@InProceedings{SilvaPoppBaptMore:2017:InMéCo,
               author = "Silva, Daniela Pereira da and Poppiel, Raul Roberto and Baptista, 
                         Gustavo Macedo de Mello and Moreira, Emmanuel Carlos G.",
                title = "Influ{\^e}ncia dos m{\'e}todos de corre{\c{c}}{\~a}o 
                         atmosf{\'e}rica FLAASH e QUAC na determina{\c{c}}{\~a}o do 
                         {\'{\i}}ndice NDBSI de solos tropicais mediante dados 
                         hiperespectrais do sensor AVIRIS",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "4134--4141",
         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 = "Hyperspectral remote sensing allows to obtain information about a 
                         target in the natural environment in different regions of the 
                         spectrum, which allows a wide range of data on its situation, and 
                         it is possible to extract the spectral features of reflectance / 
                         absorption that identify the composition of the materials in 
                         pictures. There are several methods to perform the atmospheric 
                         correction in hyperspectral data. The objective of this study was 
                         to verify the influence of the atmospheric correction on exposed 
                         soil of the municipality of S{\~a}o Jo{\~a}o dAlian{\c{c}}a, 
                         Goi{\'a}s, using the NDBSI spectral index in AVIRIS images. To 
                         determine the influence of the atmospheric correction of the 
                         images processed by FLAASH and QUAC, including the uncorrected 
                         radiance image, the NDBSI index applied to the soils of the study 
                         area was used. Then, Pearson correlation coefficients were 
                         determined. The highest correlation between the radiance data and 
                         the atmospheric correction algorithms was for the FLAASH method, 
                         followed by the QUAC. Changes were observed in the inclination of 
                         the curves related to the spatial variation of the targets along 
                         the transect in the image. Intermediate values are related to 
                         areas of partially exposed soil, or partially covered. Although 
                         the curve of the QUAC method is closer to that of radiance, the 
                         FLAASH values are more correlated. The FLAASH method showed a 
                         slightly superior performance to the QUAC, since the data had a 
                         highly linear relationship with the radiance data in determining 
                         the NDBSI index.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59294",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSM2J4",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSM2J4",
           targetfile = "59294.pdf",
                 type = "Radiometria e sensores",
        urlaccessdate = "27 abr. 2024"
}