@InProceedings{CoelhoCarvBarr:2017:RJClDi,
               author = "Coelho, Raphael Corr{\^e}a de Souza and Carvalho, Marcus 
                         Vin{\'{\i}}cius Alves de and Barros, Rafael Silva de",
                title = "Mapeamento da cobertura da terra no Parque Estadual da Serra da 
                         Conc{\'o}rdia (PESC) - RJ atrav{\'e}s de 
                         classifica{\c{c}}{\~a}o digital h{\'{\i}}brida",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "4635--4642",
         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 objective of this study is to evaluate different spectral 
                         indices (EVI, NDVI, Modified NDVI, NDWI), transformed images (PCA 
                         and IHS), and the Linear Spectral Mixing Model (fraction-image: 
                         Soil) in an application of GEOBIA: Geographic Object-Based Image 
                         Analysis (knowledge modeling: heuristic approach integrated to the 
                         discovery of patterns: geographic data mining) in images from the 
                         REIS-2 (Earth Imaging System-2) sensor of the RapidEye satellite. 
                         The study area is the Parque Estadual da Serra da Conc{\'o}rdia 
                         (PESC), a Nature Conservation Unit (UC) inserted in the Atlantic 
                         Forest Biome in the Rio de Janeiro state, Brazil. The first step 
                         consisted of the atmospheric correction of the images using 6S 
                         algorithm. This process presented a satisfactory result, due to 
                         being in agreement with the Scientific Literature. It was observed 
                         that the PCA (Principal Component Analysis) and HIS (Intensity, 
                         Hue and Saturation) images, besides helping to elaborate the class 
                         descriptors, also contributed to reduce the internal heterogeneity 
                         of the classes in the segmentation process. The Modified NDVI, 
                         generated from the change of the Red band (630-685nm) by the 
                         Red-Edge band (690 to 730 nm) was to highlight well objects of 
                         vegetation. The thematic mapping generated reached global accuracy 
                         of 87.76% and Kappa Index of 84.54%.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59887",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSM3ES",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSM3ES",
           targetfile = "59887.pdf",
                 type = "Processamento de imagens",
        urlaccessdate = "27 abr. 2024"
}