Rapid mapping of ultrafine fault zone topography with structure from motion
Structure from Motion (SfM) generates high-resolution topography and coregistered texture (color) from an unstructured set of overlapping photographs taken from varying viewpoints, overcoming many of the cost, time, and logistical limitations of Light Detection and Ranging (LiDAR) and other topographic surveying methods. This paper provides the first investigation of SfM as a tool for mapping fault zone topography in areas of sparse or low-lying vegetation. First, we present a simple, affordable SfM workflow, based on an unmanned helium balloon or motorized glider, an inexpensive camera, and semiautomated software. Second, we illustrate the system at two sites on southern California faults covered by existing airborne or terrestrial LiDAR, enabling a comparative assessment of SfM topography resolution and precision. At the first site, an ∼0.1 km2 alluvial fan on the San Andreas fault, a colored point cloud of density mostly >700 points/m2 and a 3 cm digital elevation model (DEM) and orthophoto were produced from 233 photos collected ∼50 m above ground level. When a few global positioning system ground control points are incorporated, closest point vertical distances to the much sparser (∼4 points/m2) airborne LiDAR point cloud are mostly <3 cm. The second site spans an ∼1 km section of the 1992 Landers earthquake scarp. A colored point cloud of density mostly >530 points/m2 and a 2 cm DEM and orthophoto were produced from 450 photos taken from ∼60 m above ground level. Closest point vertical distances to existing terrestrial LiDAR data of comparable density are mostly <6 cm. Each SfM survey took ∼2 h to complete and several hours to generate the scene topography and texture. SfM greatly facilitates the imaging of subtle geomorphic offsets related to past earthquakes as well as rapid response mapping or long-term monitoring of faulted landscapes.
|Rapid mapping of ultrafine fault zone topography with structure from motion
|Kendra Johnson, Edwin Nissen, Srikanth Saripalli, J. Ramón Arrowsmith, Patrick McGarey, Katherine M. Scharer, Patrick Williams, Kimberly Blisniuk
|USGS Publications Warehouse
|Earthquake Science Center