Final Report: USGS NEHRP Project G17AP00010
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Final Report: USGS NEHRP Project G17AP00010 Project Title: Automated fault mapping of the North America-Pacific plate boundary using airborne laser swath mapping (ALSM) data George Hilley and Robert Sare Department of Geological Sciences Stanford University Stanford, CA 94305-2115 email:[email protected] voice: (650) 723-3782 fax: (650) 725-0979 Term of Award: January 1, 2017-December 30, 2019 Abstract Fault scarps and fault-related landforms provide important information about fault zone ac- tivity over timescales that are not captured by instrumental measurements or historic records. Semi-automated methods for delineating these landforms using topographic data from light detection and ranging (lidar) and spaceborne imaging systems offer the opportunity to charac- terize fault zones on a global scale. This project explored a computationally efficient method for extracting scarp-like landforms from high-resolution (≤ 2 m), regional-scale (≥ 100-km-long) digital topographic datasets. We identified fault-related landforms using a curvature template based on the diffusion model for scarp degradation and extract scarp heights and morphologic ages at each pixel. The method was applied to the GeoEarthScope Northern California dataset, an airborne lidar acquisition imaging nearly 2500 km2 of the northern San Andreas fault sys- tem, by adapting the algorithm to use cloud computing resources. Template results and fault trace mapping show spatial agreement in active fault zones with clear topographic expression, including detection of fault scarps, shutter ridges, and elongated drainages. Comparison of the method against field-based morphologic dating of scarps along the southern San Andreas re- veals a trade-off between template window size and morphologic age contrasts resolved between strike-slip fault scarps of different relative ages. Detection performance suggests that window size and orientation constraints may play a key role in improving the accuracy of methods for semi-automated fault zone mapping. As data availability grows, these methods could constrain key earthquake simulation parameters such as damage zone width or rupture length and improve fault maps worldwide. This project produced two peer-reviewed publications (from which much of this Final Report is derived; Sare et al., 2019a, b), as well as three conference abstracts: Sare, R. M., & Hilley, G. E. (2017). ESTIMATING FAULT ZONE MATURITY AT THE PLATE BOUNDARY SCALE USING TEMPLATE MATCHING FOR FAULT SCARP DE- TECTION AND MORPHOLOGIC DATING. Presented at the GSA Annual Meeting in Seattle, Washington, USA - 2017, Geological Society of America. https://doi.org/10.1130/abs/2017am- 308245 Sare, R., & Hilley, G. E. (2018). Scarplet: Cloud-based Template Matching for Detecting Earthquake-Related Landforms in Large Topographic Datasets. Scientific Python Conference 2019, Austin, TX. Sare, R., & Hilley, G. E. (2018). Faults in the cloud: Distributed topographic template matching of fault-related landforms in Shuttle Radar Topography Mission data using a cloud- based processing framework. In AGU Fall Meeting Abstracts. A Introduction The lateral extent of past earthquake surface ruptures is a primary input to seismic hazard as- sessment and earthquake rupture forecasts [Field et al., 2015]. Geomorphic indicators of faulting, 1 such as fault scarps and topographic lineaments, provide important evidence of fault zone extent, maturity, and activity beyond the observational timescales of instrumental or historical data (∼100 years). In particular, the height and curvature of fault scarps may encode information about the relative activity of a fault zone over millenia, the timing and extent of past earthquakes, or the amount of aseismic motion accrued along a creeping fault [e.g., Gilbert, 1909; Arrowsmith and Zielke, 2009; Zielke et al., 2015]. Observations by G. K. Gilbert following the 1906 M = 7:9 San Francisco Earthquake seeded the idea that offsets along tectonic structures create steep surface slopes that are then rounded by geomorphic processes [Gilbert, 1907; Lawson and Reid, 1908; Gilbert, 1909]. The fact that the San Andreas fault zone hosted a diversity of sub-parallel, apparently tectonically generated landforms of various stages of rounding led Gilbert [1909] to speculate that they encoded information about the temporal development of the fault zone. This idea was later codified by Hanks et al. [1984] and Andrews and Hanks [1985], which drew on existing geomorphic theory [Culling, 1960] to associate geomorphic degradation of scarps with diffusion-like transport. This led to the deployment of “diffusion dating" of scarps to provide calibrated estimates of the time at which geomorphic features might have formed in the