Estudo da Geomorfologia de Ambientes Costeiros Tropicais Úmidos a partir de Imagens de Sensores Remotos

PEDRO WALFIR SOUZA FILHO, WALDIR RENATO PARADELLA

Resumo


Orbital remote sensing data was used to evaluate its applications in the study of wet tropical coastal environments in the Brazilian Amazon (Bragança coastal plain, in the northeastern of the State of Pará). This work was developed as part of the GlobeSAR-2 Program, whose the objectives were build and consolidate the formation of human resources, as well as evaluate the potential and the applicability of the synthetic aperture radar (SAR) RADARSTA-1 in the Latin America. The holocenic evolution of the Bragança coastal plain is marked by muddy progradation over a submerging coast, where is developed one of the most mangrove system of the world, with almost 8,900 km2. This research has showed that orbital remote sensing data can provide excellent geologic and coastal land use information. The remote sensing data represents a powerful tool to understand the coastal processes in the wet tropical environments, mainly in the mangrove coasts, where the images allow a synoptic view of the area and provide geobotanic (relation between coastal environment and vegetation) and multitemporal information. In addition to integrated data, geographic information system (SIG) combines different data sets and simultaneously it facilitates the spatial and temporal analysis and the relationship between various coastal environments, allowing a more comprehensive, accurate and easier interpretation of the geomorphologic setting. Therefore, remote sensing data integration, SIG and auxiliary fieldwork data present a fundamental role to the integrated coastal zone management, environmental risk assessment, local characterization of the study sites, base maps upgrading and information dissemination for public consultation, which are all significant factors in this decision-making process.


Palavras-chave


mangroves; RADARSAT; Landsat.

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DOI: https://doi.org/10.22456/1807-9806.20310

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