GIS applied to location of fires detection towers in domain area of tropical forest

• Published in: The Science of the total environment 2016-08, Vol.562, p.542-549
• Main Authors: Eugenio, Fernando Coelho, Rosa dos Santos, Alexandre, Fiedler, Nilton Cesar, Ribeiro, Guido Assunção, da Silva, Aderbal Gomes, Juvanhol, Ronie Silva, Schettino, Vitor Roberto, Marcatti, Gustavo Eduardo, Domingues, Getúlio Fonseca, Alves dos Santos, Gleissy Mary Amaral Dino, Pezzopane, José Eduardo Macedo, Pedra, Beatriz Duguy, Banhos, Aureo, Martins, Lima Deleon
• Format: Article
• Language: English
• Subjects: Atlantic forest; Conservation units; Forest fire prevention; Geotechnology
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2016.03.231

In most countries, the loss of biodiversity caused by the fires is worrying. In this sense, the fires detection towers are crucial for rapid identification of fire outbreaks and can also be used in environmental inspection, biodiversity monitoring, telecommunications mechanisms, telemetry and others. Currently the methodologies for allocating fire detection towers over large areas are numerous, complex and non-standardized by government supervisory agencies. Therefore, this study proposes and evaluates different methodologies to best location of points to install fire detection towers considering the topography, risk areas, conservation units and heat spots. Were used Geographic Information Systems (GIS) techniques and unaligned stratified systematic sampling for implementing and evaluating 9 methods for allocating fire detection towers. Among the methods evaluated, the C3 method was chosen, represented by 140 fire detection towers, with coverage of: a) 67% of the study area, b) 73.97% of the areas with high risk, c) 70.41% of the areas with very high risk, d) 70.42% of the conservation units and e) 84.95% of the heat spots in 2014. The proposed methodology can be adapted to areas of other countries. [Display omitted] •We examine the best location for the allocation of fire detection towers.•Coverage of 73.97% of the areas with high risk was obtained.•Coverage of 70.41% of the areas with very high risk was obtained.•84.95% coverage of the heat spots from 2014 was obtained.•The proposed methodology can be adapted to areas of other countries.