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

Paper No. 289-3
Presentation Time: 9:00 AM-6:30 PM


HAMILTON, Christopher W., Lunar and Planetary Laboratory, University of Arizona, 1629 E. University Blvd., Tucson, AZ 85721, MOERSCH, Jeffrey E., Earth and Planetary Sciences, University of Tennessee, 1412 Circle Drive, Room 306, Knoxville, TN 37996-1410 and SCHEIDT, Stephen P., Lunar and Planetary Laboratory, University of Arizona, 1629 E. University Blvd., Tucson, AZ 85701, hamilton@lpl.arizona.edu

Geomorphological investigations of volcanic landforms on Mars have been revolutionized by high resolution (25 cm/pixel) imagery and stereo-derived digital terrain models (DTMs; with 1-m-postings) generated from Mars Reconnaissance Orbiter (MRO) High Resolution Imaging Science Experiment (HiRISE) data. However, comparable data is rarely available for terrestrial volcanic systems. Fortunately, DTMs and orthomosaics generated using UAV imagery and multi-view stereo-photogrammetry techniques can provide data that is an order of magnitude better than HiRISE imagery, thereby providing a “personal satellite” to support ground-based observations. We present results of two different applications of UAV remote sensing to volcanic landforms. The first approach utilizes DJI Phantom 3 imagery of quarry exposures into the Rauðhólar Volcanic Rootless Cone (VRC) group in Iceland to examine the tephrostratigraphy of the deposits and generate orthorectified images to constrain tephra layer thicknesses in a vertical section and quantify layer thinning geometries. The second approach uses nadir-pointing DJI Phantom 3 imagery to quantify lava channel morphologies within the Laki lava flow in Iceland. Both approaches demonstrate that UAV remote sensing provides invaluable support for ground-based observations and greatly enhances the scientific return of traditional volcanological field campaigns. These data also provide a critical bridge with which to develop terrestrial analog studies of volcanic terrains on Mars using HiRISE imagery and stereo-derived DTMs.