Geology ReportsSearch

USGS · 70209736

Airborne lidar and electro-optical imagery along surface ruptures of the 2019 Ridgecrest earthquake sequence, Southern California

Abstract

Surface rupture from the 2019 Ridgecrest earthquake sequence, initially associated with the M 6.4 foreshock, occurred on July 4 on a ~17 km long, northeast-southwest oriented, left-lateral zone of faulting. Following the M 7.1 mainshock on July 5 (local time), extensive northwest-southeast-oriented, right-lateral faulting was then also mapped along a ~50 km long zone of faults, including sub-parallel splays in several areas. The largest slip was observed in the epicentral area, and crossing the dry lakebed of China Lake to the southeast. Surface fault rupture mapping by a large team, reported elsewhere, was used to guide the airborne data acquisition reported here. Rapid rupture mapping allowed for accurate and efficient flight line planning for the high-resolution lidar and aerial photography. Flight line planning trade-offs were considered to allocate the medium (25 pulses per square meter, or ppsm) and high resolution (80 ppsm) lidar data collection polygons. The National Center for Airborne Laser Mapping (NCALM) acquired the airborne imagery with a Titan multispectral lidar system and DiMAC aerial digital camera, and USGS acquired GPS ground control data. This effort required extensive coordination with the Navy as much of the airborne data acquisition occurred within their restricted airspace at the China Lake Ranges.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 35.1154153142536° to 36.27085020723902° latitude; -118.125° to -117.2076416015625° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kenneth W. Hudnut, Benjamin A. Brooks, Katherine M. Scharer, Janis L. Hernandez, Timothy E. Dawson, Michael E. Oskin, J. Ramon Arrowsmith, Christine A. Goulet, Kelly Blake, Matthew A. Boggie, Stephan Bork, Craig L. Glennie, J.C. Fernandez-Diaz, Abhinav Singhania, Darren Hauser, Sven Sorhus. 2020-04-22. Airborne lidar and electro-optical imagery along surface ruptures of the 2019 Ridgecrest earthquake sequence, Southern California. https://doi.org/10.1785/0220190338

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Digitizer Suite: The Albuquerque Seismological Laboratory Digitizer Testing Suite

Laboratory testing of digitizers and seismometers helps ensure that prior to deployment the instrumentation can produce high quality data and is operating within specifications. In this work we detail the software package called: the Albuquerque Seismological Laboratory (ASL) Digitizer Test Suite. This Java software package provides several algorithms to verify various performance parameters of digitizers commonly used for recording analog seismic instruments. The goal of these tests is not to be exhaustive, but to identify common failures that could compromise the integrity of seismic data being recorded on the digitizer. For example, Sandia National Laboratories (e.g., Slad and Merchant, 2018) routinely do comprehensive testing of digitizers for various monitoring missions. While these tests reports are valuable for comprehensively characterizing a recording system, it would be resource intensive to conduct such tests on every seismic recorder used in a network. We focus on tests that include ways to estimate the sensitivity, timing, self-noise, and clip-level of the digitizer, as well as the fidelity of the signal being recorded. The software is publicly available and provides a way for the community to verify the integrity of a digitizer using a minimum amount of outside equipment.

Seismological Research Letters

The digital archivist: Automating legacy macroseismic data processing using large language models

Macroseismic data are a key resource to investigate shaking and damage from preinstrumental and early instrumental eras. However, data are often stored as inconsistently formatted reports describing observed shaking and damage, making manually parsing and interpreting accounts labor‐intensive. We introduce a novel workflow using Google’s Gemini 2.5 Pro large language model (LLM) to automate the extraction and structuring of macroseismic observations from summary reports. We apply this workflow to the 22 March 1957 M 5.3 Daly City, California, earthquake as a case study. We used Gemini to extract addresses, originally assigned modified Mercalli intensity values, and descriptions from each report. To address coordinate precision limits, addresses were geocoded via Google’s Geocoding application programming interface. This workflow yielded over 2300 geocoded intensity reports for the Daly City earthquake. We use the geocoded accounts, with the original report intensity assignments, to develop a shaking intensity map that in some respects rivals modern Did You Feel It? Maps. We also extract and present data for the 9 February 1971 M L 6.7 Sylmar, California, earthquake. Our results demonstrate the potential of LLMs for reliably extracting and analyzing large, unstructured macroseismic datasets. LLMs offer a scalable solution for rapidly digitizing macroseismic archives, enabling their broader use to constrain ground‐motion models in modern seismic hazard analysis and to improve our understanding of site effects in urban areas. The concepts explored here may also be applied to the handling of other legacy seismological and earth science data.

Seismological Research Letters