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Methods that employ satellite-based bathymetric modeling provide an alternative to conventional shipborne measurements, offering high spatial resolution combined with extensive coverage. We developed an automated bathymetry mapping approach based on the Sentinel-2 surface reflectance dataset in Google Earth Engine. We created a new method for generating a clean-water mosaic and a tailored automatic bathymetric estimation algorithm. We then evaluated the performance of the models at six globally diverse sites (Heron Island, Australia; West Coast of Hawai\u02bbi Island, Hawai\u02bbi; Saona Island, Dominican Republic; Punta Cana, Dominican Republic; St. Croix, United States Virgin Islands; and The Grenadines) using 113,520 field bathymetry sampling points. Our approach derived accurate bathymetry maps in shallow waters, with Root Mean Square Error (RMSE) values ranging from 1.2 to 1.9 m. This automatic, efficient, and robust method was applied to map shallow water bathymetry at the global scale, especially in areas which have high biodiversity (i.e., coral reefs).<\/jats:p>","DOI":"10.3390\/rs13081469","type":"journal-article","created":{"date-parts":[[2021,4,12]],"date-time":"2021-04-12T05:52:00Z","timestamp":1618206720000},"page":"1469","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":84,"title":["Automated Global Shallow Water Bathymetry Mapping Using Google Earth Engine"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0275-4872","authenticated-orcid":false,"given":"Jiwei","family":"Li","sequence":"first","affiliation":[{"name":"Center for Global Discovery and Conservation Science, Arizona State University, Tempe, AZ 85281, USA"}]},{"given":"David E.","family":"Knapp","sequence":"additional","affiliation":[{"name":"Center for Global Discovery and Conservation Science, Arizona State University, Tempe, AZ 85281, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3960-3522","authenticated-orcid":false,"given":"Mitchell","family":"Lyons","sequence":"additional","affiliation":[{"name":"Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Brisbane QLD 4072, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0182-1356","authenticated-orcid":false,"given":"Chris","family":"Roelfsema","sequence":"additional","affiliation":[{"name":"Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Brisbane QLD 4072, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2605-6104","authenticated-orcid":false,"given":"Stuart","family":"Phinn","sequence":"additional","affiliation":[{"name":"Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Brisbane QLD 4072, Australia"}]},{"given":"Steven R.","family":"Schill","sequence":"additional","affiliation":[{"name":"The Nature Conservancy, Caribbean Division, Coral Gables, FL 33134, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7893-6421","authenticated-orcid":false,"given":"Gregory P.","family":"Asner","sequence":"additional","affiliation":[{"name":"Center for Global Discovery and Conservation Science, Arizona State University, Tempe, AZ 85281, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1016\/j.ecss.2006.06.026","article-title":"Mapping Coral Reef Benthic Substrates Using Hyperspectral Space-Borne Images and Spectral Libraries","volume":"70","author":"Kutser","year":"2006","journal-title":"Estuar. 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