FN Archimer Export Format
PT J
TI Monitoring the Topography of a Dynamic Tidal Inlet Using UAV Imagery
BT 
AF LONG, Nathalie
   MILLESCAMPS, Bastien
   GUILLOT, Benoit
   POUGET, Frederic
   BERTIN, Xavier
AS 1:1;2:1;3:2;4:1;5:1;
FF 1:;2:;3:;4:;5:;
C1 Univ Rochelle, CNRS, Littoral Environm & Soc, 2 Rue Olympe Gouges, F-17000 La Rochelle, France.
   Univ Bordeaux, CNRS, Environm & Paleoenvironm Ocean & Continentaux, Allee Geoffroy St Hilaire, F-33615 Pessac, France.
C2 UNIV ROCHELLE, FRANCE
   UNIV BORDEAUX, FRANCE
IN DOAJ
TC 83
UR https://archimer.ifremer.fr/doc/00668/78010/80247.pdf
LA English
DT Article
CR DYNAMO
BO Haliotis
DE ;UAV photogrammetry;coastal monitoring;tidal inlet;sandspit
AB 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. 
PY 2016
PD MAY
SO Remote Sensing
PU Mdpi
VL 8
IS 5
UT 000378406400031
DI 10.3390/rs8050387
ID 78010
ER

EF