@InProceedings{BeraldoCardImaiRott:2017:DiEsCo,
               author = "Beraldo, Carolina Ambrosio and Cardoso, Mayk Ferreira and Imai, 
                         Nilton Nobuhiro and Rotta, Luiz Henrique da Silva",
                title = "Distribui{\c{c}}{\~a}o espacial das concentra{\c{c}}{\~o}es de 
                         clorofila-a e s{\'o}lidos suspensos totais no reservat{\'o}rio 
                         de Rosana-SP utilizando imagens do sensor OLI/Landsat-8",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "4510--4517",
         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 = "The monitoring of reservoirs through water sampling can be a very 
                         costly and time consuming process due to the large areas of water 
                         bodies, thus remote sensing can arise as a good alternative for 
                         resolving the issue. Some components such as chlorophyll-a and 
                         suspended solids are good indicators of the trophic state of water 
                         bodies and can be identified by remote sensing. This study aimed 
                         the fitting of models to map the spatial distribution of those two 
                         components in Rosana-SP reservoir. The hyperespectral data and 
                         water samples were collected in 20 points for determination of 
                         chlorophyll-a and total suspended solids (TSS) concentrations. The 
                         model calibration was conducted using the bands of OLI sensor 
                         simulated from the field data. The models were fitted with one and 
                         two bands (ratios), using the hyperspectral data and the simulated 
                         bands. The best correlation based on hyperspectral data was 
                         obtained for the ratio between 700 and 680 nm both for the 
                         chlorophyll-a and TSS with 43.42% and 22.25% of root mean square 
                         error (RMSE), respectively. The best model based on simulated 
                         bands of OLI sensor was found for the ratio between the green and 
                         blue bands, with 34.95% of RMSE for chlorophyll-a and 45.97% for 
                         TSS. This model was then applied on the image to generate a map 
                         with the spatial distribution of the two components.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "60177",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSM398",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSM398",
           targetfile = "60177.pdf",
                 type = "{\'A}reas {\'u}midas e {\'a}guas interiores",
        urlaccessdate = "27 abr. 2024"
}