@InProceedings{MoreiraMarc:2001:AnReSe,
               author = "Moreira, Maur{\'{\i}}cio Alves and Marcelhas e Souza, 
                         {\'{\I}}ris de",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "An{\'a}lise de resultados de segmenta{\c{c}}{\~a}o por 
                         crescimento de regi{\~o}es em diferentes t{\'e}cnicas de 
                         processamento digital de dados do Landsat/TM para mapeamento de 
                         {\'a}reas cafeeiras",
            booktitle = "Anais...",
                 year = "2001",
               editor = "Krug, Thelma and Fonseca, Leila Maria Garcia",
                pages = "119--122",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 10. (SBSR).",
            publisher = "INPE",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "AGRONOMIA, Tr{\^e}s Pontas (MG), t{\'e}cnica de imageamento, 
                         reflect{\^a}ncia espectral, mapeador tem{\'a}tico (Landsat), 
                         imagens Landsat, classifica{\c{c}}{\~a}o de imagens, caf{\'e}, 
                         processamento de imagens, segmenta{\c{c}}{\~a}o de imagens, 
                         mistura, modelo, imaging technique, spectral reflectance, thematic 
                         mappers (Landsat), coffee, image classification, image processing, 
                         image segmentation, models, agronomy, mistures.",
             abstract = "This research has as objective to evaluate results derived from 
                         unsupervised segmentation and classification using different 
                         digital image processing techniques to map coffee areas. The 
                         methodology consist firstly, in adjustment of mean and variance 
                         value and filtration of the original Landsat/Tm image and applying 
                         segmentation and second the segmentation and classification of the 
                         spectral mixture model . All the results will be compare to true 
                         classification of the three areas in Tr{\^e}s Pontas city, one of 
                         the most coffee production in Minas Gerais state. We expect to be 
                         able to define the best processing that optimize the efficiency in 
                         segmentation process for mapping coffee areas.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "21-26 abr. 2001",
                 isbn = "85-17-00016-1",
                label = "9207",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais",
                  ibi = "dpi.inpe.br/lise/2001/09.13.10.56",
                  url = "http://urlib.net/ibi/dpi.inpe.br/lise/2001/09.13.10.56",
           targetfile = "0119.122.155.pdf",
                 type = "Agronomia",
        urlaccessdate = "16 jun. 2024"
}