Federal University of Espírito Santo/UFES, PostGraduate Programme in Forest Sciences, Av. Governador Lindemberg, 316, 29550-000 Jerônimo Monteiro, ES, Brazil.
Federal University of Viçosa/UFV, Graduate Program in Forest Science, Avenida P. H. Rolfs; s/n, Campus Universitário, 36570-000 Viçosa, MG, Brazil.
Sci Total Environ. 2016 Aug 15;562:542-549. doi: 10.1016/j.scitotenv.2016.03.231. Epub 2016 Apr 22.
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.
在大多数国家，火灾导致的生物多样性丧失令人担忧。从这个意义上说，火灾探测塔对于快速识别火灾爆发至关重要，也可用于环境检查、生物多样性监测、电信机制、遥测等领域。目前，用于在大面积区域分配火灾探测塔的方法数量众多，复杂且不受政府监管机构标准化。因此，本研究提出并评估了不同的方法，以考虑地形、风险区域、保护区和热点，来最佳定位安装火灾探测塔的地点。使用地理信息系统 (GIS) 技术和非对齐分层系统抽样，实施并评估了 9 种分配火灾探测塔的方法。在所评估的方法中，选择了 C3 方法，代表了 140 个火灾探测塔，其覆盖范围为：a）研究区域的 67%，b）高风险区域的 73.97%，c）极高风险区域的 70.41%，d）保护区的 70.42%和 e）2014 年热点的 84.95%。所提出的方法可以适用于其他国家的地区。
