@Article{HawakawaZanAndBerRos:2010:IdPaBa,
               author = "Hawakawa, Ericson Hideki and Zani, Hiran and Andrades Filho, 
                         Cl{\'o}dis Oliveira and Bertani, Thiago and Rossetti, Dilce de 
                         F{\'a}tima",
          affiliation = "{Aluno de doutorado do Instituto Nacional de Pesquisas Espaciais e 
                         Professor Assistente da Universidade Federal de Alfenas (UNIFAL)} 
                         and {Aluno de doutorado do Instituto Nacional de Pesquisas 
                         Espaciais e Professor Assistente da Universidade Federal de 
                         Alfenas (UNIFAL)} and {} and {Bolsista de mestrado CNPq e aluno do 
                         Instituto Nacional de Pesquisas Espaciais} and {Instituto Nacional 
                         de Pesquisas Espaciais (INPE)}",
                title = "Identifica{\c{c}}{\~a}o de paleocanais na bacia Amaz{\^o}nica a 
                         partir de dados de sensoriamento remoto",
              journal = "Revista de Geografia (Recife)",
                 year = "2010",
               volume = "27",
               number = "1 Esp",
                pages = "20--33",
                month = "Set.",
             keywords = "paleocanais, Amaz{\^o}nia, PALSAR, SRTM, Landsat-5/TM, 
                         paleochannels, Amazonian, PALSAR, SRTM, Landsat-5/TM.",
             abstract = "A reconstitui{\c{c}}{\~a}o paleogeogr{\'a}fica dos sistemas de 
                         drenagem {\'e} fundamental na identifica{\c{c}}{\~a}o e 
                         compreens{\~a}o de vari{\'a}veis (p.e., clima, relevo, solo, 
                         litologia, tect{\^o}nica, vegeta{\c{c}}{\~a}o, n{\'{\i}}vel 
                         do mar) que conduziram sua evolu{\c{c}}{\~a}o, principalmente na 
                         Era Cenoz{\'o}ica. A identifica{\c{c}}{\~a}o de 
                         fei{\c{c}}{\~o}es como paleocanais pode auxiliar nesta complexa 
                         tarefa de reconstitui{\c{c}}{\~a}o da evolu{\c{c}}{\~a}o de 
                         sistemas fluviais. Diferentes dados de sensoriamento remoto e 
                         t{\'e}cnicas de processamento digital de imagens podem dinamizar 
                         esta tarefa, principalmente na Amaz{\^o}nia, onde a dimens{\~a}o 
                         da {\'a}rea e o restrito acesso dificultam estudos desse 
                         car{\'a}ter. Neste sentido, o objetivo deste trabalho {\'e} 
                         utilizar diferentes dados de sensoriamento remoto e t{\'e}cnicas 
                         de processamento digital de imagens para identificar paleocanais e 
                         demais fei{\c{c}}{\~o}es fluviais no ambiente amaz{\^o}nico. 
                         Este trabalho baseia-se no processamento digital e an{\'a}lise de 
                         imagens Landsat-5/TM, de modelos digitais de eleva{\c{c}}{\~a}o 
                         (MDE) provenientes da SRTM e de imagens do radar PALSAR. Os 
                         resultados indicam que as imagens de radar provenientes do sensor 
                         PALSAR em polariza{\c{c}}{\~a}o HH foram eficientes na 
                         distin{\c{c}}{\~a}o e delimita{\c{c}}{\~a}o das {\'a}reas de 
                         plan{\'{\i}}cie de inunda{\c{c}}{\~a}o. J{\'a} a 
                         identifica{\c{c}}{\~a}o dos paleocanais obteve melhor resultado 
                         na polariza{\c{c}}{\~a}o HV. Os resultados obtidos pelo 
                         processamento dos MDE-SRTM revelaram demais paleocanais que 
                         estavam ocultos e/ou mascarados dado {\`a} densa cobertura 
                         vegetal. ABSTRACT The paleogeographic reconstitution of drainage 
                         systems is essential in order to identify the variables (e.g., 
                         climate, topography, soil, lithology, tectonics, vegetation, sea 
                         level) that control its evolution, particularly during the 
                         Cenozoic Era. The identification of paleochannels features can 
                         assist the identification of ancient fluvial systems. Currently, 
                         remote sensing data and its respective techniques (e.g., digital 
                         image processing) can aid broad observations and are essential for 
                         environments like Amazon, where the size and difficult access can 
                         hinder studies of this character. In this sense, our objective 
                         apply remote sensing data and techniques of digital image 
                         processing to identify paleochannels and modern rivers in the 
                         Amazon, aiming to extract features to help us characterize the 
                         area as well as in its paleogeographic reconstruction. This work 
                         is based on digital processing and image analysis of the following 
                         products: Landsat-5/TM, SRTM digital elevation model and PALSAR 
                         imagery. The results indicate that the radar images from PALSAR 
                         sensor in HH polarization were effective in the distinction and 
                         delimitation of floodplains. On the other hand, PALSAR images with 
                         HV polarization had a better performance for identification of 
                         paleochannels. The results obtained with SRTM enhanced 
                         paleochannels that were hidden due to dense vegetation cover. Key 
                         Words: paleochannels, Amazonian, PALSAR, SRTM, Landsat-5/TM.",
                 issn = "0104-5490",
                label = "lattes: 3368934680028882 2 HawakawaZanAndBerRos:2010:IdPaBa",
             language = "pt",
           targetfile = "331-1112-1-PB-1.pdf",
        urlaccessdate = "04 maio 2024"
}