FN Archimer Export Format
PT J
TI Potential of Smartphone SfM Photogrammetry to Measure Coastal Morphodynamics
BT 
AF JAUD, Marion
   KERVOT, Matthieu
   DELACOURT, Christophe
   BERTIN, Stephane
AS 1:1;2:2;3:2;4:2;
FF 1:;2:;3:;4:;
C1 Univ Brest, CNRS, European Inst Marine Studies IUEM, UMS 3113, F-29280 Plouzane, France.
   Univ Brest, Lab Geosci Oceans, UMR 6538, F-29280 Plouzane, France.
C2 UBO, FRANCE
   UBO, FRANCE
UM LGO
TC 23
UR https://archimer.ifremer.fr/doc/00637/74907/76115.pdf
LA English
DT Article
DE ;Smartphone;SfM photogrammetry;coastal monitoring;DEM;citizen observatory
AB With recent advances in photogrammetric processing methods and sensor technologies, smartphones represent a new opportunity of mainstream, low-cost sensor, with a great potential for Structure-from-Motion (SfM) photogrammetry, and in particular for participatory science programs or citizen observatories. Keeping in mind the application in citizen observatories, three smartphone models (Galaxy S7 (R), Lumia 930 (R) and iPhone 8 (R)) and a bridge camera were compared (separately and in combination) for coastal applications: A coastal cliff and a sandy beach. Various acquisition protocols, at different distances from a cliff face and using "linear" or "fan-shaped" capture mode, were also assessed in their efficiency. A simultaneous Terrestrial Laser Scanner (TLS) survey provided a reference dataset to assess the quality of the SfM reconstructions. Satisfactory reconstructions (mean error < 5 cm) of the cliff face were obtained using all smartphone models tested. To measure the cliff face, fan-shaped capturing mode allowed a quicker image acquisition on site and better results (mean error of 1.3 cm with a standard deviation of 0.1 cm at 20 m from the cliff face) than linear capturing mode (mean error of 2.5 cm with a standard deviation of 21.8 cm), provided that the distance to the cliff face is sufficient to ensure a good image overlap. To obtain satisfactory results over beaches, we show that it is preferable to have high-angle shots of the study area, which may limit the applicability of the method for certain sites. 
PY 2019
PD OCT
SO Remote Sensing
PU Mdpi
VL 11
IS 19
UT 000496827100056
DI 10.3390/rs11192242
ID 74907
ER

EF