{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T13:08:50Z","timestamp":1780492130230,"version":"3.54.1"},"reference-count":91,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2020,9,16]],"date-time":"2020-09-16T00:00:00Z","timestamp":1600214400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Geoscience Australia","award":["IWQual"],"award-info":[{"award-number":["IWQual"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Baseline determination and operational continental scale monitoring of water quality are required for reporting on marine and inland water progress to Sustainable Development Goals (SDG). This study aims to improve our knowledge of the optical complexity of Australian waters. A workflow was developed to cluster the modelled spectral response of a range of in situ bio-optical observations collected in Australian coastal and continental waters into distinct optical water types (OWTs). Following clustering and merging, most of the modelled spectra and modelled specific inherent optical properties (SIOP) sets were clustered in 11 OWTs, ranging from clear blue coastal waters to very turbid inland lakes. The resulting OWTs were used to classify Sentinel-2 MSI surface reflectance observations extracted over relatively permanent water bodies in three drainage regions in Eastern Australia. The satellite data classification demonstrated clear limnological and seasonal differences in water types within and between the drainage divisions congruent with general limnological, topographical, and climatological factors. Locations of unclassified observations can be used to inform where in situ bio-optical data acquisition may be targeted to capture a more comprehensive characterization of all Australian waters. This can contribute to global initiatives like the SDGs and increases the diversity of natural water in global databases.<\/jats:p>","DOI":"10.3390\/rs12183018","type":"journal-article","created":{"date-parts":[[2020,9,16]],"date-time":"2020-09-16T10:30:12Z","timestamp":1600252212000},"page":"3018","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Classification of Australian Waterbodies across a Wide Range of Optical Water Types"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5025-5373","authenticated-orcid":false,"given":"Elizabeth J.","family":"Botha","sequence":"first","affiliation":[{"name":"CSIRO Oceans &amp; Atmosphere, Canberra, ACT 2601, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1681-9630","authenticated-orcid":false,"given":"Janet M.","family":"Anstee","sequence":"additional","affiliation":[{"name":"CSIRO Oceans &amp; Atmosphere, Canberra, ACT 2601, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9568-9661","authenticated-orcid":false,"given":"Stephen","family":"Sagar","sequence":"additional","affiliation":[{"name":"Geoscience Australia, Symonston, ACT 2601, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9145-9551","authenticated-orcid":false,"given":"Eric","family":"Lehmann","sequence":"additional","affiliation":[{"name":"CSIRO Data61, Canberra, ACT 2601, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5583-4788","authenticated-orcid":false,"given":"Thais A. 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