@InProceedings{RoqueSanRocFigLam:2017:MéClAc,
               author = "Roque, Antoniane Arantes de Oliveira and Santos, Roberto de Barros 
                         and Rocha, Jansle Vieira and Figueiredo, Gleyce Kelly Dantas 
                         Ara{\'u}jo and Lamparelli, Rubens Augusto Camargo",
                title = "M{\'e}todos de classifica{\c{c}}{\~a}o e acompanhamento da 
                         din{\^a}mica de altera{\c{c}}{\~a}o do uso da terra nos 
                         munic{\'{\i}}pios de Anal{\^a}ndia e Santa Cruz da 
                         Concei{\c{c}}{\~a}o/SP ? 2001 a 2015",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "902--909",
         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 dynamics of the land-cover change, appears as the most 
                         important task at the present time, in which this activities have 
                         a direct influence on environmental resources available to 
                         society. The methods of the classification of remote sensing 
                         images are fundamental to understanding the dynamics of changing 
                         occupation of the territory, and are presented as a key tool for 
                         effective management of natural resources. This study aimed to 
                         define the best classifiers of images for the uses in the 
                         agricultural region of the center-east of Sao Paulo/Brazil, in the 
                         temporal cutouts 2001 and 2015, analyzing the ratings for each 
                         year, and between the two different years, using of error matrix 
                         and Kappa index. Was used images of Landsat (satellites 7 and 8), 
                         instruments ETM+ and OLI respectively, and processed in ENVI and 
                         ArcGIS. It was concluded that the classification supervised by 
                         distance of Mahalanobis should be used with caution in the event 
                         of clayey soils with high humidity, because the spectral signature 
                         of water is similar of soil wet, for this method of 
                         classification. In the analysis for the first year we obtained an 
                         overall accuracy of 85%, which is an good indicator of accuracy of 
                         the classificators selected. In the comparative analysis between 
                         the years under review, the overall accuracy was 26.3% and the 
                         Kappa index of 0.13, thus indicating that there was a significant 
                         change in land-cover. It is emphasized wich to carry out the land 
                         use classification, it is necessary to use more than one 
                         classifier.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "60081",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PS4FQE",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PS4FQE",
           targetfile = "60081.pdf",
                 type = "Mapeamento",
        urlaccessdate = "27 abr. 2024"
}