@InProceedings{RottaImFeSaRoNo:2009:PlInAl,
               author = "Rotta, Luiz Henrique da Silva and Imai, Nilton Nobuhiro and 
                         Ferreira, Monique Sacardo and Samizava, Tiago Matsuo and Rocha, 
                         Paulo Cesar and Novo, Evlyn M{\'a}rcia Le{\~a}o de Moraes",
          affiliation = "{Faculdade de Ci{\^e}ncias e Tecnologia - Universidade Estadual 
                         Paulista/SP} and {Faculdade de Ci{\^e}ncias e Tecnologia - 
                         Universidade Estadual Paulista/SP} and {Faculdade de Ci{\^e}ncias 
                         e Tecnologia - Universidade Estadual Paulista/SP} and {Faculdade 
                         de Ci{\^e}ncias e Tecnologia - Universidade Estadual Paulista/SP} 
                         and {Faculdade de Ci{\^e}ncias e Tecnologia - Universidade 
                         Estadual Paulista/SP} and {Instituto de Nacional de Pesquisas 
                         Espaciais/SP}",
                title = "Modelo de regress{\~a}o na estimativa de s{\'o}lidos em 
                         suspens{\~a}o por meio de imagens multiespectrais TM-Landsat 5 e 
                         CCD-CBERS 2B - Estudo de caso: Plan{\'{\i}}cie de 
                         inunda{\c{c}}{\~a}o do Alto Rio Paran{\'a}",
            booktitle = "Anais...",
                 year = "2009",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "5413--5420",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 14. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "CBERS image, remote sensing, floating solids, regression model.",
             abstract = "It is very important to know the spatial distribution of water 
                         component concentrations, such as suspended solids, but for that, 
                         a large number of samples spread on the water body are needed, 
                         what makes the data collection time and cost consuming. Thus the 
                         use of remote sensing to predict water component concentration has 
                         been attempted since the launch of the early satellite missions. 
                         Building on the previous efforts, this paper presents the results 
                         of using regression models to estimate the concentration of 
                         suspended solids in two sets of images: TM-Landsat 5 and CCD-CBERS 
                         2B. The images were acquired concurrently to a ground mission 
                         during which, water samples were collected, preserved and sent to 
                         laboratory analyses for determination of suspended solid 
                         concentration. TM-Landsat image was converted into reflectance and 
                         corrected for atmospheric effects and the average ground 
                         reflectance was acquired for a 3 x 3 pixels window for both data 
                         sets. The regression of image variables against suspended solid 
                         concentration allowed to derived two models which were applied to 
                         the images. The paper compares the results showing that CCD-CBERS 
                         2B was able to get suitable information for this estimation.",
  conference-location = "Natal",
      conference-year = "25-30 abr. 2009",
                 isbn = "978-85-17-00044-7",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "dpi.inpe.br/sbsr@80/2008/11.17.23.39",
                  url = "http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2008/11.17.23.39",
           targetfile = "5413-5420.pdf",
                 type = "Monitoramento e Modelagem Ambiental",
        urlaccessdate = "20 maio 2024"
}