@InProceedings{VianaReisVelaKört:2019:ShExUs,
               author = "Viana, Rafael Duarte and Reis, Giullian Nicola Lima dos and 
                         Velame, Vict{\'o}ria Maria Gomes and K{\"o}rting, Thales Sehn",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Shoreline extraction using unsupervised classification on 
                         Sentinel-2 imagery",
            booktitle = "Anais...",
                 year = "2019",
               editor = "Gherardi, Douglas Francisco Marcolino and Sanches, Ieda DelArco 
                         and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de",
                pages = "2422--2425",
         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 = "Shoreline extraction, Sentinel-2 MSI, Image Fusion, MNDWI, 
                         K-Means.",
             abstract = "Shoreline extraction is a key process for many coastal zone 
                         applications, such as navigation and coastal environmental 
                         protection. The manual extraction of shorelines manually is 
                         tedious and subject to the operators ability. The main objective 
                         of this research is to evaluate the use of two different image 
                         fusion techniques (IHS and PCA - Principal Component Analisys) 
                         using near-infrared band on multispectral Sentinel-2 imagery to 
                         extract shoreline in the coastal zone of Cassino beach, Southern 
                         Brazil. The resulting images were classified into two classes 
                         (water and non-water) using the K-Means algorithm, and the 
                         accuracy was evaluated through the analysis of mean absolute 
                         difference and RMSE applied on segments of artificial coastal 
                         structures. The results indicate that the shoreline extraction by 
                         PCA method obtained the most accurate results, and the use of 
                         sharpened MNDWI (Modified Normalized Difference Water Index) image 
                         shows a good alternative to improve shoreline extraction.",
  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/3U9HRC2",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3U9HRC2",
           targetfile = "97817.pdf",
                 type = "Processamento de imagens",
        urlaccessdate = "27 abr. 2024"
}