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

Paper No. 229-2
Presentation Time: 9:00 AM-6:30 PM

CAPTURING AND CHARACTERIZING SEDIMENTARY OUTCROPS IN 3-D: A WORKFLOW UTILIZING UAVS AND STRUCTURE-FROM-MOTION PHOTOGRAMMETRY


LEIER, Andrew, CHESLEY, John and WHITE, Scott, Department of Earth and Ocean Sciences, University of South Carolina, Columbia, SC 29208, aleier@geol.sc.edu

Outcrops have long served as the fundamental source of information for sedimentary geology. However, given the complicated nature of outcrop exposures, it is often difficult to capture outcrop-to-outcrop variation in 3-D using either traditional ground-based field techniques or air photos at scales relevant to describing entire depositional systems. Here we present a workflow that utilizes unmanned aerial vehicles (UAV) and structure-from-motion (SfM) photogrammetry to produce sub-meter scale outcrop reconstructions in 3-D space over areas of 100’s of square meters. The first step in the process involves obtaining multiple, overlapping photographs of the outcrop. Identifiable markers with known locations should be placed in the study area and used as ground control points (GCPs). Photographs can be taken from different platforms including hand-held cameras, or cameras mounted on Helikites and UAVs. Ideally, the photographs should be geotagged so that the location and direction of the camera image is recorded. Once the photographs are taken, the resulting images are uploaded into an SfM software package. SfM is a photogrammetric process that uses multiple overlapping images of the same object to reconstruct the location of individual points in a 3-D reference frame. SfM software processes the images, matches points, and produces a 3-D point cloud. The GCPs can be used to georeference the point cloud, if the images were not initially geotagged, or to correct the SfM-produced point cloud. The georeferenced point clouds can be imported into spatial-analysis and visualization software to create a 3-D model of the sedimentary framework, populated with field measurements (e.g. paleocurrent directions), and used for spatial analysis. This workflow is not without drawbacks, most notably that the resolution and accuracy of the final products are generally far less than that with ground-based lidar. However, the low cost and ease of use of this technique may outweigh the negatives for many studies.