@InProceedings{MonteiroSouzLing:2005:AvImAb,
               author = "Monteiro, Andr{\'e} Luiz Silva and Souza J{\'u}nior, Carlos 
                         Moreira de and Lingnau, Christel",
          affiliation = "{Instituto do Homem e Meio Ambiente da Amaz{\^o}nia (IMAZON). 
                         Universidade Federal do Paran{\'a} (UFPR).} and {Instituto do 
                         Homem e Meio Ambiente da Amaz{\^o}nia (IMAZON)} and {Universidade 
                         Federal do Paran{\'a} (UFPR)}",
                title = "Avalia{\c{c}}{\~a}o de imagem de abund{\^a}ncia de 
                         vegeta{\c{c}}{\~a}o para o monitoramento de indicadores de 
                         manejo florestal na Amaz{\^o}nia",
            booktitle = "Anais...",
                 year = "2005",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Fonseca, Leila Maria 
                         Garcia",
                pages = "3151--3158",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 12. (SBSR)",
            publisher = "INPE",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "sensoriamento remoto, modelo de mistura espectral, 
                         explora{\c{c}}{\~a}o madeireira, impacto no dossel, 
                         Amaz{\^o}nia, remote sensing, spectral mixing models, selective 
                         logging, canopy disturbance, Amazon.",
             abstract = "Several recent studies have demonstrated the potential of 
                         satellite images to monitor selective logging in the Amazon 
                         region. However, there is a lack of remote sensing studies to 
                         evaluate the quality of forest management practiced by logging 
                         activity. In this study, we carried out a temporal analysis of 
                         vegetation fraction images (Landsat ETM+), obtained through 
                         spectral mixture models, to evaluate and distinguish canopy 
                         disturbance due to Conventional Logging (CL) and Managed Logging 
                         (ML) in the region of Paragominas, NE Para, Brazil. The results 
                         showed that it is possible to distinguish CL from ML using 
                         vegetation fraction images because of the distinct canopy damage 
                         created by these two types of logging practices. This methodology 
                         can be used as environmental agencies in charge of monitoring 
                         selective logging in the Amazon and by institutes that provide 
                         forest certification.",
  conference-location = "Goi{\^a}nia",
      conference-year = "16-21 abr. 2005",
                 isbn = "85-17-00018-8",
             language = "Portugu{\^e}s",
         organisation = "Instituto Nacional de Pesquisas Espaciais",
                  ibi = "ltid.inpe.br/sbsr/2004/11.19.18.39",
                  url = "http://urlib.net/ibi/ltid.inpe.br/sbsr/2004/11.19.18.39",
           targetfile = "3151.pdf",
                 type = "Monitoramento e Modelagem Ambiental",
        urlaccessdate = "04 jun. 2024"
}