@InProceedings{AboudNetaDuScNeFrSi:2009:UtImPo,
               author = "Aboud Neta, Sumaia Resegue and Dutra, Luciano Vieira and Scofield, 
                         Graziela Balda and Negri, Rog{\'e}rio Galante and Freitas, Corina 
                         da Costa and Silva, Daniel Lu{\'{\i}}s Andrade e",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Compara{\c{c}}{\~a}o entre classifica{\c{c}}{\~a}o contextual 
                         e classifica{\c{c}}{\~a}o por regi{\~o}es para mapeamento de 
                         uso e cobertura da terra na regi{\~a}o da Floresta Nacional de 
                         Tapaj{\'o}s - PA (FLONA): utilizando imagens polarim{\'e}tricas 
                         em banda L",
            booktitle = "Anais...",
                 year = "2009",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "7749--7756",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 14. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "remote sensing, polarimetric, MAXVER-ICM, Bhattacharyya, 
                         ALOS/PALSAR, sensoriamento remoto, polarim{\'e}trico.",
             abstract = "The ALOS PALSAR (Phased Array type L-band Synthetic Aperture 
                         Radar) sensor can provide full polarimetric data (HH, HV and VV) 
                         for scientific purposes. Dutra et al.(2008) showed that, from the 
                         three possible channels, HH-HV channels presented better 
                         classification results when the following five classes are used: 
                         primary forest, secondary forest, bare soil, agriculture and 
                         degraded forest. This study is extending the former work by 
                         increasing the number of classes, including now pasture and dirty 
                         pasture, and testing if contextual classification can improve the 
                         overall accuracy. The results showed that the contextual 
                         classification does improve the per point classification results, 
                         however not as good as region classification when SEGSAR 
                         segmentation is used. Region based classification, particularly 
                         the one developed to take in account as much as possible the radar 
                         statistical behavior, performed better for VV-HV channels with 
                         98.6% of overall accuracy using gamma filter on image and 92.7% 
                         without gamma filter on image. Comparing this study with Dutra et 
                         al.(2008), it was possible to observe that the better channels are 
                         different, with only two classes more, which shows that the best 
                         channels set is totally dependent on a particular set of classes 
                         being considered. So, the best dual polarization depends on the 
                         desired land use application, but the HV channels seems to be 
                         always chosen. The presence of HV channel in the dual polarization 
                         products provide the better combinations for general mapping of 
                         the rain forest problem.",
  conference-location = "Natal",
      conference-year = "25-30 abr. 2009",
                 isbn = "978-85-17-00044-7",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "dpi.inpe.br/sbsr@80/2008/11.16.03.20",
                  url = "http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2008/11.16.03.20",
           targetfile = "7749-7756.pdf",
                 type = "T{\'e}cnicas de Classifica{\c{c}}{\~a}o e Minera{\c{c}}{\~a}o 
                         de Dados",
        urlaccessdate = "18 jun. 2024"
}