@InProceedings{SoaresSantBarrFran:2017:SPUtDa,
               author = "Soares, Adilson and Santana, Willian Reis de and Barradas, Thais 
                         Fernandes and Franchi, Jos{\'e} Guilherme",
                title = "Mapeamento da Suscetibilidade a movimentos de massa no 
                         Munic{\'{\i}}pio de Santo Andr{\'e} - SP utilizando dados 
                         geol{\'o}gicos e de Sensoriamento Remoto",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "6521--6528",
         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 = "This paper presents a methodology for susceptibility mapping of 
                         shallow landslides just from data and software from the public 
                         domain. The study was conducted in a mountainous region located on 
                         Santo Andr{\'e} City, in the state of S{\~a}o Paulo. The 
                         susceptibility mapping was generated based on the following maps: 
                         geological, slope, vertical curvatures, lineament density and land 
                         use. The thematic classes of these maps were weighted according to 
                         technical and scientific criteria related to the triggering of 
                         landslides. A numerical rating scheme for the factors was 
                         developed for spatial data analysis in a GIS. The resulting 
                         landslide susceptibility map delineates the area into different 
                         zones of four relative susceptibility classes: very high, high, 
                         moderate and very low. The results show that some urban areas were 
                         built on high and very high risk areas. Slope and lithology are 
                         the factors that most influence susceptibility classes.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59514",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMD3R",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMD3R",
           targetfile = "59514.pdf",
                 type = "Geomorfologia",
        urlaccessdate = "27 abr. 2024"
}