@InProceedings{GassSilvFuchMart:2019:CoPrIm,
               author = "Gass, Sidnei Luis Bohn and Silva, Dieison Morozoli da and Fuchs, 
                         Jessica Paola Silva and Martins, Vinicius Emmel",
          affiliation = "{Universidade Federal do Pampa (UNIPAMPA)} and {Universidade 
                         Federal do Pampa (UNIPAMPA)} and {Universidade Federal do Pampa 
                         (UNIPAMPA)} and {Universidade Federal do Pampa (UNIPAMPA)}",
                title = "Classifica{\c{c}}{\~a}o supervisionada no mapeamento do uso do 
                         solo de Itaqui, RS: um comparativo entre os produtos de imagens 
                         sem e com corre{\c{c}}{\~a}o atmosf{\'e}ricas",
            booktitle = "Anais...",
                 year = "2019",
               editor = "Gherardi, Douglas Francisco Marcolino and Sanches, Ieda DelArco 
                         and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de",
                pages = "2334--2337",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 19. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "Corre{\c{c}}{\~a}o atmosf{\'e}rica, QGIS, Landsat-8, 
                         Semi-Automatic Classification Plugin, Itaqui, Atmospheric 
                         correction, QGIS, Landsat- 8, Semi-Automatic Classification 
                         Plugin, Itaqui.",
             abstract = "A corre{\c{c}}{\~a}o atmosf{\'e}rica {\'e} um importante 
                         procedimento para o sensoriamento remoto. Este trabalho objetivou 
                         estabelecer um comparativo entre a classifica{\c{c}}{\~a}o de 
                         imagens sem e com corre{\c{c}}{\~a}o atmosf{\'e}rica. A 
                         {\'a}rea de estudo foi a por{\c{c}}{\~a}o sudoeste do 
                         munic{\'{\i}}pio de Itaqui. Foram utilizadas imagens do 
                         sat{\'e}lite Landsat-8, o SIG QGIS e o Semi-Automatic 
                         Classification Plugin, no qual foi realizada a 
                         classifica{\c{c}}{\~a}o e corre{\c{c}}{\~a}o atmosf{\'e}rica 
                         das imagens. Foi verificado que a corre{\c{c}}{\~a}o 
                         atmosf{\'e}rica causa mudan{\c{c}}as no aspecto visual das 
                         imagens, por{\'e}m o comportamento espectral dos alvos imageados 
                         muda de forma proporcional. Com rela{\c{c}}{\~a}o a 
                         classifica{\c{c}}{\~a}o, houve varia{\c{c}}{\~a}o de apenas 
                         0,07% da {\'a}rea total, de forma que a varia{\c{c}}{\~a}o de 
                         maior intensidade foi observada para a vegeta{\c{c}}{\~a}o 
                         (varia{\c{c}}{\~a}o de 6,78%). Dessa forma, conclui-se que a 
                         utiliza{\c{c}}{\~a}o de corre{\c{c}}{\~a}o atmosf{\'e}rica 
                         n{\~a}o tem grande impacto para processamentos que utilizem 
                         apenas uma cena do sat{\'e}lite Landsat-8. ABSTRACT: Atmospheric 
                         correction is an important procedure for remote sensing. This work 
                         aimed to establish a comparison between the classification of 
                         images without and with atmospheric correction. The study area was 
                         the southwestern portion of the municipality of Itaqui. Images 
                         from the Landsat-8 satellite, the SIG QGIS and the Semi- Automatic 
                         Classification Plugin were used, in which the classification and 
                         atmospheric correction of the images were performed. It was 
                         verified that the atmospheric correction causes changes in the 
                         visual aspect of the images, however the spectral behavior of the 
                         imaged targets changes proportionally. Regarding classification, 
                         there was variation of only 0.07% of the total area, so that the 
                         highest intensity variation was observed for vegetation (variation 
                         of 6.78%). Thus, it is concluded that the use of atmospheric 
                         correction does not have great impact for processing that uses 
                         only one scene of the Landsat-8 satellite.",
  conference-location = "Santos",
      conference-year = "14-17 abril 2019",
                 isbn = "978-85-17-00097-3",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3U9HQTS",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3U9HQTS",
           targetfile = "97815.pdf",
                 type = "Processamento de imagens",
        urlaccessdate = "11 maio 2024"
}