Mendenhall postdoc opportunity - Quantitative 3D analysis of the Northern San Andreas fault

Application of newly acquired airborne LiDAR data for quantitative analysis of landforms associated with active faults in northern California

Airborne LiDAR (Light Detection And Ranging, also known as Airborne Laser Swath Mapping, or ALSM) data have revolutionized the study of landforms associated with active faults in a variety of tectonic settings by providing high-resolution (<1 m under ideal circumstances) Digital Elevation Models (DEMs). The high measurement density of airborne LiDAR data allows the ground surface, even in heavily vegetated regions, to be imaged (known as a "bare earth" DEM), and therefore has been especially useful in locating previously unknown faults in the Pacific Northwest and in refining the positions of active fault strands along part of the northern San Andreas Fault. GeoEarthScope (GeoES), an NSF-funded program administered by UNAVCO, has just completed (April, 2007) the acquisition of airborne LiDAR data along most of the major, active, strike-slip faults in northern California. This acquisition has imaged >1500 square kilometers in swaths 1 to 2 km wide centered on the most significant faults of the region. The USGS has been centrally involved in the planning and implementation of this data acquisition. Along with its partners, the USGS has provided funding as well as expertise and other resources in support of this effort because of the great potential of these data to provide new insights into these hazardous earthquake faults. These data are expected to be the highest-resolution LiDAR data collected along any active fault to date, and once processed will be freely available at no cost to any user (estimated time of availability is autumn, 2007).

The GeoES northern California LiDAR acquisition provides an unprecedented opportunity to advance the understanding of the major active faults and evaluate the earthquake hazards they present. For the first time, these data will provide exceptionally clear images of the ground surface beneath the vegetation canopy along the San Andreas, San Gregorio, Calaveras, Paicines, Rodgers Creek, Maacama, Hayward, and Green Valley Faults. The dense forest canopy above most of these fault zones has hampered the accurate mapping of active fault traces in northern California, and the acquisition of LiDAR data will reveal the fault traces with extraordinary clarity. Even more importantly, the LiDAR data will provide the opportunity to locate paleoseismic sites in forested regions where slip-rate and pre-historic earthquake chronologies can be acquired. Because the LiDAR data are digital, they provide the additional opportunity for innovative quantitative geomorphic analyses of landforms associated with active faults. LiDAR data in southern California have been used to locate and digitally quantify offsets of small stream channels that are displaced by one or more earthquakes, and we anticipate similar opportunities in northern California. These data can be used to define offsets of geomorphic features that can provide information about coseismic slip, and may provide slip-rate estimates when evaluated in concert with other paleoseismic data. In addition, the long-term complexity of fault-zone activity is recorded in landforms associated with and adjacent to the faults, and these will be imaged in great detail as a result of the new LiDAR data acquisition. Thus, exploration of this rich dataset will provide new and unexplored means of evaluating fault-zone complexity and long-term fault development. The topography of fault systems of Northern California contains a rich record of both the horizontal and vertical deformation field, and quantitative analyses of LiDAR data should elucidate the spatial patterns of this deformation. By comparing topographic metrics such as topographic steepness and residual relief along fault zones and considering them within the context of differences in the underlying bedrock lithologies, these metrics may reveal differences in the rates of vertical deformation related to restraining fault geometries and plate-normal convergence. Rates of plate-normal convergence are currently not uniquely resolved by geodetic measurements in northern California, and so analysis of LiDAR data has the potential to shed light on the relative influence of restraining fault geometries vs. transpression on the long-term vertical deformation of the plate margin in Northern California.

Proposed Duty Station: Menlo Park, CA

Areas of Ph.D.: Geology, geophysics, neotectonics, tectonic geomorphology, GIS, remote sensing

Qualifications: Applicants must meet one of the following qualifications: Research Geologist, Research Geophysicist, Research Geochemist

(This type of research is performed by those who have backgrounds for the occupations stated above. However, other titles may be applicable depending on the applicant's background, education, and research proposal. The final classification of the position will be made by the Human Resources specialist.)

Research Advisor(s): Carol Prentice, (650) 329-5690, cprentice@usgs.gov; George Hilley (Stanford University), (650) 723-2782, hilley@pangea.stanford.edu; Gerald Bawden, (916) 278-3131, gbawden@usgs.gov; David Phillips (UNAVCO), (303) 381-7471, dap@unavco.org

Human Resources Office contact: Erica Settlemyer, (916) 278-9383, esettlemyer@usgs.gov