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Name: SHP_2019_Ridgecrest_Earthquakes_Rupture_Mapping

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Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P STYLE="text-align:Justify;margin:0 0 0 0;"><SPAN><SPAN>The </SPAN></SPAN><SPAN STYLE="font-style:italic;"><SPAN>M</SPAN></SPAN><SPAN STYLE="font-style:italic;"><SPAN>W</SPAN></SPAN><SPAN><SPAN> 6.4 and </SPAN></SPAN><SPAN STYLE="font-style:italic;"><SPAN>M</SPAN></SPAN><SPAN STYLE="font-style:italic;"><SPAN>W</SPAN></SPAN><SPAN><SPAN> 7.1 2019 Ridgecrest Earthquake Sequence produced complex surface rupture and ground deformation along two distinct fault zones with mapped rupture lengths extending 18 km and 50 km, respectively. Immediate post-earthquake field reconnaissance allowed for efficient flight-line planning for the simultaneous collection of medium- to high-resolution aerial lidar (25 to 80 pulses per square meter (ppsm), respectively) and airborne optical imagery along the rupture (Hudnut et al., 2020). We produced a comprehensive surface rupture map using orthoimages and hillshades derived from these data, documenting visible features with qualitative descriptions and an associated catalog of attributes. We mapped the full extent of surface rupture at a consistent digital screen scale (1:300 – 1:500), the largest scale at which imagery resolution is not degraded. This allowed for centimeter-scale features to be resolved, although mapping using orthoimagery was somewhat limited by image resolution, variable image quality, and time available to map at a large scale. Both fault zones consist of primary fault strands with linear cracks continuous along strike, broad regions of distributed fractures, and well-defined scarps as high as 3 m. The mapping approach was designed to capture the width of these rupture zones and zones of cracking and to characterize the rupture’s expression through varying terrain, such as hillslopes, fan surfaces, and relatively flat playa surfaces. These aerial lidar and orthoimagery datasets allow for comprehensive and uniform documentation of surface rupture and ground deformation features and are complementary with previous mapping datasets. Features mapped in our dataset generally have greater location accuracy and more specificity to fine-scale expression when compared with previous mapping datasets. Whereas our mapping does capture deformation in previously undocumented areas, it can be less comprehensive compared with ground-based and geodetic observations in the near-field. Our dataset of surface rupture features will be potentially useful for longer term, geomorphic-based fault evaluation as we continue to learn from mapping of earthquake ruptures that are the primary evidence of large &gt;</SPAN></SPAN><SPAN STYLE="font-style:italic;"><SPAN>M</SPAN></SPAN><SPAN STYLE="font-style:italic;"><SPAN>W</SPAN></SPAN><SPAN> 6.0 earthquakes. Characterizing zones of deformation for the 2019 Ridgecrest Earthquake Sequence, important for improving fault displacement and seismic hazard assessment and understanding fault mechanics, benefits from a paired approach using both high-resolution lidar and orthoimagery in addition to established ground-based collection methods.</SPAN></P></DIV></DIV></DIV>

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