2014 GSA Annual Meeting in Vancouver, British Columbia (19–22 October 2014)

Paper No. 34-17
Presentation Time: 1:00 PM


SHILPAKAR, Prabin, Department of Geosciences, The University of Texas at Dallas, 800 West Campbell Road, Richardson, TX 75080, OLDOW, John S., Department of Geosciences, University of Texas at Dallas, 800 West Campbell Road, Richardson, TX 75080, WALKER, Douglas, Department of Geology, University of Kansas, Lawrence, KS 66045 and WHIPPLE, Kelin X., School of Earth and Space Exploration, Arizona State University, Tempe, CO 85287

Terrestrial Laser Scanner (TLS) images provide assessment of geomorphic surfaces at a centimeter scale but for quantitative analysis, require understanding of the uncertainty budget and the limit of image resolution. We conducted two experiments to assess contributions of instrumental, georeferencing, and surface modeling methods to the uncertainty budget and to establish the relation between reference network uncertainty and the repeatability and resolution of imaged natural surfaces. A combination of Riegl LMS-Z620 and LPM-800HA instruments were used to image fault scarps and erosional ravines in Panamint Valley and the San Gabriel Mountains of California, respectively. In both experiments, a control network of reflectors was surveyed using a Total Station (TS) and georeferenced with the Global Navigation Satellite System (GNSS) in Real Time Kinematic (RTK) and Static (S) modes in the first and second experiment, respectively. For successive scans, we tested the impact of using a fixed network of control reflectors and scan positions versus using variable scan positions in a fixed reflector network and variable scan and reflector network configurations. The geometry of the reflector network in both experiments was established using a TS to within ± 0.005 m and in addition to ± 0.006 m using S-GNSS occupations during second experiment. TLS repeatability in a local frame is ± 0.028 m, with uncertainty increasing to ± 0.032 m and ± 0.038 m using S-GNSS and RTK-GNSS, respectively. Point-cloud interpolation, where vegetation effects were mitigated, contributed ± 0.01 m to the total error budget. We document that the combined uncertainty for the reference network and surface interpolation represents the repeatability of an imaged natural surface.