{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T22:28:04Z","timestamp":1776378484799,"version":"3.51.2"},"reference-count":34,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2016,5,6]],"date-time":"2016-05-06T00:00:00Z","timestamp":1462492800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Unmanned Aerial Vehicles (UAVs) are being increasingly used to monitor topographic changes in coastal areas. Compared to Light Detection And Ranging (LiDAR) data or Terrestrial Laser Scanning data, this solution is low-cost and easy to use, while allowing the production of a Digital Surface Model (DSM) with a similar accuracy. Three campaigns were carried out within a three-month period at a lagoon-inlet system (Bonne-Anse Bay, La Palmyre, France), with a flying wing (eBee) combined with a digital camera. Ground Control Points (GCPs), surveyed by the Global Navigation Satellite System (GNSS) and post-processed by differential correction, allowed georeferencing DSMs. Using a photogrammetry process (Structure From Motion algorithm), DSMs and orthomosaics were produced. The DSM accuracy was assessed against the ellipsoidal height of a GNSS profile and Independent Control Points (ICPs) and the root mean square discrepancies were about 10 and 17 cm, respectively. Compared to traditional topographic surveys, this solution allows the accurate representation of bedforms with a wavelength of the order of 1 m and a height of 0.1 m. Finally, changes identified between both main campaigns revealed erosion\/accretion areas and the progradation of a sandspit. These results open new perspectives to validate detailed morphological predictions or to parameterize bottom friction in coastal numerical models.<\/jats:p>","DOI":"10.3390\/rs8050387","type":"journal-article","created":{"date-parts":[[2016,5,6]],"date-time":"2016-05-06T10:19:23Z","timestamp":1462529963000},"page":"387","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":102,"title":["Monitoring the Topography of a Dynamic Tidal Inlet Using UAV Imagery"],"prefix":"10.3390","volume":"8","author":[{"given":"Nathalie","family":"Long","sequence":"first","affiliation":[{"name":"Littoral, Environnement et Soci\u00e9t\u00e9s, Universit\u00e9 de la Rochelle\u2014CNRS, 2 rue Olympe de Gouges, La Rochelle 17000, France"}]},{"given":"Bastien","family":"Millescamps","sequence":"additional","affiliation":[{"name":"Littoral, Environnement et Soci\u00e9t\u00e9s, Universit\u00e9 de la Rochelle\u2014CNRS, 2 rue Olympe de Gouges, La Rochelle 17000, France"}]},{"given":"Beno\u00eet","family":"Guillot","sequence":"additional","affiliation":[{"name":"Environnements et Pal\u00e9oenvironnements Oc\u00e9aniques et Continentaux, Universit\u00e9 de Bordeaux\u2014CNRS, All\u00e9e Geoffroy Saint-Hilaire, Pessac 33615, France"}]},{"given":"Fr\u00e9d\u00e9ric","family":"Pouget","sequence":"additional","affiliation":[{"name":"Littoral, Environnement et Soci\u00e9t\u00e9s, Universit\u00e9 de la Rochelle\u2014CNRS, 2 rue Olympe de Gouges, La Rochelle 17000, France"}]},{"given":"Xavier","family":"Bertin","sequence":"additional","affiliation":[{"name":"Littoral, Environnement et Soci\u00e9t\u00e9s, Universit\u00e9 de la Rochelle\u2014CNRS, 2 rue Olympe de Gouges, La Rochelle 17000, France"}]}],"member":"1968","published-online":{"date-parts":[[2016,5,6]]},"reference":[{"key":"ref_1","first-page":"549","article-title":"Historical Shoreline Mapping (I): Improving Techniques and Reducing Positioning Errors","volume":"10","author":"Thieler","year":"1994","journal-title":"J. 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