@Article{OmachiSCMCGTST:2018:AtFoLo,
               author = "Omachi, Claudia Y. and Siani, Sacha Maru{\~a} Ortiz and Chagas, 
                         Felipe M. and Mascagni, M{\'a}rio L. and Cordeiro, Marcelle and 
                         Garcia, Gizele D. and Thompson, Cristiane C. and Siegle, Eduardo 
                         and Thompson, Fabiano L.",
          affiliation = "{Universidade Federal do Rio de Janeiro (UFRJ)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {SIAA Meio Ambiente e 
                         Tecnologia} and {SIAA Meio Ambiente e Tecnologia} and {SIAA Meio 
                         Ambiente e Tecnologia} and {SIAA Meio Ambiente e Tecnologia} and 
                         {SIAA Meio Ambiente e Tecnologia} and {SIAA Meio Ambiente e 
                         Tecnologia} and {SIAA Meio Ambiente e Tecnologia}",
                title = "Atlantic Forest loss caused by the world´s largest tailing dam 
                         collapse (Fund{\~a}o Dam, Mariana, Brazil)",
              journal = "Remote Sensing Applications: Society and Environment",
                 year = "2018",
               volume = "12",
                pages = "30--34",
                month = "Nov.",
             keywords = "Doce River, NDVI, Forest loss, Landsat, Atlantic Forest.",
             abstract = "The collapse of Fund{\~a}o dam in Mariana, Minas Gerais, Brazil, 
                         released more than 50 million cubic meters of ore tailings into 
                         the environment, representing the world's largest mining disaster. 
                         Three analyses estimating the forest loss to the ore tailings were 
                         produced soon after the collapse but the values varied threefold 
                         between them due to differences in objective and spatial 
                         resolution. Our aim was to estimate the riverside forest loss due 
                         to the flooding of the ore tailings. We analyzed Landsat 
                         Normalized Difference Vegetation Indexes (NDVI) with the digital 
                         elevation model (DEM) specific for flooded forest and limited to 
                         analyze an area floodable and contiguous from the water stream. 
                         Our forest loss quantification resulted in the same order of 
                         magnitude than the two of previous estimates. The area other than 
                         forest flooded by the ore tailings accounted for 1176.6 ha. The 
                         loss of the forest area due to the collapse was 457.6 ha and 
                         concentrated along the first 74 km from the Fund{\~a}o Dam.",
                  doi = "10.1016/j.rsase.2018.08.003",
                  url = "http://dx.doi.org/10.1016/j.rsase.2018.08.003",
                 issn = "2352-9385",
             language = "en",
           targetfile = "omachi_atlantic.pdf",
        urlaccessdate = "27 abr. 2024"
}