@InProceedings{RodriguesRodTagCarCam:2017:DeAcSI,
               author = "Rodrigues, Mikael Tim{\'o}teo and Rodrigues, Bruno Tim{\'o}teo 
                         and Tagliarini, Felipe de Souza Nogueira and Cardoso, Lincoln 
                         Gehring and Campos, S{\'e}rgio",
                title = "Desempenho e acur{\'a}cia dos SIGs Terra View e Idrisi e seus 
                         respectivos classificadores supervisionados",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "2263--2270",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "The main objective of this study is to investigate the performance 
                         of TerraView 4.2.2 and Idrisi Selva performing classification 
                         oversees through the spectral pattern on Landsat 5, associated 
                         with comparing the land use of the river Capivara watershed, 
                         inserted in the municipality of Botucatu, S{\~a}o Paulo, Brazil. 
                         The areas of supervised training were defined through seven land 
                         use classes, founded by the Manual Use of Technical IBGE Earth. In 
                         the region of Capivara watershed, they are practiced multiple 
                         types of management, which can be found planting crops from 
                         subsistence scale, through small and medium-sized farms, to major 
                         agro-industrial structures, thus providing a panorama of great 
                         complexity to mapped and subsequently patterned. An aggravating 
                         the methodology were the weed common in cultivated pastures and 
                         soils with various forms of culture, because they cause 
                         interference in the spectral pattern of land use classes, thus 
                         providing noise that changed the pure spectral response of crops 
                         inducing error digital classification. Post-classification also 
                         improved matrix realignment estimates for removal of pixel groups, 
                         reaching a higher order than 50% accuracy, increasing accuracy, 
                         allowing a lower inclusion of items of other classes, thus making 
                         it the best classification. Unlike the products derived from the 
                         supervised classification by maximum likelihood post classified 
                         with the majority filter, which after reclassification accuracy 
                         was high, presented fewer errors, as well as smoothing of 
                         classified maps.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59441",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSLQ99",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSLQ99",
           targetfile = "59441.pdf",
                 type = "Bacias hidrogr{\'a}ficas",
        urlaccessdate = "27 abr. 2024"
}