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@Article{SpyrakosOHMSSNBBBBDGGKLMMMORSTZT:2018:OpTyIn,
               author = "Spyrakos, Evangelos and O’Donnell, Ruth and Hunter, Peter D. and 
                         Miller, Claire and Scott, Marian and Simis, Stefan G. H. and Neil, 
                         Claire and Barbosa, Cl{\'a}udio Clemente Faria and Binding, Caren 
                         E. and Bradt, Shane and Bresciani, Mariano and Dall’Olmo, Giorgio 
                         and Giardino, Claudia and Gitelson, Anatoly A. and Kutser, Tiit 
                         and Li, Lin and Matsushita, Bunkei and Martinez-Vicente, Victor 
                         and Matthews, Mark W. and Ogashawara, Igor and Ruiz-Verdu, Antonio 
                         and Schalles, John F. and Tebbs, Emma and Zhang, Yunlin and Tyler, 
                         Andrew N.",
          affiliation = "{University of Stirling} and {University of Glasgow} and 
                         {University of Stirling} and {University of Glasgow} and 
                         {University of Glasgow} and {Plymouth Marine Laboratory} and 
                         {University of Stirling} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Environment and Climate Change Canada} and 
                         {University of New Hampshire} and {Institute for Electromagnetic 
                         Sensing of the Environment} and {Plymouth Marine Laboratory} and 
                         {Institute for Electromagnetic Sensing of the Environment} and 
                         {Israel Institute of Technology} and {University of Tartu} and 
                         {Indiana University-Purdue University at Indianapolis} and 
                         {University of Tsukuba} and {Plymouth Marine Laboratory} and 
                         {CyanoLakes (Pty) Ltd} and {Indiana University-Purdue University 
                         at Indianapolis} and {Universitat de Val{\`e}ncia Catedratico 
                         Jos{\'e} Beltran} and {Creighton University} and {King’s College 
                         London} and {Chinese Academy of Sciences} and {University of 
                         Stirling}",
                title = "Optical types of inland and coastal waters",
              journal = "Limnology and Oceanography",
                 year = "2018",
               volume = "63",
               number = "2",
                pages = "846--870",
                month = "Mar.",
             abstract = "Inland and coastal waterbodies are critical components of the 
                         global biosphere. Timely monitoring is necessary to enhance our 
                         understanding of their functions, the drivers impacting on these 
                         functions and to deliver more effective management. The ability to 
                         observe waterbodies from space has led to Earth observation (EO) 
                         becoming established as an important source of information on 
                         water quality and ecosystem condition. However, progress toward a 
                         globally valid EO approach is still largely hampered by 
                         inconsistences over temporally and spatially variable in-water 
                         optical conditions. In this study, a comprehensive dataset from 
                         more than 250 aquatic systems, representing a wide range of 
                         conditions, was analyzed in order to develop a typology of optical 
                         water types (OWTs) for inland and coastal waters. We introduce a 
                         novel approach for clustering in situ hyperspectral water 
                         reflectance measurements (n = 4045) from multiple sources based on 
                         a functional data analysis. The resulting classification algorithm 
                         identified 13 spectrally distinct clusters of measurements in 
                         inland waters, and a further nine clusters from the marine 
                         environment. The distinction and characterization of OWTs was 
                         supported by the availability of a wide range of coincident data 
                         on biogeochemical and inherent optical properties from inland 
                         waters. Phylogenetic trees based on the shapes of cluster means 
                         were constructed to identify similarities among the derived 
                         clusters with respect to spectral diversity. This typification 
                         provides a valuable framework for a globally applicable EO scheme 
                         and the design of future EO missions.",
                  doi = "10.1002/lno.10674",
                  url = "http://dx.doi.org/10.1002/lno.10674",
                 issn = "0024-3590",
             language = "en",
           targetfile = "spyrakos_optical.pdf",
        urlaccessdate = "24 nov. 2020"
}


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