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@InProceedings{SaitoSauParMadLim:2011:AvDeNa,
               author = "Saito, Silvia Midori and Sausen, Tania Maria and Pardi Lacruz, 
                         Maria Silvia and Madruga, Roberta and Lima Junior, Edgar da Rosa",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais  INPE} and {Instituto 
                         Nacional de Pesquisas Espaciais  INPE} and {Centro Regional de 
                         Educa{\c{c}}{\~a}o em Ci{\^e}ncia e Tecnologia Espacial para 
                         Am{\'e}rica Latina e o Caribe  CRECTEALC} and {Instituto 
                         Nacional de Pesquisas Espaciais  INPE} and {Instituto Nacional de 
                         Pesquisas Espaciais  INPE}",
                title = "Avalia{\c{c}}{\~a}o dos desastres naturais ocorridos no Rio 
                         Grande do Sul em 2008",
            booktitle = "Anais...",
                 year = "2011",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "4828--4834",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 15. (SBSR).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "extreme events, Geographic Information System, database, damage, 
                         eventos extremos, Sistema de Informa{\c{c}}{\~a}o 
                         Geogr{\'a}fica, banco de dados, danos.",
             abstract = "The aim of this paper is to analyze natural disaster occurrences 
                         in 2008 year at Rio Grande do Sul State in order to supply basic 
                         information of the most affected areas by them. Data of drought, 
                         landslide, storm, hail, flash flood, and gradual flood were taken 
                         from GEODESASTRES-SUL, which maintains an information system 
                         collection about natural disasters, from online daily news and 
                         Civil Defense homepage. Information as type of event, local, date, 
                         affected people were used to characterize natural disasters. A 
                         Geographic Information System (SPRING 5.1.4) was used to connect 
                         the natural disaster database to spatial information. It was 
                         possible to verify that 302 of 496 municipalities were affected by 
                         some natural disaster, mainly drought, storm and hail. Drought was 
                         the phenomenon which affected the most of the municipalities. This 
                         natural disaster reached twice the state from February to April 
                         and at December, especially in regions located at north and 
                         northwest. Storms and hail affected population in general without 
                         preferential areas. Concerning the flash flood and gradual flood, 
                         it was possible to identify that September was the month which 
                         presented the greatest number of events. It is important to 
                         highlight the need of this kind of analysis to identify possible 
                         standards of natural disasters occurrences. Therefore it could be 
                         possible to supply basic information of the most affected areas by 
                         some adverse event besides to support urban planning and Civil 
                         Defense actions to prevention damage procedures.",
  conference-location = "Curitiba",
      conference-year = "30 abr. - 5 maio 2011",
                 isbn = "{978-85-17-00056-0 (Internet)} and {978-85-17-00057-7 (DVD)}",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW/3A3P86B",
                  url = "http://urlib.net/rep/3ERPFQRTRW/3A3P86B",
           targetfile = "p0840.pdf",
        urlaccessdate = "2020, July 12"
}


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