Some thoughts on the use of InSAR data to constrain models of surface deformation: Noise structure and data downsampling

Repeat-pass Interferometric Synthetic Aperture Radar (InSAR) provides spatially dense maps of surface deformation with potentially tens of millions of data points. Here we estimate the actual covariance structure of noise in InSAR data. We compare the results for several independent interferograms with a large ensemble of GPS observations of tropospheric delay and discuss how the common approaches used during processing of InSAR data affects the inferred covariance structure. Motivated by computational concerns associated with numerical modeling of deformation sources, we then combine the data-covariance information with the inherent resolution of an assumed source model to develop an efficient algorithm for spatially variable data resampling (or averaging). We illustrate these technical developments with two earthquake scenarios at different ends of the earthquake magnitude spectrum. For the larger events, our goal is to invert for the coseismic fault slip distribution. For smaller events, we infer the hypocenter location and moment. We compare the results of inversions using several different resampling algorithms, and we assess the importance of using the full noise covariance matrix

Some thoughts on the use of InSAR data to constrain models of surface deformation : noise structure and data downsampling

Author Posting. © American Geophysical Union, 2005. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geochemistry Geophysics Geosystems 6 (2005): Q01007, doi:10.1029/2004GC000841.Repeat-pass Interferometric Synthetic Aperture Radar (InSAR) provides spatially dense maps of surface deformation with potentially tens of millions of data points. Here we estimate the actual covariance structure of noise in InSAR data. We compare the results for several independent interferograms with a large ensemble of GPS observations of tropospheric delay and discuss how the common approaches used during processing of InSAR data affects the inferred covariance structure. Motivated by computational concerns associated with numerical modeling of deformation sources, we then combine the data-covariance information with the inherent resolution of an assumed source model to develop an efficient algorithm for spatially variable data resampling (or averaging). We illustrate these technical developments with two earthquake scenarios at different ends of the earthquake magnitude spectrum. For the larger events, our goal is to invert for the coseismic fault slip distribution. For smaller events, we infer the hypocenter location and moment. We compare the results of inversions using several different resampling algorithms, and we assess the importance of using the full noise covariance matrix.R. Lohman is partially supported by a NASA New Investigator Program grant award to M. Simons

Locations of selected small earthquakes in the Zagros mountains

Author Posting. © American Geophysical Union, 2005. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geochemistry Geophysics Geosystems 6 (2005): Q03001, doi:10.1029/2004GC000849.The Zagros mountains of southern Iran are marked by a zone of high seismicity and accommodate a significant portion of the convergence between Arabia and Eurasia. Due to the lack of dense local seismic or geodetic networks, the inferred kinematics of the collision in Iran is mainly based on catalogs of teleseismically determined earthquake locations. We surveyed all M w > 4.5 earthquakes in the Harvard Centroid Moment Tensor (HCMT) and International Seismological Centre (ISC) catalogs that occurred in the Zagros mountains during the period 1992–2002 and that were spanned by Interferometric Synthetic Aperture Radar (InSAR) images from the ERS 1 and 2 satellites. We invert the observed deformation for the best fitting point source, single fault plane, and distributed fault slip for four earthquakes and one unexplained deformation event. We find that we can precisely locate earthquakes that are too small to be well-located by either the HCMT or ISC catalogs, allowing us to tie specific earthquakes to active geologic structures.ERS 1 and 2 data were acquired through an ESA category-1 proposal. R. Lohman is partially supported by a NASA New Investigator Program grant award to M. Simons

Relationships among seismic velocity, metamorphism, and seismic and aseismic fault slip in the Salton Sea Geothermal Field region

Author Posting. © American Geophysical Union, 2015. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Solid Earth 120 (2015): 2600–2615, doi:10.1002/2014JB011579.The Salton Sea Geothermal Field is one of the most geothermally and seismically active areas in California and presents an opportunity to study the effect of high-temperature metamorphism on the properties of seismogenic faults. The area includes numerous active tectonic faults that have recently been imaged with active source seismic reflection and refraction. We utilize the active source surveys, along with the abundant microseismicity data from a dense borehole seismic network, to image the 3-D variations in seismic velocity in the upper 5 km of the crust. There are strong velocity variations, up to ~30%, that correlate spatially with the distribution of shallow heat flow patterns. The combination of hydrothermal circulation and high-temperature contact metamorphism has significantly altered the shallow sandstone sedimentary layers within the geothermal field to denser, more feldspathic, rock with higher P wave velocity, as is seen in the numerous exploration wells within the field. This alteration appears to have a first-order effect on the frictional stability of shallow faults. In 2005, a large earthquake swarm and deformation event occurred. Analysis of interferometric synthetic aperture radar data and earthquake relocations indicates that the shallow aseismic fault creep that occurred in 2005 was localized on the Kalin fault system that lies just outside the region of high-temperature metamorphism. In contrast, the earthquake swarm, which includes all of the M > 4 earthquakes to have occurred within the Salton Sea Geothermal Field in the last 15 years, ruptured the Main Central Fault (MCF) system that is localized in the heart of the geothermal anomaly. The background microseismicity induced by the geothermal operations is also concentrated in the high-temperature regions in the vicinity of operational wells. However, while this microseismicity occurs over a few kilometer scale region, much of it is clustered in earthquake swarms that last from hours to a few days and are localized near the MCF system.This work was funded by USGS NEHRP proposal G10AP00101 and NSF proposal 0943906.2015-10-2

