Review of state-of-the-art decision support systems (DSSs) for prevention and suppression of forest fires
Document Type: Journal Article
Author(s): Stavros Sakellariou; Stergios Tampekis; Fani Samara; Athanassios Sfougaris; Olga Christopoulou
Publication Year: 2017

Cataloging Information

  • decision support system
  • fire behavior simulation modeling
  • fire management
  • firefighting
  • forest fire
  • GIS - geographic information system
  • mathematical algorithms
  • risk management
Record Maintained By:
Record Last Modified: September 17, 2018
FRAMES Record Number: 56539


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.

Online Link(s):
Sakellariou, Stavros; Tampekis, Stergios; Samara, Fani; Sfougaris, Athanassios; Christopoulou, Olga. 2017. Review of state-of-the-art decision support systems (DSSs) for prevention and suppression of forest fires. Journal of Forestry Research 28(6):1107-1117.