Projetos
ECO.Fire – The economic value of forest fires as support for prevention behavior
Forest fires have been considered one of the main environmental problems. Despite this importance, its economic impact, which takes into account direct and indirect economic losses, is currently not well measured. In addition to the loss of human life, of properties and infrastructures, the extent of the consequences of the fire, from a forest perspective, can be assessed in large part by the social cost of such fires, which is the most negative of the associated externalities. Accurate accounting of the impacts of Forest fires is essential, not only for determining the compensation due to the affected communities but also for producing useful information for management and protection actions against the fire itself. The possibility of being able to estimate a priori the predictable cost of a forest fire in a given location can support the decision process of owners, managers and territorial entities with regard to decisions such as choice of species to explore, management of forest strips, alteration of land uses or even balance costs of cleanings taking into account the various cost scenarios in advance. It is recognized that the assessment of economic losses caused by forest fires is an activity of high complexity and importance, due to the number of short, medium and long-term effects, on social, economic and environmental levels, and also by the difficulty of allocating a market value to resources such as biological diversity and the preservation of threatened species.
The team in this work, combining high-level knowledge of environmental economic assessment methods, impacts of forest fires and computational tools, aims to build a model for the economic assessment of the impacts of forest fires, involving the local population, which will serve as a tool to support forest management and fire prevention policies. In addition to the direct and indirect accounting of the impacts of fires, we propose to use non-market valuation methods to explore the value of assets related to forest resources that can be lost through forest fires. In addition, we design a socio-economic experience, which tests mechanisms to contribute to the prevention of forest fires. Both methodologies are established in the literature and have been implemented in several studies by members of the research team following high international standards.
About
Forest fires have been considered one of the major environmental, social and economic problems of the last decade. Despite this, the costs of direct and indirect economic losses have not been well measured. Accurate accounting of the impacts of forest fires is essential for determining compensation to affected communities and producing useful information for management and protection actions against the fires themselves.
The possibility of estimating a priori the predictable cost of a fire, related to environmental, social and economic issues in a given location, provides excellent support for decision-making by landowners, managers and territorial entities.
In this context, ECOFIRE aims to develop new methodologies for the economic assessment of damage and impacts of forest fires in areas affected by fires, mechanisms for collecting relevant information for preventing forest fires, and a mobile application for assessing the economic damage and environmental impacts of fires.
As the economic evaluation of the damages caused by forest fires is complex, the team of this project combines a high-level knowledge of environmental-economic evaluation methods, forest fire impacts and computational tools to build an evaluation model. The work will count on the local population’s involvement and serve as a tool to support forest management and fire prevention policies.
ECOFIRE began in October 2019 and will last for two years. The project includes experts from the University of Minho and the Computer Graphics Centre.
Goals
The proposed work will result in new methodologies for the economic evaluation of damage and impacts of forest fires, for the rapid identification of areas affected by fires and the contributions of the economic experiment to develop mechanisms for collecting geographically relevant information for forest fire prevention. An operational tool of a mobile application will also be designed to evaluate and calculate the economic data and environmental impacts caused by fires. The overall goal is to make the territory more resilient to forest fires and enable more effective fire fighting.
Fast mapping tools
Design of rapid mapping tools to identify critical areas in terms of economic losses and environmental impacts and the public involvement of critical stakeholders. The economic assessment of forest fire losses and environmental impacts is challenging. For cost-effective use of the proposed methodologies, they should be initially applied in selected locations where the burned area is large, and the severity of forest fires is more significant. This task aims to identify critical areas affected by forest fires in terms of economic losses and environmental impacts.
Experimental design
Development of a methodology to evaluate the impact of forest fires, the calculation of the value and the experience with local actors to promote forest fire prevention. This task discrete variable choice experiments, questionnaires on attitudes and preferences and the economic experiment itself. This task results in two models to assess the economic value of fires and fire prevention and a more preventive community. This task is fundamental to define the model to calculate the economic value of fires and understand how to develop effective awareness campaigns.
Crowdsensing tool
Development of computation tools to support the project regarding the field information collection, based on the results of the questionnaire activity and the data. All data collection work and crowdsensing applications will be carried out. The crowdsensing aims to send and make available information from a back-office platform, implement the model, and then, based on the models’ results, produce new information that will support the decision on the use of the land.
Aplicação (soon) and Report