GSA Annual Meeting in Phoenix, Arizona, USA - 2019

Paper No. 72-14
Presentation Time: 5:00 PM


LASALA, Blase, Mining and Geological Engineering, University of Arizona, 1235 James E. Rogers Way, Tucson, AZ 85719, KEMENY, John M., Mining & Geological Engineering, University of Arizona, Tucson, AZ 85721, LEVINE, Joshua A., Department of Computer Science, University of Arizona, 1040 E. 4th Street, Tucson, AZ 85721, SWETNAM, Tyson, Data Science Insitute, University of Arizona, 1230 N Cherry Ave, Tucson, AZ 85721, KAZHDAN, Misha, Department of Computer Science, John Hopkins University, Whiting School of Engineering, 3400 N Charles St, Baltimore, AZ 21218, STEELE, Nicholas E., National Park Service, Grand Canyon National Park, Grand Canyon, AZ 86023, MCKINNEY, Cami, Department of Interior, National Park Service, Timpanogos Cave National Monument, American Fork, UT 84003 and ARMSTRONG, Andy, National Park Service, Timpanogos Cave National Monument, 2038 Alpine Loop Rd, American Fork, UT 84003

Point clouds are becoming widespread as a method for digitizing representations of surfaces and objects. While this is in-part thanks to advancements in technology and lowering price points of equipment, being able to render large mesh datasets at high resolution has been limited by graphical hardware. This limitation can make these data difficult to utilize unless the resolution is reduced, which results in a loss of small-scale features. When it comes to underground spaces such as caves, the preservation of these small-scale features can be vital for geological characterization, safety, and resource management.

In the winter of 2015, a 22-billion-point cloud of Timpanogos Cave System was collected over the course of two weeks from 478 terrestrial LiDAR scans. While not in color, its resolution is such that sub-centimeter scale cave formations, such as helictites and soda straws, are visible. A CESU (Cooperative Ecosystems Studies Units) agreement between the University of Arizona and Timpanogos Cave National Monument was enacted in 2018 to develop this terabyte scale dataset into an interactive simulation of the cave system. This simulator will be used for research and public outreach and will be featured in the new visitor center.

This talk summarizes the methodology and challenges associated with processing the Timpanogos Cave System dataset. Using high performance computing (HPC) solutions, python scripting, and meshing algorithms specially adapted to work with clouds exceeding several billion points, a model that is detailed enough to preserve the delicate formations the cave is famous for can be rendered using today’s hardware. A beta version of Timpanogos Virtual will be featured, allowing users to explore the cave system via a computer and/or virtual reality headset depending on space accommodations. A live demo for audience members to view after the talk will also be made available.