Tecnologias geoespaciais na gestão de riscos: mapeamento e zoneamento de quedas de árvores em áreas vulneráveis em Maceió, Alagoas

Abstract

Urban tree planting plays a fundamental role in urban sustainability, providing essential ecosystem services such as thermal regulation, reduction of atmospheric pollutants, and biodiversity conservation. However, Maceió, like other Brazilian metropolises — such as São Paulo, Rio de Janeiro, and Belo Horizonte — faces structural challenges that compromise its green infrastructure. Factors such as tree aging, inadequate management practices, and the intensification of extreme climatic events increase the risks of tree falls, threatening not only urban safety but also the environmental resilience of these centers. In this context, this study aimed to develop a risk zoning map for tree falls using geospatial technologies. The research was conducted in the municipality of Maceió, covering all its neighborhoods. Records of incidents from the Civil Defense of Maceió (DCM, 2021–2024) were processed in Microsoft Excel spreadsheets for data organization, standardization, and integrity assurance. Subsequently, the data were imported into QGIS 3.34 software for geoprocessing. In the initial QGIS stage, georeferenced point layers were created to represent tree fall incidents and associated hazards. The "Point-in-Polygon Count" tool was applied to quantify events per neighborhood, followed by graduated symbology classification, which categorized risks into: no occurrence, very low, low, moderate, high, and very high. As a result, the comparative analysis of DCM records (2021–2024) revealed critical patterns associated with heavy rainfall and strong winds, with extreme climatic events, such as torrential rains and windstorms, being decisive factors for tree instability. Data indicated a higher incidence of falls in densely populated neighborhoods, particularly Benedito Bentes, Jacintinho, and Jatiúca, which emerged as critical areas due to the recurrence of incidents, especially during wet periods. The mapping identified Benedito Bentes as a priority area for immediate intervention, alongside other vulnerable regions, guiding public prevention and mitigation policies. It is concluded that the integration of geotechnologies, such as remote sensing and GIS, is crucial to optimize urban risk management, as they enable refined temporal and spatial analyses. This approach not only reduces socioeconomic impacts but also promotes environmental resilience in the face of increasingly adverse climatic scenarios.