@InProceedings{OliveiraMata:2013:AvDeCl,
               author = "Oliveira, Bruno Silva and Mataveli, Guilherme Augusto Verola",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Avalia{\c{c}}{\~a}o do desempenho dos classificadores Isoseg e 
                         Bhattacharya para o mapeamento de {\'a}reas de 
                         cana-de-a{\c{c}}{\'u}car no munic{\'{\i}}pio de Barretos-SP",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "89--96",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 16. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Sugarcane is one of the most important crops for Brazils economy. 
                         The increase in global demand for sugarcanes ethanol requires the 
                         conversion of areas of conventional crops in sugarcane cultivation 
                         areas, making it necessary to know the level of expansion of this 
                         culture. The CANASAT project is mapping sugarcane areas in South 
                         central Brazil, using visual interpretation to generate sugarcane 
                         cultivation maps. The use of automatic classifiers must be 
                         improved, searching for new alternatives for mapping sugarcane. 
                         This study aimed to apply automatic classifiers for mapping areas 
                         of sugarcane in the city of Barretos-SP, comparing the performance 
                         of these classifiers with the map of CANASAT project for this 
                         municipality. We tested the classifiers Isoseg and Bhattacharya, 
                         and the GIS used was SPRING 4.3.3. Comparing the two classifiers 
                         evaluated, Bhattacharya achieved the best results, with a Kappa 
                         index of 0.47, which is considered good, while the Isoseg was 
                         considered reasonable. The sugarcane areas that were at maximum 
                         vigor were classified correctly, but in areas at the beginning of 
                         vegetative cycle, after harvest or in reform generated errors of 
                         omission and inclusion, what shows the need of multitemporal 
                         analysis for mapping sugarcane. However, the classification based 
                         on visual interpretation still shows up the most appropriate way 
                         to do this mapping.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "13-18 abr. 2013",
                 isbn = "{978-85-17-00066-9 (Internet)} and {978-85-17-00065-2 (DVD)}",
                label = "863",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GGEM",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GGEM",
           targetfile = "p0863.pdf",
                 type = "Agricultura",
        urlaccessdate = "18 jun. 2024"
}