RESUMEN
The current case study focuses on the Environmental Sensitivity Index (ESI) mapping of Guanabara Bay, Rio de Janeiro, Brazil - a region at risk from petroleum sector pollution. By mapping 981.5 km of coastline and classifying it in 10 oil sensitivity indices, we integrated biotic resources, socioeconomic attributes, and geoenvironmental diversity into a georeferenced database. Results reveal a high oil sensitivity of the bay, with approximately 89 % of the mapped coast scoring ESI 8 and ESI 10. These scores comprise, respectively, estuarine and solid substrate habitats that are sheltered from wave action. Notably, numerous manufacturing and oil handling plants, along with intensive urbanization, also contribute to the bay's oil sensitivity. Additionally, the rich biotic diversity in the study area, particularly in protected areas housing 79 conservation units, further amplifies its environmental vulnerability. This study aims to serve as a reference for detailed ESI mapping of coastal areas in tropical rainy zones with significant environmental diversity, industrial development, and a dense population.
Asunto(s)
Contaminación por Petróleo , Brasil , Monitoreo del Ambiente/métodos , Ecosistema , Bases de Datos FactualesRESUMEN
The Environmental Sensitivity Index (ESI) for oil spills was developed to assist coordinators to evaluate oil spill impact along shorelines and also to coordinate the allocation of resources during and after the incident, aiming to reduce environmental damage and consequences. Recently, Remotely Piloted Aerial Systems (RPAS) are being used in a wide range of areas, since they complement traditional remote sensing data (e.g., satellite images) and offer a rapidly, precise, detail and high-resolution images that fit well for environmental studies. Herein, the use of high-resolution RPAS images for ESI analysis of rocky shores in the Brazilian territory was performed. Using RPAS images, with their higher-resolution compared with ArcGIS Pro Basemap satellite images, increased the detailed of ESI analysis for oil spills, increasing the number of regions in the rocky shore that are more sensitive to oil spills. The RPAS images were able to decrease the number of areas that were less sensitive to oil spills, and increase areas that are more sensitive to oil spills. This increase is important, since they were not detected in the ESI analysis using conventional ArcGIS Pro Basemap satellite images. The RPAS images permit to delineate precisely rocky shores, improving ESI interpretation in rocky shores.