@InProceedings{BragaArAnDuCaDa:2023:StCaJa,
               author = "Braga, Daniel and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de and 
                         Anderson, Liana O. and Dutra, D{\'e}bora J. and Cabral, Beatriz 
                         Figueiredo and Dalagnol, Ricardo",
          affiliation = "{Universidade Federal de Santa Catarina (UFSC)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Centro Nacional de 
                         Monitoramento e Alertas de Desastres Naturais (CEMADEN)} and 
                         {Centro Nacional de Monitoramento e Alertas de Desastres Naturais 
                         (CEMADEN)} and {Centro Nacional de Monitoramento e Alertas de 
                         Desastres Naturais (CEMADEN)} and {University of California}",
                title = "Quantifying selective logging intensity through airborne LiDAR 
                         data in an Amazon rainforest: study case at Jamari National 
                         Forest",
            booktitle = "Anais...",
                 year = "2023",
               editor = "Vinhas, Lubia (INPE) and Feitosa, Flavia F. (UFABC)",
         organization = "Simp{\'o}sio Brasileiro de Geoinform{\'a}tica, 24. (GEOINFO)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Airborne LiDAR data represents one of the most accurate ways to 
                         estimate forest strucutre and carbon nowadays. This study aimed to 
                         estimate the intensity of selective logging activities in terms of 
                         density and volume of logged trees based on airborne LiDAR data in 
                         comparison to ground measurements on a forest concession area in 
                         the Brazilian Amazon, the Jamari National Forest. The results show 
                         a significant relationship between logging intensity and LiDAR 
                         intensity. This constituted an important step towards monitoring 
                         selective logging in the Amazon and areas under forest 
                         concession.",
  conference-location = "On-line",
      conference-year = "04 a 06 dez. 2023",
                 issn = "2179-4847",
             language = "en",
                  ibi = "8JMKD3MGPDW34P/4ADCA38",
                  url = "http://urlib.net/ibi/8JMKD3MGPDW34P/4ADCA38",
           targetfile = "Braga_Quantifying.pdf",
        urlaccessdate = "2024, May 02"
}