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@Article{OrtizLore:2018:ObMuOc,
               author = "Ortiz, Gustavo P. and Lorenzzetti, Joao Antonio",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Observing multimodal ocean wave systems by a multiscale analysis 
                         of polarimetric SAR imagery",
              journal = "IEEE Geoscience and Remote Sensing Letters",
                 year = "2018",
               volume = "15",
               number = "11",
                pages = "1735--1739",
                month = "nov.",
             keywords = "Synthetic Aperture Radar - SAR, Polarimetria SAR, Multimodal wave 
                         systems, Mean Square Slopes.",
             abstract = "A new methodology is here presented for the assessment of deep 
                         water multimodal ocean wave systems using polarimetric Radarsat-2 
                         imagery. To separate wave systems in multimodal cases and evaluate 
                         their statistics individually, the new approach uses a multiscale 
                         processing scheme together with the mean square slope statistics 
                         theory of ocean waves, which has been originally developed from 
                         optical and radar altimetry sensors. Moreover, it was possible to 
                         classify the wave systems as wind driven or pure swell. The 
                         results show a reasonable agreement with data by a nearby metocean 
                         buoy. More C-band polarimetric SAR imagery is required to fully 
                         validate the methodology with well collocated wave buoys. We 
                         reckon that this new approach, being a fast and independent 
                         satellite algorithm to assess multimodal ocean wave systems, could 
                         contribute to several coastal/oceanic engineering applications and 
                         monitoring systems.",
                  doi = "10.1109/lgrs.2018.2859810",
                  url = "http://dx.doi.org/10.1109/lgrs.2018.2859810",
                 issn = "1545-598X",
                label = "lattes: 3852581196429739 2 OrtizLore:2018:ObMuOc",
             language = "en",
           targetfile = "ortiz_observing.pdf",
        urlaccessdate = "24 nov. 2020"
}


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