@InProceedings{CelesShimCampHigu:2013:AMBr,
               author = "Celes, Carlos Henrique Souza and Shimabukuro, Yosio Edemir and 
                         Campos, Moacir Alberto Assis and Higuchi, Niro",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Estimativa de biomassa em uma floresta tropical no 
                         munic{\'{\i}}pio de Mau{\'e}s - AM, Brasil",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "2827--2834",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 16. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "forest inventories, remote sensing, image processing, carbon, 
                         invent{\'a}rio florestal sensoriamento remoto, processamento de 
                         imagens, carbono.",
             abstract = "The remote sensing, geographic information system (GIS) and global 
                         positioning system (GPS) are important tools for the several steps 
                         of forest inventories, including estimates of biomass. The 
                         objective of this work was to consolidate a methodology for 
                         mapping or spatialization the biophysical variables using field 
                         data and remote sensing techniques. The field data were available 
                         from continuous forest inventory system (IFC) in Mau{\'e}s (AM) 
                         region conducted by the Forest Management Laboratory of the 
                         National Institute of Amazonian Research (INPA-LMF). The remote 
                         sensing data were obtained from TM sensor of Landsat-5 satellite, 
                         and digital surface elevation model (MDS) of the SRTM mission. The 
                         equations were adjusted and performed the classifications for the 
                         estimates and spatialization of the biophysical variables. The 
                         study area presented an average of 485.3 ± 1.9% individuals per 
                         hectare and 578.3 ± 3.4% tons per hectare of fresh biomass. The 
                         adjusted equations didnt fit to data. The highest adjusted R2 was 
                         0.24 for the volume and the density presented the best residual 
                         distribution. The spatialization of biomass was performed using 
                         the isocluster classification of the topography, including 
                         elevation, slope and curvature. The estimation for the all study 
                         area of biomass and carbon was 662,6 ±13% 189,2 million tons, 
                         respectively.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "13-18 abr. 2013",
                 isbn = "{978-85-17-00066-9 (Internet)} and {978-85-17-00065-2 (DVD)}",
                label = "107",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7G8U3",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7G8U3",
           targetfile = "p0107.pdf",
                 type = "Floresta e Vegeta{\c{c}}{\~a}o",
        urlaccessdate = "11 maio 2024"
}