GSA Annual Meeting in Phoenix, Arizona, USA - 2019

Paper No. 265-9
Presentation Time: 9:00 AM-6:30 PM

APPLICATION OF GROUND-BASED PHOTOGRAMMETRY AND VIRTUAL OUTCROPS FOR STRUCTURAL ANALYSIS OF PRECARIOUSLY PERCHED GRAVEL OUTCROPS IN THE AVAWATZ MOUNTAINS, EASTERN CALIFORNIA


GOMEZ, Francisco, Department of Geological Sciences, University of Missouri, 101 Geology Building, Columbia, MO 65211 and MOORE, Kimberly D., University of Missouri, Department of Geological Sciences, 101 Geological Sciences Bldg, Columbia, MO 65211

In areas of active tectonic uplift, key structural information is often preserved in deformation of mid-to-late Quaternary sediments that may be difficult to measure directly. Use of apparent dips involves uncertainty that can limit the reliability of attitude measurements for gentle dips. To address this challenge, we apply high-resolution modeling of virtual outcrops to complement field studies along the front of the Avawatz Mountains in eastern California, where Quaternary gravels lie unconformably atop Proterozoic bedrock. Neotectonic activity is expressed by folding above a blind reverse fault, which is recorded by deformation of the capping gravels. Although gravel bedding is apparent from the distance, measuring accurate bedding attitudes is challenged by the general inaccessibility of outcrops. We construct a virtual outcrop model using ground-based photogrammetry. Accurate structural geometries require precise real-world orientation of the 3D model. Ground control is provided by a network of targets on the stream cut walls. These targets are surveyed using total station measurements and high-precision GPS methods. Photographs are acquired using handheld cameras with a fixed-focal-length lenses. Photographic stations are spaced for “base-to-height” ratios of 0.2 to 0.5 relative to the stream-cut face, and multiple photos are taken from each photographic station. Photogrammetric processing is accomplished using a structure-from-motion (SFM) approach, and post-processing of resulting point clouds include classifying and cleaning vegetation and noisy points. Point clouds are imported into visualization software in which gravel bedding attitudes are measured by planar fit to three or more points in a bed– selecting many points allows a more robust fit and estimate of measure uncertainty. This method also allows rapid measurement of multiple attitudes from different beds at the same outcrop location so that an average dip can be robustly calculated. This overall approach provides a safe and robust means of measuring precise attitudes in gently dipping gravel beds, although a current limitation is the impracticality of data processing and analysis while in the field.