Investigating the geomorphological potential of freely available and accessible structure‐from‐motion photogrammetry using a smartphone

We test the acquisition of high-resolution topographic and terrain data using hand-held smartphone technology, where the acquired images can be processed using technology freely available to the research community. This is achieved by evaluating the quality of digital terrain models (DTM) of a river bank and an Alpine alluvial fan generated with a fully automated, free-to-use, structure-from-motion package and a smartphone integrated camera (5 megapixels) with terrestrial laser scanning (TLS) data used to provide a benchmark. To evaluate this approach a 16.2-megapixel digital camera and an established, commercial, close-range and semi-automated software are also employed, and the product of the four combinations of the two types of cameras and software are compared. Results for the river bank survey demonstrate that centimetre-precision DTMs can be achieved at close range (10 m or less), using a smartphone camera and a fully automated package. Results improve to sub-centimetre precision with either higher-resolution images or by applying specific post-processing techniques to the smartphone DTMs. Application to an entire Alpine alluvial fan system shows the degradation of precision scales linearly with image scale, but that (i) the expected level of precision remains and (ii) difficulties in separating vegetation and sediment cover within the results are similar to those typically found when using other photo-based techniques and laser scanning systems. Copyright © 2014 John Wiley & Sons, Ltd.

[1]  J. Hyyppä,et al.  Application of boat‐based laser scanning for river survey , 2009 .

[2]  James Brasington,et al.  Close range digital photogrammetric analysis of experimental drainage basin evolution , 2003 .

[3]  M. James,et al.  Measuring 3D coastal change with a digital camera , 2013 .

[4]  G. Heritage,et al.  Towards a protocol for laser scanning in fluvial geomorphology , 2007 .

[5]  Mark A. Fonstad,et al.  Topographic structure from motion: a new development in photogrammetric measurement , 2013 .

[6]  Paul D. Bates,et al.  Spatial modelling of the terrestrial environment , 2004 .

[7]  Stuart N. Lane,et al.  Assessment of Dem Quality for Characterizing Surface Roughness Using Close Range Digital Photogrammetry , 1998 .

[8]  J. Brasington,et al.  Analysing laser‐scanned digital terrain models of gravel bed surfaces: linking morphology to sediment transport processes and hydraulics , 2009 .

[9]  Enoc Sanz-Ablanedo,et al.  Parameterising Internal Camera Geometry with Focusing Distance , 2012 .

[10]  R. Inkpen,et al.  Towards a protocol for laser scanning of rock surfaces , 2010 .

[11]  Á. Gómez‐Gutiérrez,et al.  Using 3D photo-reconstruction methods to estimate gully headcut erosion , 2014 .

[12]  Jim H. Chandler,et al.  Analytical Aspects of Small Format Surveys using Oblique Aerial Photographs , 1989 .

[13]  S. Lane,et al.  Through‐Water Close Range Digital Photogrammetry in Flume and Field Environments , 2002 .

[14]  A. Badoux,et al.  Range imaging: a new method for high‐resolution topographic measurements in small‐ and medium‐scale field sites , 2013 .

[15]  Stuart N. Lane,et al.  The development of an automated correction ­procedure for digital photogrammetry for the study of wide, shallow, gravel‐bed rivers , 2000 .

[16]  Tim Burt,et al.  Global positioning system: An effective way to map a small area or catchment , 1995 .

[17]  J. Brasington,et al.  In situ characterization of grain‐scale fluvial morphology using Terrestrial Laser Scanning , 2009 .

[18]  K. Richards,et al.  Developments in monitoring and modelling small‐scale river bed topography , 1994 .

[19]  S. Robson,et al.  Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application , 2012 .

[20]  M. Westoby,et al.  ‘Structure-from-Motion’ photogrammetry: A low-cost, effective tool for geoscience applications , 2012 .

[21]  K. D. Mankoff,et al.  The Kinect: a low‐cost, high‐resolution, short‐range 3D camera , 2013 .

[22]  Janet Hooke,et al.  Use of terrestrial photogrammetry for monitoring and measuring bank erosion , 1997 .

[23]  Roger Moore,et al.  Analytical photogrammetry: a method for monitoring slope instability , 1989, Quarterly Journal of Engineering Geology.

[24]  Zhengyou Zhang,et al.  Iterative point matching for registration of free-form curves and surfaces , 1994, International Journal of Computer Vision.

[25]  F. Visser,et al.  Quantifying submerged fluvial topography using hyperspatial resolution UAS imagery and structure from motion photogrammetry , 2015 .

[26]  J. Brasington,et al.  Monitoring and modelling morphological change in a braided gravel‐bed river using high resolution GPS‐based survey , 2000 .

[27]  Robert C. Bolles,et al.  Parametric Correspondence and Chamfer Matching: Two New Techniques for Image Matching , 1977, IJCAI.

[28]  Berthold K. P. Horn,et al.  Closed-form solution of absolute orientation using unit quaternions , 1987 .

[29]  J. Chandler Effective application of automated digital photogrammetry for geomorphological research: Earth Surf , 1999 .

[30]  J. Fryer,et al.  Metric capabilities of low‐cost digital cameras for close range surface measurement , 2005 .

[31]  S. Lane,et al.  The Measurement of River Channel Morphology Using Digital Photogrammetry , 2000 .