@InProceedings{PachecoKux:2017:IdCiDe,
               author = "Pacheco, T{\'e}hrrie Caroline K{\"o}nig Ferraz and Kux, Hermann 
                         Johann Heinrich",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Identifica{\c{c}}{\~a}o de cicatrizes de deslizamento no 
                         munic{\'{\i}}pio de Campos do Jord{\~a}o-SP com imagens de 
                         alt{\'{\i}}ssima resolu{\c{c}}{\~a}o espacial",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "3393--3398",
         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 = "Natural disasters occur all over the world, and landslides are a 
                         common problem in tropical countries, like Brazil. Remote Sensing 
                         techniques help to improve monitoring of areas with steep slopes. 
                         The aim of this work is to identify landslide scars and elaborate 
                         a risk map. Images from IKONOS sensor system were used to enhance 
                         the visual interpretation through the fusion of multi-spectral and 
                         panchromatic bands, and an RGB to HIS transformation, using ENVI 
                         5.3 software. Further processing will include a database from 
                         CEMADEM, our partner in this work, including data mining, to 
                         select the best attributes for image segmentation and 
                         classification, using the E-cognition software. The classification 
                         process is based on the Object-Based Image Analysis (OBIA) 
                         paradigm, which is the most indicated approach for studies based 
                         on satellite images with very high spatial resolution.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "60050",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSLSRQ",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSLSRQ",
           targetfile = "60050.pdf",
                 type = "Geomorfologia",
        urlaccessdate = "27 abr. 2024"
}