Because cross-polarized radar returns are highly associated with volume scatter, radar polarimetry returns tend to show strong evidence of wildfire scars and recovery in forest and chaparral. We focus on the polarimetry images from UAVSAR line SanAnd_08525, which covers a roughly 20 km wide swath over the Transverse Range including parts of the Santa Monica, San Gabriel and San Bernardino Mountains. We select images from four acquisition dates from October 2009 to September 2020, very roughly four years apart. These are compared to fire perimeters from the national GeoMAC and NIFC databases for years 2003-2020, which shows the areas affected by the major fires (west to east) Springs2013, Woolsey2018, Topanga2005, LaTuna2017, Station2009, BlueCut2016, Pilot2016, Slide2007, Butler2007 and many smaller fires. UAVSAR polarimetry images are shown to be helpful in identifying types and boundaries of fire, fifty-meter scale details of vegetation loss, and variability of vegetation recovery in post-fire years.

We present a data-driven approach to clustering or grouping Global Navigation Satellite System (GNSS) stations according to their observed velocities, displacements or other selected characteristics. Clustering GNSS stations has the potential for identifying useful scientific information, and is a necessary initial step in other analysis, such as detecting aseismic transient signals (Granat et. al., 2013). Desired features of the data can be selected for clustering, including some subset of displacement or velocity components, uncertainty estimates, station location, and other relevant information. Based on those selections, the clustering procedure autonomously groups the GNSS stations according to a selected clustering method. We have implemented this approach as a Python application, allowing us to draw upon the full range of open source clustering methods available in Python’s scikit-learn package (Pedregosa et. al., 2011). The application returns the stations labeled by group as a table and color coded KML file and is designed to work with the GNSS information available from GeoGateway (Heflin et. al., 2020; Donnellan et al, 2021) but is easily extensible. We focused on California and western Nevada. The results show partitions that follow faults or geologic boundaries, including for recent large earthquakes and post-seismic motion. The San Andreas fault system is most prominent, reflecting Pacific-North American plate boundary motion. Deformation reflected as class boundaries is distributed north and south of the central California creeping section. For most models the southernmost San Andreas fault connects with the Eastern California Shear Zone (ECSZ) rather than continuing through the San Gorgonio Pass.

We use UAVSAR interferograms to characterize fault slip, triggered by the Mw 7.2 El Mayor-Cucapah earthquake on the southernmost San Andreas Fault in the Coachella Valley providing comprehensive maps of landscape change that complement in situ measurements. Creepmeters and geological mapping of fault offsets on Durmid Hill recorded 4 mm and 8 mm of average triggered slip respectively on the fault, in contrast to radar views that reveal significant off-fault dextral deformation averaging 20 mm. Unlike slip in previous triggered slip events on the southernmost San Andreas fault, dextral shear in 2010 is not confined to transpressional hills in the Coachella valley. Edge detection and gradient estimation applied to the 50-m-sampled interferogram data identify the location (to 20 m) and local strike (to < 4°) of secondary surface ruptures. Transverse curve fitting applied to these local detections provides local estimates of the radar-projected dextral slip and a parameter indicating the transverse width of the slip, which we equate with the depth of subsurface shear. These estimates are partially validated by fault-transverse interferogram profiles generated using the web-based UAVSAR tool of GeoGateway, and appear consistent for radar-projected slip greater than about 5 mm. An unexpected finding is that creep and triggered slip on the San Andreas fault terminate in the shallow subsurface below a surface shear zone that resists the simple expression of aseismic fault slip. We introduce the notion of a surface locking depth above which fault slip is manifest as distributed shear, and evaluate its depth as 6-27 m.

The La Conchita Landslide is infamous for its repeated devastation of the coastal community in Southern California. The landslide caused severe damage and loss of life once in 1995 and 2005. In this study we use UAVSAR interferograms of the La Conchita area to identify any residual motion or slope instability associated with the landslides. UAVSAR is NASA’s airborne interferometric synthetic aperture radar (InSAR) platform and is useful for imaging changes in the Earth’s surface. UAVSAR repeat pass interferometry products show disturbances in the image pairs that may correlate with landslides, including where the La Conchita landslides had previously occurred. We used UAVSAR to compare different line-of-sight velocity profiles of the landslide to a stable area to the northeast. UAVSAR pairs show ongoing motion of up to -0.14 cm/day average velocity years after the landslides occurred. More stable areas show less than -0.06 cm/day maximum average velocity. The results imply that damaged rock and soil of a landslide continue to move relative to the surrounding more stable area. UAVSAR image pairs may be useful for identifying unstable areas on slopes that may be associated with landslides or other disturbances.