@InProceedings{SousaFernCost:2015:MoCoAp,
               author = "Sousa, Gustavo Mota de and Fernandes, Manoel do Couto and Costa, 
                         Gilson Alexandre Ostwald Pedro da",
                title = "Modelagem do conhecimento aplicada a susceptibilidade de 
                         ocorr{\^e}ncia de inc{\^e}ndios no Parque Nacional de Itatiaia",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "4822--4827",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Forest fires result from numerous causes, usually triggered by 
                         human agents. Nevertheless, the landscape has several 
                         characteristics that can ease fire generation and spread, which 
                         are important indicators for the prevention and combat of forest 
                         fires. The goal of this paper is to contribute methodologically to 
                         the field of forest fire susceptibility mapping through the 
                         application of knowledge models built with conceptual support from 
                         Geoecology, Data Mining and GEOBIA techniques. The study area is 
                         located in Brazil, more specifically in a protected area known as 
                         the Itatiaia National Park, an Atlantic Forest reminiscent area 
                         between the states of Rio de Janeiro and Minas Gerais. Multiple 
                         data sources were used in the development of the methodology: 
                         AVNIR-2/ALOS imagery; Digital Elevation Models (DEM); and burned 
                         area reports acquired in situ from 2008 to 2012. The Geoecological 
                         variables were analyzed by means of data mining techniques which 
                         supported the generation of decision trees for susceptibility 
                         classification. Fire susceptibility mapping was then computed 
                         through a GEOBIA-based classification technique. The results 
                         showed that the susceptibility mapping produced is highly 
                         correlated with the actual forest fires that occurred in the Park, 
                         even though they define a smaller percentage of high 
                         susceptibility areas when compared to prior susceptibility mapping 
                         initiatives for the study area.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "941",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM4DAH",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4DAH",
           targetfile = "p0941.pdf",
                 type = "Classifica{\c{c}}{\~a}o e minera{\c{c}}{\~a}o de dados",
        urlaccessdate = "10 maio 2024"
}