Uso de imagem orbital de alta resolução espacial para monitoramento de níveis de degradação florestal no baixo curso do Rio Mearim no Maranhão

• Ano de defesa: 2017
• Autor(a) principal: Nunes, Zélia Maria
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: UEMA; Brasil; Campus São Luis Centro de Ciências Agrárias – CCA; Centro de Ciências Agrárias; PROGRAMA DE PÓS-GRADUAÇÃO EM AGROECOLOGIA
• Palavras-chave em Português: Degradação florestal; Biomassa; Sensoriamento Remoto; Forest degradation; Biomass; Remote Sensing; Ciências Agrárias
• Link de acesso: http://repositorio.uema.br/handle/123456789/746

Degradation of forests throughout the world is one of the most serious environmental problems facing societies, ecosystem health and social welfare, provided by ecosystem goods and services, are increasingly threatened. Thinking about preservation, conservation and restoration goes through understanding the inherent processes and degradation itself. In this sense, the objective of this work was to analyze the environmental implications caused by ciliary deforestation in the lower course of the Mearim river, in Maranhão. For this, a first chapter brought a literature review focused on the main concepts and current research in order to present a panorama of the theme. A second chapter deals with the possibilities of using spectral bands (Green, Red, Red Edge and NIR) and vegetation indices (NDVI, NDVIre, VIgreen) based on Remote Sensing to define forest degradation gradients, vegetation in watersheds (Aquatic, SemiAquatic and Terra Firma) and also on the composition of forest biomass. Statistical analyzes (ANOVA and linear regression) were performed and the sensitivity of NDVI, NDVIre and VIgreen was determined to define two of the four levels of degradation proposed and to differentiate vegetation in one of the three hydrographic zones presented. Red Edge reflectance shows sensitivity to hydrographic zones. Indices and bands are sensitive to the composition of forest biomass.