@InProceedings{DéstroInojDiasBott:2009:ÁrRiAm,
               author = "D{\'e}stro, Guilherme Fernando Gomes and Inojosa, Fernanda Cunha 
                         Pirillo and Dias, Jailton and Bottura, Giovana",
          affiliation = "{Coordena{\c{c}}{\~a}o de Zoneamento Ambiental - IBAMA/DF} and 
                         {Coordena{\c{c}}{\~a}o Geral de Emerg{\^e}ncias Ambientais - 
                         IBAMA/DF} and {Coordena{\c{c}}{\~a}o de Zoneamento Ambiental - 
                         IBAMA/DF} and {Coordena{\c{c}}{\~a}o de Zoneamento Ambiental - 
                         IBAMA/DF}",
                title = "{\'A}reas de risco ambiental por barragens no Estado de Minas 
                         Gerais",
            booktitle = "Anais...",
                 year = "2009",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "5193--5200",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 14. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "environmental risk, dam, ArcGis, environmental sensibility, Minas 
                         Gerais state.",
             abstract = "Environmental risk mapping is an interesting tool to assist 
                         government agents, considering that it´s technical and scientific 
                         approach can provide a guide to public policies formulation. 
                         Besides bringing dynamism to the decision making process, such 
                         tool involves a great variety of disciplines and knowledge areas. 
                         However, easily applicable methodologies, aimed specifically to 
                         environmental risk mapping, are still scarce. In this context, the 
                         present work is focused on the development of a risk mapping 
                         method based on geographic information system - GIS. For this 
                         pilot project, mining dams in Minas Gerais state, Brazil, were 
                         chosen as potential causes of environmental accidents. The 
                         environmental risk map proposed is the result of the intersection 
                         of a sensitivity map and a threat map, caused by mining dams and 
                         associated hazards. A multi-criteria approach was used in GIS 
                         (ArcGis 9.2), achieved by an analytic hierarchy process (AHP), and 
                         weighted linear combination - which means summing different 
                         variables calculated by Euclidean distance, with estimated values 
                         according to the variable´s relative importance. Threat, 
                         sensitivity and risk levels were categorized in: {"}extremely 
                         high{"}, {"}high{"}, {"}medium{"}, {"}low{"} and {"}extremely 
                         low{"}. It was possible to verify that Belo Horizonte metropolitan 
                         area was considered the most risky concerning mining dams; which 
                         can be explained by environmental sensitivity (due to intrinsic 
                         characteristics) and dams concentration. In conclusion, the method 
                         proposed by this work has been proved effective to risk mapping, 
                         if there are previous environmental information available, such as 
                         topology and drainage maps.",
  conference-location = "Natal",
      conference-year = "25-30 abr. 2009",
                 isbn = "978-85-17-00044-7",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "dpi.inpe.br/sbsr@80/2008/11.06.11.50",
                  url = "http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2008/11.06.11.50",
           targetfile = "5193-5200.pdf",
                 type = "Monitoramento e Modelagem Ambiental",
        urlaccessdate = "17 maio 2024"
}