@InProceedings{RufattoRicMenFerPia:2017:MaÁrVe,
               author = "Rufatto, Mariana Eveli and Richetti, Jonathan and Mengue, Diego 
                         Hendler Scheffer and Fernandes, Gustavo and Piasecki, Allice",
                title = "Primeiras Experi{\^e}ncias com Setinel-2: Mapeamento de {\'A}rea 
                         Verdes na regi{\~a}o Sudoeste do Paran{\'a}",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "6582--6587",
         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 = "Changes related to land use and vegetation cover are extremely 
                         dynamic. Factors associated with economic development influence 
                         the changes of the landscape by man, which combined with poor 
                         urban planning, cause many environmental impacts. The efficiency 
                         of the environmental management of a territory depends largely on 
                         surveys and previous systematic studies on the main elements and 
                         conditions of the physical environment. In this context, one of 
                         the most powerful analytical tools to mitigate and reduce the 
                         destructive effects of environmental disasters is mapping risk 
                         areas by remote sensing. This technology is emerging as an 
                         important tool for spatial analysis of various targets without the 
                         need of transportation fields, being valuable in gathering data 
                         quickly and relatively low cost. One of the main steps for the 
                         preparation of this map is the mapping of vegetation, using 
                         methods and GIS techniques and remote sensing with satellite 
                         imagery analysis. Therefore, this study aims to classify satellite 
                         images of Sentinel-2 satellite, through the supervised 
                         classification maximum likelihood method, and thus obtain reliable 
                         results for the mapping of green areas. Therefore, it is evident 
                         the importance of using tools and digital processing technologies 
                         for high-resolution images for the mapping of vegetation cover the 
                         State of Paran{\'a}, and the relevance of the decision-making 
                         subsidy to prevent possible natural disasters and humans.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59822",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMD74",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMD74",
           targetfile = "59822.pdf",
                 type = "Mapeamento",
        urlaccessdate = "27 abr. 2024"
}