Geotecnologias na alocação de torres de observação de incêndios florestais

• Autor(a) principal: Eugenio, Fernando Coelho
• Data de Publicação: 2014
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da Universidade Federal do Espírito Santo (riUfes)
• Texto Completo: http://repositorio.ufes.br/handle/10/5031
• topic: Proteção florestal; Geotecnologias; Risco de incêndios; Forest fires; Geotechnology; Recursos florestais e Engenharia florestal; Incêndios florestais - Prevenção e controle; Geotecnologia ambiental; Florestas - Proteção; 630

Where prevention is not enough to prevent the outbreak of a fire outbreak, rapid detection is a key factor to be able to minimize the damage caused by fire and to reduce costs associated with their fight. Faced with this fact, watch towers appear as an excellent system of early detection of forest fire. In this context, this research aims to develop a methodology for allocating towers detection of forest fires in the state of Espirito Santo, addressing the following methodological steps: a) develop a model to map the risk of forest fires in the state of Espirito Santo ( RIF- ES ) b ) mapping the Permanent Preservation Areas from the perspective of the new forest code in the state of Espirito Santo, c) allocate strategic sites for deployment of towers detection in the state of Espirito Santo, Brazil and d) comparing areas displaying the towers detection with the areas most prone to the risk of fire and areas preserved permanent (APP's + UC's). The proposed methodology is efficient for placing towers fire detection, where as the C3 Method, was the chosen methodology, with coverage of 67% of the state of Espírito Santo, from 140 watch towers. The areas that have the highest risk of forest fires, the classes with high risk, very high and extreme have a preview of respectively 73.97%, 70.41% and 61.03%. The APP's, with C3 method will have 61.76% of their areas visualized with the installation of 140 watch towers. The C3 method, showed a coverage of 70.42% of UC's state.