SPATIAL MODEL FOR PREVENTING WILDLAND FIRES IN A RESTINGA PROTECTED AREA
Name: LEONARDO DUARTE BIAZATTI
Publication date: 19/02/2024
Examining board:
Name |
Role |
|---|---|
| ANDRÉ QUINTÃO DE ALMEIDA | Examinador Externo |
| DANILO SIMÕES | Examinador Externo |
| HENRIQUE MACHADO DIAS | Examinador Interno |
| NILTON CESAR FIEDLER | Presidente |
| PATRÍCIA BORGES DIAS | Examinador Externo |
Summary: The Restingas face constant threats from anthropogenic pressure, especially forest fires, which act as agents of degradation in these environments, especially for the purposes of real estate speculation. Despite advances in understanding the behavior
of fires in the most varied types of vegetation, the occurrence of these events in sandbanks has been little studied. This research aimed to develop a model for predicting, preventing, detecting and helping to fight forest fires, using geotechnological tools, in the Paulo César Vinha State Park (PEPCV) and the Setiba Environmental Protection Area (APA), located in the municipality of Guarapari, which spatially and structurally represent a large part of the Atlantic Forest sandbank formations in the south of the state of Espírito Santo. Through the application of geoprocessing techniques using geotechnological tools such as Fuzzy logic,
Hierarchical Process Analysis (HPA) logic, least-cost path and network analysis on the variables of land use and occupation, altitude, slope, relief orientation, proximity to roads, urban areas, and watercourses, rainfall, air temperature and land surface
temperature and heat zones, the areas most at risk of forest fires were delimited, as were the priority sites for the construction of firebreaks and roads, the optimum points for installing video monitoring towers and water collection points. It was found that the
area is at very high risk of fires, as 55.17% of the territory is in this risk range. The sites classified as priorities for the construction of firebreaks, because they are close to urban areas and areas of higher risk, represented 65.41% of the study area, so there was a need to install them around these sites. The road allocation model indicated 30 possible routes for opening complementary roads, always going through already anthropized sites. The model for installing video surveillance towers determined six possible allocation scenarios and, considering the 96.55% visualization rate achieved and the cost of implementation, the third scenario (2A) was the best. On the other hand, the optimization for the allocation of water collection points established sixteen possible scenarios, with the eleventh (3C) being the most promising as it showed 80%
coverage of the demand points, using only eleven points, which makes it cost-effective to install. Given these results, it was possible to conclude that the high level of risk of forest fires in the PEPCV and Setiba APA highlights the urgency of implementing
preventive measures aimed at reducing the risk and mitigating the possible consequences of fires in the region. In this context, this study is a source of information for designing predictive and preventive strategies for the PEPCV, as well as providing
support when fighting fires. Finally, it should be noted that the methodology used is applicable, replicable and adaptable to any conservation unit.
