In spite of the increasing performance of operational safety technology in exploration, production and transportation of petroleum, the risk of accidents is still present and the corresponding impacts are a threat for coastal zones throughout the world. The largest oil spills in the world have been ecologically devastating due to the destruction of wildlife. Natural resources in the Guajará Bay (Belém-PA, Amazonian) are threatened by several human activities, such as industrial pollution by heavy metals and urban effluents that are daily spilled there. In addition, the location of the Miramar petrochemistry terminal in the vicinities of Belém constitutes a risk for potential oil spills. Ships and tankers that daily cross the bay also represent an environmental threat. The aim of this work is to carry out an environmental sensitivity index (ESI) analysis of the Amazonian coast for oil spills, and to provide an environmental sensitivity index map for the region. With this objective in mind, the ESI was analysed for the region using the method proposed for NOAA (2002) and Petrobras (2002), in order to develop a new approach that consider the uniqueness of the coastal environment of the Amazonian Region. The method used to develop an environmental sensitivity index map considers an integrated analysis of the coastal environment and includes digital image processing of remote sensing data, in this case, RADARSAT-1 Wide-1 and LANDSAT-7 ETM+ images, as well as the use of Geographic Information System (GIS) and field surveys focusing on geomorphology, topography, sedimentology and social-economics. This approach allowed an accurate analysis of ESI for potential oil spills, based on an environmental georeferenced data base. As a result, seven landscape units were identified, ESI corresponding to the following values: i) solid man-made structure - ESI 1B; ii) cliff - ESI 3; iii) beach - ESI 4; iv) sheltered man-made structure - ESI 8B; v) tidal mudflat - ESI 9B; vi) mangrove - ESI 10A; vii) freshwater marsh - 10B. The use of remote sensing technologies and GIS together with the field work, proved to be a powerful combination to assess the geomorphology in the study area and therefore, to establish environmental sensibility indexes for oil spills. These procedures were helpful to define priority areas to be protected in case of oil spills.
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