@InProceedings{OliveiraFort:2017:AnMuCr,
               author = "Oliveira, Matheus Serri Moulin de and Fortes, Paulo de Tarso Ferro 
                         Oliveira",
                title = "An{\'a}lise multitemporal do crescimento de {\'a}reas de 
                         minera{\c{c}}{\~a}o nos m{\'a}rmores da Serra de Itaoca, sul do 
                         Esp{\'{\i}}rito Santo",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "5424--5431",
         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 development of mining in Itaoca Ridge, Cachoeiro de 
                         Itapemirim, south of Esp{\'{\i}}rito Santo, Brazil, has 
                         increased considerably in last 30 years. This work has as 
                         objective the study multitemporal of mining expansion areas in 
                         this region. Were utilized images of Landsat 5, 7 e 8 satellites 
                         of 1987, 1999, 2007 and 2016 years. These images were preprocessed 
                         with clipping, contrast and afertly processed in bands 
                         compositions, segmentation and classification. Finally, the 
                         products generated in processing stage were evaluated and compared 
                         with orthophotos. The best RGB composition was RGB 421 in Landsat 
                         satellities 5 and 7, however for Landsat 8 satellite the best was 
                         RGB 532. In the segmentation technical was employed 80 and 1000 of 
                         similarity and 1 to 5 pixel area attributes, while the 
                         classification technical utilized acceptance limit of 75% or 95% 
                         and 5 iterations numbers. The results showed that the classes 
                         generated for segmentation and classification were able to 
                         distinguished mining areas to urban center, but were unable to 
                         distinguished mining areas to exposed ground zones. The increases 
                         was of almost 1000% in 30 years due the increases of exportation 
                         and Brazilian intern market development since 2000 year.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59973",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSM4RS",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSM4RS",
           targetfile = "59973.pdf",
                 type = "An{\'a}lise de s{\'e}ries temporais de imagens de 
                         sat{\'e}lite",
        urlaccessdate = "27 abr. 2024"
}