities and their respective financial flexibility.

Spatial Resilience to Wildfires through the Optimal Deployment of Firefighting Resources:Impact of Topography on Initial Attack Effectiveness

Strongly affected by the escalating impacts of climate change,wildfires have been increasing in frequency and severity around the world.The primary aim of this study was the development of specific territorial measures—estimating the optimal locations of firefighting resources—to enhance the spatial resilience to wildfires in the fire-prone region of Chalkidiki Prefecture in northern Greece.These measures focus on the resistance to wildfires and the adaptation of strategies to wildfire management,based on the estimation of burn probability,including the effect of anthropogenic factors on fire ignition.The proposed location schemes of firefighting resources such as vehicles consider both the susceptibility to fire and the influence of the topography on travel simulation,highlighting the impact of road slope on the initial firefighting attack.The spatial scheme,as well as the number of required firefighting forces is totally differentiated due to slope impact.When we ignore the topography effect,a minimum number of fire vehicles is required to achieve the maximization of coverage(99.2%of the entire study area)giving priority to the most susceptible regions(that is,employing 18 of 24 available fire vehicles).But when we adopt more realistic conditions that integrate the slope effect with travel time,the model finds an optimal solution that requires more resources(that is,employing all 24 available fire vehicles)to maximize the coverage of the most vulnerable regions within 27 min.This process achieves 80%of total coverage.The proposed methodology is characterized by a high degree of flexibility,and provides optimized solutions to decision makers,while considering key factors that greatly affect the effectiveness of the initial firefighting attack.

Geospatial predictive modelling of the Neolithic archaeological sites of Magnesia in Greece

Sources of heterogeneous geospatial data such as the elevation,the slope,the aspect,the water network and the current settlements related to the known Neolithic archaeological sites of Magnesia,are used in an attempt to confirm the existence and allow for the prediction of other archaeological sites using predictive modelling theory.Predictive modelling allows the update of the problem solving strategy as soon as new data layers are available.The Dempster
Shafer Theory also commonly referred to as evidential reasoning(ER)is used to compose probability maps of areas of archaeological interest from physiographical and historical data.The advantage of this theory is that the ignorance is quantified and used to compose the probability maps named as belief,plausibility and belief interval for the archaeological sites.The final digital probability maps show that the Neolithic archaeological sites can be detected in the prefecture of Magnesia.This research study forms a methodological tool for the prediction of new archaeological sites in other areas of archaeological interest according to the physiographical and historical characteristics of the archaeological period being examined.It also contributes to the digital earth modelling and archaeological site protection,one of the most critical and challenging global initiatives.