@InProceedings{OliveiraOliv:2017:CoMoLi,
               author = "Oliveira, Marcus Vin{\'{\i}}cio Neves de and Oliveira, Luis 
                         Claudio de",
                title = "Compara{\c{c}}{\~a}o de modelos lidar para a estimativa de 
                         biomassa seca acima do solo de florestas com diferentes 
                         hist{\'o}ricos de perturba{\c{c}}{\~a}o natural ou 
                         antr{\'o}pica no Estado do Acre",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "5187--5194",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Lidar data has been largely used to produce estimative on biomass 
                         and timber stocks in tropical forests. A major problem is the 
                         lidar flights costs, and the exhaustive and expensive ground plot 
                         data acquisition necessary to calibrate lidar data metrics. The 
                         use of ground information from previously established plots and 
                         the generalization of existent models to structurally similar 
                         forests should be a way to minimize these costs. In this work we 
                         study six forest in Acre state with similar structure and 
                         different disturbance history covered by lidar flights and forest 
                         inventories. We investigate whether the use of plots with 
                         different sizes violate the null hypothesis of the variance 
                         equality of the lidar metrics and tested the use of a lidar 
                         general model to estimate the biomass on the studied sites. We 
                         generated regression models to estimate above ground biomass for 
                         each area and compared them to a general model elaborated with the 
                         ground and lidar information of all areas together. The results 
                         showed that the null hypotheses of the variance was not violated 
                         to the variable selected to compose the models and no significant 
                         differences were found among the local and general models 
                         suggesting that in the absence of forest inventories, when forest 
                         were structurally similar, a general lidar model can be used to 
                         assess biomass stocks.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59321",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSM4E4",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSM4E4",
           targetfile = "59321.pdf",
                 type = "LIDAR: sensores e aplica{\c{c}}{\~o}es",
        urlaccessdate = "27 abr. 2024"
}