@InProceedings{PradoMaHaTaAlSh:2009:SeClOr,
               author = "Prado, Bruno Rodrigues do and Martins, Vagner Azarias and 
                         Hayakawa, Ericson Hideki and Tavares J{\'u}nior, Jo{\~a}o 
                         Batista and Almeida Filho, Raimundo and Shimabukuro, Yosio 
                         Edemir",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais - INPE} and {Instituto 
                         Nacional de Pesquisas Espaciais - INPE} and {Instituto Nacional de 
                         Pesquisas Espaciais - INPE} and {Universidade Federal do 
                         Paran{\'a} - UFPR} and {Instituto Nacional de Pesquisas Espaciais 
                         - INPE} and {Instituto Nacional de Pesquisas Espaciais - INPE}",
                title = "Segmenta{\c{c}}{\~a}o e classifica{\c{c}}{\~a}o orientada a 
                         objeto de imagens ALOS/PALSAR para a identifica{\c{c}}{\~a}o de 
                         classes de cobertura da terra na Amaz{\^o}nia",
            booktitle = "Anais...",
                 year = "2009",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "7401--7408",
         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 = "amplitude data, L band, tropical forest, synthetic aperture radar, 
                         dados de amplitude, banda L, floresta tropical, radar de abertura 
                         sint{\'e}tica.",
             abstract = "Currently the microwave remote sensing for monitoring the 
                         environment has been gaining much attention. The main goal of this 
                         research is to apply the object oriented classification in L-band 
                         synthetic aperture radar (SAR) data for mapping and quantifying 
                         the following land cover/land use classes: Primary Forest, 
                         Degraded Forest (degraded and secondary forest), Bare Soil and 
                         Agriculture (agriculture and pasture). Monitoring land cover and 
                         land use is important for tropical environment and is necessary to 
                         know the land use patterns and to identify the agents of change. A 
                         polarimetric scene of ALOS/PALSAR (FBD, 1.5 level), acquired on 
                         August 21, 2006, was used in this work. Gamma speckle filtering 
                         method (window 5x5) was applied to the radar data in the amplitude 
                         image format. The object oriented classification was carried out 
                         using Definiens eCognition software. Multiresolution segmentation 
                         and boolean logic based classification are the main key process. 
                         The study area covers the municipality of Cl{\'a}udia, located in 
                         the north region of Mato Grosso state, Brazilian Amazon. PRODES, 
                         DETER, and Landsat Thematic Mapper (TM) data covering the study 
                         area were used to evaluate the performance of the classification. 
                         The confusion matrix was used to assess the classification 
                         accuracy using Kappa coefficient of agreement and overall 
                         accuracy. Initial results indicate that, no phase considered, the 
                         cross-polarized (horizontal - vertical) image can improve the 
                         distinction between land cover/land use classes, especially 
                         primary forest, degraded (recently deforested areas), and 
                         secondary forest.",
  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@80/2008/11.17.15.12",
                  url = "http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2008/11.17.15.12",
           targetfile = "7401-7408.pdf",
                 type = "Radar: Pesquisa, Desenvolvimento e Aplica{\c{c}}{\~o}es",
        urlaccessdate = "13 maio 2024"
}