past. These methods have since been applied extensively to tectonic and non-tectonic landforms, including normal fault scarps [Hanks and Schwartz, 1987; Avouac and Peltzer, 1993; Enzel et al., 1996; Hanks, 2000; Mattson and Bruhn, 2001; Kogan and Bendick, 2011], fault scarps resulting from strike-slip motion [Arrowsmith et al., 1998; DeLong et al., 2010; Hilley et al., 2010], wave-cut shorelines, [Hanks et al., 1984; Hanks and Wallace, 1985; Andrews and Bucknam, 1987; Pelletier et al., 2006], alluvial terrace scarps [Pierce and Colman, 1986; Clarke and Burbank, 2010], and gullies on alluvial fan surfaces [Hsu and Pelletier, 2004]. Early approaches to dating of scarp-like landforms used the slope at the midpoint of one or several scarp profiles to determine the relative or morphologic age of individual features [Bucknam and Anderson, 1979; Nash, 1980; Colman and Watson, 1983]. Later, quantitative methods based on solutions to the diffusion equation were developed for a variety of scarp-like initial conditions, such as multiple-event fault scarps or scarps cutting sloped fan surfaces [Andrews and Hanks, 1985; Andrews and Bucknam, 1987; Hanks and Andrews, 1989; Hanks, 2000]. Subsequent work used this approach to invert for initial offset and morphologic age using the full scarp profile [Avouac, 1993; Avouac and Peltzer, 1993; Arrowsmith et al., 1998]. Such profiles were often created manually by field surveys or hand-selected profiles from detailed contour maps. In contrast, recent innovations in laser-based ranging now provide < 0.5-m-resolution postings of the bare-ground surface across broad (> 100s of km2) areas [e.g., Prentice et al., 2009]. This large volume of data, some of which images entire fault systems, requires some semi-automated method of extracting scarp-like landforms for further targeted analysis. To this end, recent studies developed a template-based method for detection of fault-related landforms and morphologic dating of fault scarps in digital topographic data using a curvature template derived from the analytic solution for the elevation of a vertical scarp subject to diffusive degradation [Hilley et al., 2010]. Similar methods incorporating template matching, spectral trans- forms, or wavelet transforms have been developed to extract channel networks [Lashermes et al., 2007; Sangireddy et al., 2016; Isikdogan et al., 2017], map landslides [Booth et al., 2009], and model lateral moraine evolution [Doane et al., 2018] using topographic data. While large-scale results have been achieved in channel network extraction from topographic data [Isikdogan et al., 2017] and measuring the planform geometry of rivers in satellite imagery [Rowland et al., 2016; Schwenk et al., 2017], applications to other landforms have been limited to smaller areas of 1-100 km2. The size of high-resolution topographic datasets and the potentially large search space of morphologic ages, wavelet scales, or window sizes limit many existing spectral or template-based methods, which rely on serial implementations that scale poorly with problem size. 2 In this contribution, we apply a distributed template matching algorithm to a plate-boundary- scale topographic dataset along the northern San Andreas fault system (SAF). We evaluate the hypothesis that template-based feature detectability is related to the orientations and length scales of fault-related landforms, including scarps, elongated valleys, and topographic lineaments. Mor- phologic age estimates are compared to field-based morphologic dating of scarps on the southern San Andreas Fault. We find template morphologic ages to be biased towards lower values and that the discriminating power of age estimates declines with increasing template window size. We mea- sure template performance through comparison to regional fault mapping and detailed geomorphic mapping of individual fault zones. We find that changes in template window size and orientation constraints impact the fidelity of template-derived fault mapping in a range of topographic settings. Relationships between template parameter estimates and slip rate and time of latest fault activ- ity are also explored. Drawing on these findings, we discuss improvements to increase the resolving power of semi-automated mapping methods, including supervised learning methods, and ameliorate the trade-off between window size and morphologic age discrimination. B Data B.1 Topographic datasets This study primarily uses the GeoEarthScope (GES) Northern California lidar dataset [NCAL, 2008] (Figure 1). Collected in 2007, it images the San Andreas Fault and other major fault zones in Northern California [Prentice et al., 2009]. Elevation data is provided as 3680 digital elevation model (DEM) tiles covering 1 km2 at 0.5 m resolution over a total survey area of 2448 km2 with an average point density