BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/St_Johns BEGIN:DAYLIGHT DTSTART:20260308T030000 TZOFFSETFROM:-0430 TZOFFSETTO:-0330 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:NDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20261101T010000 TZOFFSETFROM:-0330 TZOFFSETTO:-0430 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:NST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260506T170842Z UID:5AFDCA8C-7FA5-435C-A85D-591863299AC5 DTSTART;TZID=America/St_Johns:20260714T150000 DTEND;TZID=America/St_Johns:20260714T160000 DESCRIPTION:IEEE OES-GRSS-APS Invited Technical Talk 2\n\nSpeaker: Dr. Kege n Yu\n\nTitle：Monitoring Ocean States with Spaceborne GNSS Reflectometry \n\nAbstract: Global Satellite Navigation System Reflectometry (GNSS-R) is an emerging remote sensing technology that is increasingly widely used in Earth observation\, environmental parameter retrieval\, and monitoring of marine and terrestrial disasters. This talk primarily discusses the use o f spaceborne GNSS-R technology for monitoring ocean conditions\, selecting three ocean parameters—sea surface wind speed and direction\, and sea s urface wave height—as retrieval targets. It focuses on studying how to c onstruct ocean parameter retrieval models using machine learning algorithm s under the condition of sufficient observational data samples. Model trai ning primarily utilizes GNSS-R observation data from China's Fengyun-3E an d the U.S. CYGNSS satellites\, along with several ocean parameter product datasets as reference data. Through extensive experimental data processing \, the model's performance was validated\, demonstrating that spaceborne G NSS-R technology can be applied to monitor ocean conditions and serve as a n effective supplement to existing ocean monitoring techniques.\n\nTime: 3 pm-4pm NST\, 14 July\, 2026\n\nLocation: CSF-1203\, Memorial University\n\ nSpeaker(s): Kegen Yu\, \n\nRoom: 1203\, Bldg: CSF\, St. John's\, Newfound land and Labrador\, Canada LOCATION:Room: 1203\, Bldg: CSF\, St. John's\, Newfoundland and Labrador\, Canada ORGANIZER:weimin@mun.ca SEQUENCE:25 SUMMARY:IEEE OES-GRSS-APS Invited Talk 2 (14 July 2026) URL;VALUE=URI:https://events.vtools.ieee.org/m/558823 X-ALT-DESC:Description: <br /><p>IEEE OES-GRSS-APS Invited Technical Talk 2 </p>\n<p class="MsoListParagraph" style="margin-left: 18.0pt\; text-indent : -18.0pt\; mso-char-indent-count: 0\; mso-list: l0 level1 lfo1\;"><span l ang="EN-US"><span lang="EN-US" style="mso-fareast-font-family: DengXian\; mso-fareast-theme-font: minor-latin\; mso-bidi-font-family: DengXian\; mso -bidi-theme-font: minor-latin\;"><span style="mso-list: Ignore\;"><strong> Speaker: </strong>Dr. Kegen Yu</span></span></span></p>\n<p class="MsoList Paragraph" style="margin-left: 18.0pt\; text-indent: -18.0pt\; mso-char-in dent-count: 0\; mso-list: l0 level1 lfo1\;"><span lang="EN-US"><span lang= "EN-US" style="mso-fareast-font-family: DengXian\; mso-fareast-theme-font: minor-latin\; mso-bidi-font-family: DengXian\; mso-bidi-theme-font: minor -latin\;"><span style="mso-list: Ignore\;"><strong>Title：</strong>Monito ring Ocean States with Spaceborne GNSS Reflectometry</span></span></span>< /p>\n<p class="MsoListParagraph" style="margin-left: 18.0pt\; text-indent: -18.0pt\; mso-char-indent-count: 0\; mso-list: l0 level1 lfo1\;"><span la ng="EN-US"><span lang="EN-US" style="mso-fareast-font-family: DengXian\; m so-fareast-theme-font: minor-latin\; mso-bidi-font-family: DengXian\; mso- bidi-theme-font: minor-latin\;"><span style="mso-list: Ignore\;"><strong>A bstract:</strong> </span></span></span><span lang="EN-US"><span lang="EN-U S" style="mso-fareast-font-family: DengXian\; mso-fareast-theme-font: mino r-latin\; mso-bidi-font-family: DengXian\; mso-bidi-theme-font: minor-lati n\;"><span style="mso-list: Ignore\;">Global Satellite Navigation System R eflectometry (GNSS-R) is an emerging remote sensing technology that is inc reasingly widely used in Earth observation\, environmental parameter retri eval\, and monitoring of marine and terrestrial disasters. This talk prima rily discusses the use of spaceborne GNSS-R technology for monitoring ocea n conditions\, selecting three ocean parameters&mdash\;sea surface wind sp eed and direction\, and sea surface wave height&mdash\;as retrieval target s. It focuses on studying how to construct ocean parameter retrieval model s using machine learning algorithms under the condition of sufficient obse rvational data samples. Model training primarily utilizes GNSS-R observati on data from China's Fengyun-3E and the U.S. CYGNSS satellites\, along wit h several ocean parameter product datasets as reference data. Through exte nsive experimental data processing\, the model's performance was validated \, demonstrating that spaceborne GNSS-R technology can be applied to monit or ocean conditions and serve as an effective supplement to existing ocean monitoring techniques.</span></span></span></p>\n<p class="MsoListParagra ph" style="margin-left: 18.0pt\; text-indent: -18.0pt\; mso-char-indent-co unt: 0\; mso-list: l0 level1 lfo1\;"><span lang="EN-US"><span lang="EN-US" style="mso-fareast-font-family: DengXian\; mso-fareast-theme-font: minor- latin\; mso-bidi-font-family: DengXian\; mso-bidi-theme-font: minor-latin\ ;"><span style="mso-list: Ignore\;"><strong>Time: </strong>3pm-4pm NST\, 1 4 July\, 2026</span></span></span></p>\n<p class="MsoListParagraph" style= "margin-left: 18.0pt\; text-indent: -18.0pt\; mso-char-indent-count: 0\; m so-list: l0 level1 lfo1\;"><span lang="EN-US"><span lang="EN-US" style="ms o-fareast-font-family: DengXian\; mso-fareast-theme-font: minor-latin\; ms o-bidi-font-family: DengXian\; mso-bidi-theme-font: minor-latin\;"><span s tyle="mso-list: Ignore\;"><strong>Location:</strong> CSF-1203\, Memorial U niversity</span></span></span></p> END:VEVENT END:VCALENDAR