Potential of Smartphone SfM Photogrammetry to Measure Coastal Morphodynamics

Marion Jaud (1) , Matthieu Kervot (2) , Christophe Delacourt (2) , Stéphane Bertin (2)

1 IUEM - Institut Universitaire Européen de la Mer
2 LGO - Laboratoire Géosciences Océan

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®, Lumia 930® and iPhone 8®) 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.

Mots clés: Smartphone; SfM photogrammetry; coastal monitoring; DEM; citizen observatory

Domaines: Sciences de la Terre; Géomorphologie

Marion Jaud, Matthieu Kervot, Christophe Delacourt, Stéphane Bertin. Potential of Smartphone SfM Photogrammetry to Measure Coastal Morphodynamics. Remote Sensing, 2019, ⟨10.3390/rs11192242⟩. ⟨hal-02297923⟩