Detection of surface change in complex topography using terrestrial laser scanning: application to the Illgraben debris‐flow channel

Detection of surface change is a fundamental task in geomorphology. Terrestrial laser scanners are increasingly used for monitoring surface change resulting from a variety of geomorphic processes, as they allow the rapid generation of high-resolution digital elevation models. Irrespective of instrument specifics, survey design or data processing, such data are subject to a finite level of ambiguity in position measurement, a consideration of which must be taken into account when deriving change. The propagation of errors is crucial in change detection because even very small uncertainties in elevation can produce large uncertainties in volume when extrapolated over an area of interest. In this study we propose a methodology to detect surface change and to quantify the resultant volumetric errors in areas of complex topography such as channels, where data from multiple scan stations must be combined. We find that a commonly proposed source of error – laser point elongation at low incidence angles – has a negligible effect on the quality of the final registered point cloud. Instead, ambiguities in elevation inherent to registered datasets have a strong effect on our ability to detect and measure surface change. Similarly, we find that changes in surface roughness between surveys also reduce our ability to detect change. Explicit consideration of these ambiguities, when propagated through to volume calculations, allows us to detect volume change of 87 ±5m3, over an area of ∼ ​4900m2, due to passage of a debris flow down a 300m reach of the Illgraben channel in Switzerland.

[1]  Wolfgang von Hansen REGISTRATION OF AGIA SANMARINA LIDAR DATA USING SURFACE ELEMENTS , 2007 .

[2]  Peter Molnar,et al.  Limits of sediment transfer in an alpine debris-flow catchment, Illgraben, Switzerland , 2009 .

[3]  D. Petley,et al.  Combined Digital Photogrammetry and Time‐of‐Flight Laser Scanning for Monitoring Cliff Evolution , 2005 .

[4]  Nicole M. Gasparini,et al.  An object-oriented framework for distributed hydrologic and geomorphic modeling using triangulated irregular networks , 2001 .

[5]  J. Brasington,et al.  Accounting for uncertainty in DEMs from repeat topographic surveys: improved sediment budgets , 2009 .

[6]  S. Buckley,et al.  Terrestrial laser scanning in geology: data acquisition, processing and accuracy considerations , 2008, Journal of the Geological Society.

[7]  Derek D. Lichti,et al.  Ground-based Laser Scanners: Operation, systems and Applications , 2002 .

[8]  S. Lane,et al.  Estimation of erosion and deposition volumes in a large, gravel‐bed, braided river using synoptic remote sensing , 2003 .

[9]  D. Milan,et al.  Influence of survey strategy and interpolation model on DEM quality , 2009 .

[10]  D. Milan,et al.  Reach‐scale sediment transfers: an evaluation of two morphological budgeting approaches , 2003 .

[11]  P. Bartelt,et al.  Field observations of basal forces and fluid pore pressure in a debris flow , 2006 .

[12]  D. Milan,et al.  Application of a 3D laser scanner in the assessment of erosion and deposition volumes and channel change in a proglacial river , 2007 .

[13]  D. Petley,et al.  Patterns of precursory rockfall prior to slope failure , 2007 .

[14]  Jim H. Chandler,et al.  The assessment of sediment transport rates by automated digital photogrammetry: Photogram , 1998 .

[15]  Nicholas C. Coops,et al.  Evaluating error associated with lidar-derived DEM interpolation , 2009, Comput. Geosci..

[16]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Gérard G. Medioni,et al.  Object modelling by registration of multiple range images , 1992, Image Vis. Comput..

[18]  Patrick J. Flynn,et al.  Pair-Wise Range Image Registration: A Study in Outlier Classification , 2002, Comput. Vis. Image Underst..

[19]  J. Brasington,et al.  Methodological sensitivity of morphometric estimates of coarse fluvial sediment transport , 2003 .

[20]  Michel Jaboyedoff,et al.  Detection of millimetric deformation using a terrestrial laser scanner: experiment and application to a rockfall event , 2009 .

[21]  M. O'Neal,et al.  The rates and spatial patterns of annual riverbank erosion revealed through terrestrial laser‐scanner surveys of the South River, Virginia , 2011 .

[22]  Jon P. Mills,et al.  Laser Scanning Surveying of Linear Features: Considerations and Applications , 2009 .

[23]  Juha Hyyppä,et al.  Brightness Measurements and Calibration With Airborne and Terrestrial Laser Scanners , 2008, IEEE Transactions on Geoscience and Remote Sensing.

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