Abstract
Abstract Observations of fault geometry and cumulative slip distribution serve as critical constraints on fault behavior over temporal scales ranging from a single earthquake to a fault’s complete history. The increasing availability of high-resolution topography (at least one observation per square meter) from air- and spaceborne platforms facilitates measuring geometric properties along faults over a range of spatial scales. However, manually mapping faults and measuring slip or scarp height is time-intensive, limiting the use of rich topography datasets. To substantially decrease the time required to analyze fault systems, we developed a novel approach for systematically mapping dip-slip faults and measuring scarp height. Our MATLAB algorithm detects fault scarps from topography by identifying regions of steep relief given length and slope parameters calibrated from a manually drawn fault map. We applied our algorithm to well-preserved normal faults in the Volcanic Tablelands of eastern California using four datasets: (1) structure-from-motion topography from a small uncrewed aerial system (sUAS; 20 cm resolution), (2) airborne laser scanning (25 cm), (3) Pléiades stereosatellite imagery (50 cm), and SRTM (30 m) topography. The algorithm and manually mapped fault trace architectures are consistent for primary faults, although can differ for secondary faults. On average, the scarp height profiles are asymmetric, suggesting fault lateral propagation and along-strike variations in the fault’s mechanical properties. We applied our algorithm to Arizona and Utah with a specific focus on the normal Hurricane fault where the algorithm mapped faults and other prominent topographic features well. This analysis demonstrates that the algorithm can be applied in a variety of geomorphic and tectonic settings.
Highlights
Scientists use a tectonic fault’s three-dimensional geometry and the surrounding damage zone to probe research questions about fault mechanics and hazard [1,2,3,4,5,6]
Our algorithm significantly reduces the time required to build large fault geometry and scarp height datasets
We developed a new algorithm that maps dip-slip faults and measures scarp height from well-preserved faults using the growing archive of global and high-resolution topography datasets
Summary
Scientists use a tectonic fault’s three-dimensional geometry and the surrounding damage zone to probe research questions about fault mechanics and hazard [1,2,3,4,5,6]. Howe et al.’s [27] approach constrains slip by mapping paleolake shorelines from topographic inflection points Despite these advancements, many algorithms either map faults or measure slip and are often applied to a single geomorphic setting, which limited their broad usage. We present a new computational algorithm that maps normal faults and estimates scarp height from highresolution and global topography datasets. We derived a height versus length scaling relationship for 152 faults which is consistent with the relationship derived from ~850 faults from the literature in different settings and over a variety of spatial scales. This demonstrates the robustness of our measurements and of our algorithm. We anticipate that our algorithm could successfully map normal fault systems in a variety of tectonic contexts
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