2015 GSA Annual Meeting in Baltimore, Maryland, USA (1-4 November 2015)

Paper No. 157-8
Presentation Time: 3:45 PM


BRUSH, Jade Ashley1, PAVLIS, Terry L.2, HURTADO Jr., José M.1 and KNOTT, Jeffrey R.3, (1)Geological Sciences, The University of Texas at El Paso, 500 W University Ave., Geological Sciences, El Paso, TX 79902, (2)Geological Sciences, University of Texas at El Paso, 500 W. University Ave, El Paso, TX 79968, (3)Department of Geological Sciences, California State Univ, Fullerton, Box 6850, Fullerton, CA 92834, jabrush@miners.utep.edu

Traditional field geology relies on 2D, paper-based workflows, but digital mapping is rapidly replacing these methods. Here we apply digital mapping techniques and terrestrially-based 3D structure-from-motion based photogrammetry and Light Detection and Ranging (LiDAR) to a metamorphic terrain in the Panamint Mountains, CA to show the efficiency and accuracy of digital mapping in a complex geologic situation. The spatial accuracy of photogrammetrically-generated terrain models is evaluated relative to point-cloud derived terrain models obtained by terrestrial laser scanner (TLS) LiDAR system. We constrained the photogrammetric models by utilizing the following ground controls (GC): (1) GPS-determined camera positions only (no GC); (2) GC points at prominent natural objects located with a GPS-enabled laser rangefinder and photos; (3) GC points at artificial targets located with differential GPS unit and photos; and (4) GC points at prominent natural objects identified in the LiDAR terrain model and photos. Method (1) had positioning errors of <200 m. For methods (2) and (4) position accuracy depended on the ability to locate the natural objects accurately, which relied on the object size, color, texture, and shape as well as lighting and camera settings. Where natural objects were accurately located and evenly distributed on overlapping images, the spatial error was within the object size (<2 m). The photogrammetric model accuracy depends primarily on the baseline (line that connects the camera positions) length and the distance to the farthest feature (BTD) ratio. The Clair Camp model with a <200 m position error has a 0.35 BTD, whereas the Noonday model with a 1.0 BTD has <45 m. BTD may be improved with GC points, more frequent overlapping photographs from more positions, GPS accuracy and software processing. Some factors may not be improved based on the site conditions. The geologic accuracy of this high-resolution imagery in “flat-map” view depends on the topography, with the greatest discrepancies found on the steepest slopes. Orientation measurements (i.e., strike and dip) obtained from terrain model multipoint analyses correlate well with manually collected data where shelf-like outcrops or obvious marker beds are present, but are poor on steep cliffs.
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