@Article{CamarinhaCanaAlva:2013:ShLaPr,
               author = "Camarinha, Pedro Ivo Mioni and Canavesi, Vanessa and Alval{\'a}, 
                         Regina C{\'e}lia dos Santos",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Shallow landslide prediction and analysis with risk assessment 
                         using a spatial model in the coastal region in the state of 
                         S{\~a}o Paulo, Brazil",
              journal = "Natural Hazards and Earth System Sciences Discussion",
                 year = "2013",
               volume = "1",
               number = "5",
                pages = "5199--5236",
             keywords = "landslide, fuzzy gamma, risk assesment.",
             abstract = "In Brazil, most of the disasters involving landslide occur in 
                         coastal regions, with population density concentrated on steep 
                         slopes. Thus, different approaches have been used to evaluate the 
                         landslide risk, although the greatest difficulty is related to the 
                         scarcity of spatial data with good quality. In this context, four 
                         cities located on the southeast coast of Brazil Santos, 
                         Cubat{\~a}o, Caraguatatuba and Ubatuba in a region with the rough 
                         reliefs of the Serra do Mar and with a history of natural 
                         disasters were evaluated. Spatial prediction by fuzzy gamma 
                         technique was used for the landslide susceptibility mapping, 
                         considering environmental variables from data and software in the 
                         public domain. To validate the susceptibility mapping results, it 
                         was overlapped with risk sectors provided by the Geological Survey 
                         of Brazil (CPRM). A positive correlation was observed between the 
                         classes most susceptible and the location of these sectors. The 
                         results were also analyzed from the categorization of risk levels 
                         provided by CPRM. To compare the approach with other studies using 
                         landslide-scar maps, correlated indexes were evaluated, which also 
                         showed satisfactory results, thus indicating that the methodology 
                         presented is appropriate for risk assessment in urban areas and 
                         can be replicated to municipalities that do not have risk areas 
                         mapped.",
                  doi = "10.5194/nhessd-1-5199-2013",
                  url = "http://dx.doi.org/10.5194/nhessd-1-5199-2013",
                 issn = "2195-9269",
                label = "lattes: 0554631424547411 1 CamarinhaCanaAlva:2013:ShLaPr",
             language = "en",
                  url = "http://www.nat-hazards-earth-syst-sci-discuss.net/1/5199/2013/nhessd-1-5199-2013.html",
        urlaccessdate = "28 abr. 2024"
}