@InProceedings{EduardoSilv:2013:AvInCo,
               author = "Eduardo, Beatriz Fernandes Simplicio and Silva, Antonio Jos{\'e} 
                         Ferreira Machado e",
                title = "Avalia{\c{c}}{\~a}o da influ{\^e}ncia da corre{\c{c}}{\~a}o 
                         atmosf{\'e}rica no c{\'a}lculo do {\'{\i}}ndice de 
                         vegeta{\c{c}}{\~a}o NDVI em imagens Landsat 5 e RapidEye",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "1442--1449",
         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",
             abstract = "Atmospheric correction is an important preprocessing step required 
                         in many remote sensing applications. The objective of this process 
                         is to retrieve the surface reflectance (that characterizes the 
                         surface properties) from remotely sensed imagery by removing the 
                         atmospheric effects. The Normalized Difference Vegetation Index 
                         (NDVI) derived from satellite image data have become one of the 
                         primary information sources for monitoring vegetation conditions 
                         and mapping land cover change. NDVI is a function of red and 
                         near-infrared spectral bands. The aim of this work is compare NDVI 
                         values from both non-corrected and corrected images. NDVI have 
                         been calculated for two different images. The first one is a 
                         Landsat image, and the second one is RapidEye's. Both images 
                         correspond to the same area during the same period. Atmospheric 
                         corrections have been carried out at ATCOR2 (ATmospheric 
                         CORrection) module of ERDAS IMAGINEŽ, which uses MODTRAN-4 
                         (MODerate Resolution Atmospheric TRANsmittance Algorithm) code. 
                         Mean NDVI values were analyzed for vegetation, soil, grass, and 
                         water classes. The mean difference between the two images NDVI 
                         values were 0.12, 0.18, 0.14, and 0.18, for vegetation, exposed 
                         soil, grass, and water classes, respectively. After correction 
                         these values fell to 0.04, 0.03, 0.04 e 0.02, respectively. It is 
                         possible to conclude using these results that corrected images 
                         have better agreement than those that have not. This indicates 
                         that this methodology is consistent with the evaluated sensor 
                         images.",
  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 = "525",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GDT2",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GDT2",
           targetfile = "p0525.pdf",
                 type = "An{\'a}lise e Aplica{\c{c}}{\~a}o de Dados Multiespectrais",
        urlaccessdate = "11 maio 2024"
}