@InProceedings{MegaKupl:2019:ApFlLi,
               author = "Mega, Caciane Peinhopf and Kuplich, Tatiana Mora",
          affiliation = "{Universidade Federal do Rio Grande do Sul (UFRGS)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Aplica{\c{c}}{\~o}es florestais do LiDAR",
            booktitle = "Anais...",
                 year = "2019",
               editor = "Gherardi, Douglas Francisco Marcolino and Sanches, Ieda DelArco 
                         and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de",
                pages = "3016--3019",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 19. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "Sensoriamento Remoto, ALS, floresta nativa, floresta plantada, 
                         publica{\c{c}}{\~o}es. remote sensing, LiDAR, ALS, forestry.",
             abstract = "O presente trabalho tem como objetivo fornecer uma vis{\~a}o 
                         geral dos trabalhos publicados no Brasil nos {\'u}ltimos anos 
                         (2010 a 2018) com aplica{\c{c}}{\~o}es florestais e 
                         extra{\c{c}}{\~a}o de par{\^a}metros da floresta por meio de 
                         dados LiDAR (Light Detection and Ranging). Os artigos selecionados 
                         que envolvem pesquisas relacionadas a florestas plantadas 
                         (Eucalyptus e Pinnus) s{\~a}o 11, com algumas das var{\'a}veis 
                         mensuradas envolvendo n{\'u}mero de {\'a}rvores, altura, volume, 
                         carbono e biomassa. Para as florestas nativas as 
                         avalia{\c{c}}{\~o}es s{\~a}o mais complexas, dada a 
                         heterogeneidade das esp{\'e}cies, principalmente em ambientes 
                         tropicais. Foram encontradas 8 publica{\c{c}}{\~o}es para 
                         ambiente nativo, que envolvem individualiza{\c{c}}{\~a}o de 
                         copas, estratifica{\c{c}}{\~a}o da floresta e volume. Ainda 
                         n{\~a}o existem metodologias consolidadas no Brasil que permita a 
                         substitui{\c{c}}{\~a}o de invent{\'a}rio florestal tradicional 
                         por aquisi{\c{c}}{\~a}o de informa{\c{c}}{\~o}es a partir de 
                         dados LiDAR, mas com a fus{\~a}o das duas informa{\c{c}}{\~o}es 
                         as estimativas podem ser mais precisas e eficientes. ABSTRACT: 
                         This paper aims to provide an overview of the works published in 
                         Brazil in recent years (2010 to 2018) with forest applications of 
                         LiDAR (Light Detection and Ranging) data. Eleven articles 
                         involving research related to planted forests (Eucalyptus and 
                         Pinnus) were selected, and the measured variables were: number of 
                         trees, height, volume, and biomass. For native forests, with more 
                         complex structures due to the species diversity, 8 publications 
                         were found and the measured variables were: individualization of 
                         trees, forest stratification, and volume. There are still no 
                         consolidated methodologies in Brazil that allows the replacement 
                         of traditional forest inventory information with LiDAR data, but 
                         with the combination of the two types of information (field and 
                         LiDAR) the estimates are certainly more accurate and efficient.",
  conference-location = "Santos",
      conference-year = "14-17 abril 2019",
                 isbn = "978-85-17-00097-3",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3U3RS4B",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3U3RS4B",
           targetfile = "97597.pdf",
                 type = "LIDAR: sensores e aplica{\c{c}}{\~o}es",
        urlaccessdate = "27 abr. 2024"
}