Using Unmanned Aerial Vehicle (UAV) Imagery to Investigate Surface Displacements and Surface Features of the Super-Sauze Earthflow (France)

Monday, 15 December 2014
Samuel Tizzard, University of Lancaster, Lancaster, LA1, United Kingdom, Uwe Niethammer, University of Stuttgart, Stuttgart, Germany and Mike R James, University of Lancaster, Lancaster Environment Centre, Lancaster, United Kingdom
We present the result of using imagery collected with a small rotary wing UAV (unmanned aerial vehicle) to investigate surface displacements and fissures on the Super-Sauze earthflow (France); a slow moving earthflow with the potential to develop into rapid and highly destructive mud flows. UAV imagery acquired in October 2009 was processed using a structure-from-motion and multi-view stereo (SfM-MVS) approach in PhotoScan software. Identification of ~200 ground control points throughout the image set was facilitated by automated image matching in SfM_georef software[1] and the data incorporated into PhotoScan for network optimisation and georeferencing. The completed 2009 model enabled an ~5 cm spatial resolution orthoimage to be generated with an expected accuracy (based on residuals on control) of ~0.3 m. This was supported by comparison to a previously created 2008 model, which gave standard deviations on tie points (located on stationary terrain) of 0.27 m and 0.43 m in Easting and Northing respectively.

The high resolution of the orthoimage allowed an investigation into surface displacements and geomorphology of surface features (compared to the 2008 model). The results have produced a comprehensive surface displacement map of the Super-Sauze earthflow, as well as highlighting interesting variations in fissure geomorphology and density between the 2008 and 2009 models. This study underscored the capability for UAV imagery and SfM-MVS to generate highly detailed orthographic imagery and DEMs with a low cost approach that offers significant potential for landslide hazard assessments.

[1] http://www.lancaster.ac.uk/staff/jamesm/software/sfm_georef.htm