@InProceedings{NakaiVett:2017:ApSeRe,
               author = "Nakai, {\'E}rica Silva and Vettorazzi, Carlos Alberto",
                title = "Aplica{\c{c}}{\~a}o do sensoriamento remoto na estimativa de 
                         biomassa de gram{\'{\i}}neas",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "1510--1517",
         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 = "Vegetation is very important in climate regulation and carbon 
                         cycle to remove and store large amounts of carbon dioxide. This 
                         study quantified the aerial plant biomass to obtain the carbon 
                         stock of pastures with the aid of remote sensing at Figueira Farm, 
                         municipality of Londrina, State of Paran{\'a}, Brazil. Five 10m 
                         x10m plots were established with Tanzania grass and after their 
                         free growth, five locations of 1m2 were cut to calculate biomass. 
                         Four vegetation spectral indices were generated: SR, NDVI, EVI and 
                         EVI2, as well as two buffers (50m and 100m), for greater coverage, 
                         from a scene of Landsat-8/OLI from August, 2015. The statistical 
                         analysis was performed with Pearson''s correlation and stepwise 
                         regression. The Tanzania grass produced a mean biomass of 3.67 
                         Mg.ha-1 and mean carbon stock of 1.83 MgC.ha-1. The mean values of 
                         vegetation indices were 0.67 for NDVI, 0.58 for EVI, 0.54 for 
                         EVI2, and 4.80 for SR. The average values for the 50m buffer were 
                         0.64 for NDVI, 0.54 for EVI, 0.52 for EVI2, and 4.35 for SR. The 
                         average values for the 100m buffer were 0.61 for NDVI, 0.51 for 
                         EVI, 0.49 for EVI2, and 3.98 for SR. The Pearsons correlation 
                         analysis indicated a strong negative correlation of the total 
                         biomass of pasture with all vegetation indices and buffers values. 
                         Stepwise regression analysis was significant for EVI (R2=0.91). It 
                         was found that vegetation indices have great potential in estimate 
                         the aboveground biomass, however these indices have not been 
                         sensitive enough to eliminate the soil effects.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59770",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PS4GR5",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PS4GR5",
           targetfile = "59770.pdf",
                 type = "Floresta e outros tipos de vegeta{\c{c}}{\~a}o",
        urlaccessdate = "27 abr. 2024"
}