@InProceedings{SousaSouMatSilDua:2017:ExAuLi,
               author = "Sousa, Willamys Rangel Nunes de and Souto, Michael Vandesteen 
                         Silva and Matos, Stefanny Soares and Silva Neto, Cl{\'a}udio 
                         {\^A}ngelo da and Duarte, Cynthia Romariz",
                title = "Extra{\c{c}}{\~a}o autom{\'a}tica de linhas de costa aplicada 
                         ao monitoramento de processos de eros{\~a}o costeira",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "6423--6429",
         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 = "Coastal erosion has been considered a global issue which impacts 
                         approximately 70% the shore regions on Earth. It causes 
                         environmental problems, affecting biodiversity, social problems, 
                         including property loss, and infrastructure damage, wasting 
                         millions of economic resources annually. Therefore, coastal 
                         erosion is a key concept that needs to be monitored and 
                         investigated. Remote sensing techniques and geographic information 
                         systems (GIS) have been vastly used in studies that evaluate land 
                         use changes in space and time being testified as extremely 
                         efficient approaches. Thus, remote sensing techniques and 
                         geoprocessing tools are powerful ways to obtain information 
                         continuously and dynamically for coastal regions in different 
                         levels and scales. In this context, the main objective of this 
                         study was to evaluate changes that occurred on the shoreline of 
                         Icapu{\'{\i}}, a municipality in the state of Cear{\'a}, 
                         creating a time-series using Landsat data from 1990 to 2015. 
                         Additionally, Digital Image Processing techniques were applied and 
                         the Modified Normalized Difference Water Index (MNDWI) was 
                         extracted to enhance the difference between pixel values for land 
                         and water. Through the use of those procedures and Python 
                         libraries, it was possible to extract automatically the shoreline 
                         for each year and then execute a dynamic analysis of the region 
                         for the past 25 years. Finally, the results showed that during the 
                         years, Icapu{\'{\i}} in fact suffered significative 
                         modifications in its shoreline.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59894",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMCSC",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMCSC",
           targetfile = "59894.pdf",
                 type = "Processamento de imagens",
        urlaccessdate = "27 abr. 2024"
}