Análise de risco de incêndios em florestas plantadas

• Autor(a) principal: Eugenio, Fernando Coelho
• Data de Publicação: 2017
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da Universidade Federal do Espírito Santo (riUfes)
• Texto Completo: http://repositorio.ufes.br/handle/10/7706
• topic: Geotecnologias; Proteção florestal; RIF-Database; Risco de incêndio; Forest fire risk; Forest protection; Geotechnology; Recursos Florestais e Engenharia Florestal; Florestas - Proteção; Incêndios florestais; Geotecnologia ambiental; 630

In cases where prevention is not sufficient to prevent a forest fire, a rapid detection of it is a decisive factor to minimize the damage caused by fire, as well as the reduction of costs associated with its combat. Within this context, with this research we aimed to developed a Database-based risk model and to evaluate, along with other methodologies of forest fire risk, the onde that best represent the forest fires in areas of planted forests on the central coast of Espírito Santo state and Bahia south coast. A) Determination of areas with a homogeneous climate; B) Statistics on forest fires; C) Calculation and spatialization of forest fire risk indexes: Fire Weather Index (FWI); Monte Alegre Alterated Formula (FMA +) and Fire Risk of the National Institute of Space Research (RF); D) to develop a model for calculating the risk of forest fires based on the Database (RIF-Database); and, f) Selection of risk models from the forest inventories cataloged by FIBRIA Celulose S. A. The methodology adopted proved to be efficient for the grouping of meteorological stations in three homogeneous climatic subzones for a study area. There are two phases of forest fires in the studied area, being the first fase, subarea 1, from december to march, for subarea 2 from january to march and for subarea 3 in the months of january and february. The second season, for all subzones, is placed between the months of august to october. The FWI model presented the best results for a subarea 1. The RIF-Database model presented excellent results, being the model used for subareas 2 and 3. The FWI model is seen as a prosperous model for the study area since it discovered higher values for a subarea, faced to a model developed through the study area database, however, a study is needed to calibrate its parameters.