Aplicação da análise fractal na linha de costa como subsídio à confecção de mapas de sensibilidade ambiental a derremes de óleo no litoral amazônico

• Ano de defesa: 2017
• Autor(a) principal: Moura, Aline Maria Alvarez de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Rio de Janeiro; Brasil; Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia; Programa de Pós-Graduação em Engenharia Civil; UFRJ
• Palavras-chave em Português: Engenharia civil; Dimensão fractal; Sensibilidade ambiental; CNPQ::ENGENHARIAS::ENGENHARIA CIVIL
• Link de acesso: http://hdl.handle.net/11422/9589

In the Northern Brazilian Coast, there is an infrastructure linked to the petroleum industry,which includes waterway terminals near mangroves that are very sensitive to oil spills.This region comprises three macro-compartments: “Litoral da Amapá” (LA), “Golfão Amazônico” (GA), and “LItoral da Reetrância Pará-maranhão” (PM). This fact suggests the existence of different configurations for the boundary between earth and water, which can be characterized by fractal geometry. The fractal dimension (D) of 615 distinct segments of the Amazon coast representative of different environments were obtained in this research.Hypothesis tests have shown that the mean value of D for mangroves in LA (1,090) is different from those found for this environment in GA (1,166) and PM (1,167). In the later two, the values for the mangroves can be considered statistically equal. This result may indicate differences in the recovery capacity of Amazonian mangrove swamps in the event of an oil spill accident. In fact, it was possible to refine the ISA 10C class ( intertidal mangrove) by subdividing it into two new classes: 10C.1(with an intermediate energy level, where the oil can be removed days or months after the spill in an environment with intermediate spatial complexity), and 10C.2( With low energy level, in which oil removal may take a long time due to high spatial complexity).