Reconhecimento e mapeamento de ambientes sedimentares através de imagens LANDSAT-7 ETM+, RADARSAT-1 WIDE e SRTM da baía do Caeté (PA) a baia de Maracaçumé (MA)

Abstract

From the 1980s onwards, with the launch of the Landsat TM series of satellites, orbital images began to be extensively used in coastal geological and geomorphological mapping. These remote sensor products are sources of geographic information, providing important subsidies for analyzes in the domain of space and time. The studied area is located in the best preserved humid tropical environment on the planet, the Amazon Region, more specifically along the mangrove coast of the northeast of the State of Pará and northwest of Maranhão. The area is part of a set of independent basins, where the main river is the Gurupi, on the border between Pará and Maranhão. The objective of this dissertation was to accurately recognize and map the different coastal environments, using images from remote optical and microwave sensors integrated with digital elevation models (DEM), generated by the Shuttle Radar Topography Mission (SRTM) program. The dataset used for this purpose included RADARSAT-1 images from January and February 2003 and September and October 2004; Landsat ETM+ August 7, 1999; and digital elevation models (SRTM) from February 2000. The synergisms of these data used IHS transformation techniques and principal components. In this way, it was possible to apply classical methodologies in Geographic Information Systems for mapping coastal environments. As a result, 15 coastal environments were mapped, grouped into 4 geomorphological domains: coastal plateau, paleodunes, coastal plain (muddy tide plain without vegetation, mangroves, saline marshes, freshwater marshes, frontal dune cord, interdunes, current dunes, macro-tidal beach), estuarine plain (estuarine channel, sandy tidal bar, ebb tide delta) and alluvial plain (lakes and floodplain). , ETM+ AND SRTM, generated a lot of information for the recognition of coastal environments, as they were able to integrate in a single product important characteristics of their particular sensor with those of another, complementing each other, producing maps with high detail.