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@Article{CarvalhoJoBeLoSoSa:2018:CoGeIn,
               author = "Carvalho, Tiago and Jorge, Aurelienne Apareida Souza and 
                         Bernardes, Tiago and Londe, Luciana R. and Soriano, Erico and 
                         Santos, Leonardo B. L.",
          affiliation = "{Instituto Federal de S{\~a}o Paulo (IFSP)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Centro Nacional de 
                         Monitoramento e Alertas de Desastre Naturais (CEMADEN)} and 
                         {Centro Nacional de Monitoramento e Alertas de Desastre Naturais 
                         (CEMADEN)} and {Universidade Federal de S{\~a}o Carlos (UFSCar)} 
                         and {Centro Nacional de Monitoramento e Alertas de Desastre 
                         Naturais (CEMADEN)}",
                title = "A computational geographical index on road networks for disaster 
                         risk reduction",
              journal = "IEEE Latin America Transactions",
                 year = "2018",
               volume = "16",
               number = "5",
                pages = "1454--1459",
                month = "May",
             keywords = "Geographical Databases, Geoprocessing, Floods, Landslides, 
                         Cemaden.",
             abstract = "In a scenario of global change, extreme weather and climatic 
                         events are expected to increase in frequency and intensity and 
                         cause more social and economic impacts in several sectors, such as 
                         the transportation system. This work analyzes geographical 
                         measures (distance and coverage) for the Brazilian road network 
                         taking both the susceptible areas to the occurrence of disasters 
                         and the multi-institutional meteorological observational network, 
                         in order to propose an index of fragility, calculated in a 
                         Geographical Database. The results show 26 highway stretches very 
                         close to areas of susceptibility and not covered by any of the 
                         monitoring tools.",
                  doi = "10.1109/TLA.2018.8408441",
                  url = "http://dx.doi.org/10.1109/TLA.2018.8408441",
                 issn = "1548-0992",
             language = "en",
           targetfile = "carvalho_computational.pdf",
        urlaccessdate = "24 nov. 2020"
}


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