Location and mechanism of the Little Skull Mountain earthquake as constrained by satellite radar interferometry and seismic waveform modeling

We use interferometric synthetic aperture radar (InSAR) and broadband seismic waveform data to estimate source parameters of the 29 June 1992, M_s 5.4 Little Skull Mountain (LSM) earthquake. This event occurred within a geodetic network designed to measure the strain rate across the region around Yucca Mountain. The LSM earthquake complicates interpretation of the existing GPS and trilateration data, as the earthquake magnitude is sufficiently small that seismic data do not tightly constrain the epicenter but large enough to potentially affect the geodetic observations. We model the InSAR data using a finite dislocation in a layered elastic space. We also invert regional seismic waveforms both alone and jointly with the InSAR data. Because of limitations in the existing data set, InSAR data alone cannot determine the area of the fault plane independent of magnitude of slip nor the location of the fault plane independent of the earthquake mechanism. Our seismic waveform data tightly constrain the mechanism of the earthquake but not the location. Together, the two complementary data types can be used to determine the mechanism and location but cannot distinguish between the two potential conjugate fault planes. Our preferred model has a moment of ∼3.2 × 10^(17) N m (M_w 5.6) and predicts a line length change between the Wahomie and Mile geodetic benchmarks of ∼5 mm

An Incomplete Inventory of Suspected Human-Induced Surface Deformation in North America Detected by Satellite Interferometric Synthetic-Aperture Radar

We used satellite interferometric synthetic-aperture radar (InSAR) data to document ground deformation across North America suspected to be caused by human activities. We showed that anthropogenic deformation can be measured from space across the continent and thus satellite observations should be collected routinely to characterize this deformation. We included results from the literature as well as new analysis of more than 5000 interferograms from the European Remote Sensing (ERS) satellite, Envisat, the Advanced Land Observing Satellite (ALOS), and other satellites, collectively spanning the period 1992–2015. This compilation, while not complete in terms of spatial or temporal coverage nor uniform in quality over the region, contains 263 different areas of likely anthropogenic ground deformation, including 65 that were previously unreported. The sources can be attributed to groundwater extraction (50%), geothermal sites (6%), hydrocarbon production (20%), mining (21%), and other sources (3%) such as lake level changes driven by human activities and tunneling. In a few areas, the source of deformation is ambiguous. We found at least 80 global positioning system (GPS) stations within 20 km of of these areas that could be contaminated by the anthropogenic deformation. At sites where we performed a full time series analysis, we found a mix of steady and time-variable deformation rates. For example, at the East Mesa Geothermal Field in California, we found an area that changed from subsidence to uplift around 2006, even though publicly available records of pumping and injection showed no change during that time. We illustrate selected non-detections from wastewater injection in Oklahoma and eastern Texas, where we found that the detection threshold with available data is >0.5 cm/yr. This places into doubt previous results claiming detection below this threshold in eastern Texas. However, we found likely injection-induced uplift in a different area of eastern Texas at rates in excess of −2 cm/yr. We encourage others to expand the database in space and time in the supplemental material

Proof-of-concept for monitoring ground displacements in Tompkins County, NY using Persistent Scatterer Interferometric Synthetic Aperture Radar from the TerraSAR-X and Sentinel-1 satellites

Underground mining and the pumping of fluids, such as the proposed Cornell University Earth Source Heat Project (ESH), can result in observable displacement of the Earth’s surface that we can use to better understand the effects of those subsurface activities. Such surface movements can be monitored by ground surveying, but the process is labor intensive, limited in spatial extent, and potentially expensive. Here we test whether the established satellite monitoring of surface movements called Interferometric Synthetic Aperture Radar (InSAR) can be used in Tompkins County, NY as part of the ESH project with the goal of achieving a precision of a few mm/year over the areas of interest. We used data from two types of satellites: the TerraSAR-X and TanDEM-X (TSX) satellites of the German Space Agency ( X-band, 3.1 cm radar wavelength) and the Sentinel-1 (S1) satellites of the European Space Agency (C-band, 5.6 cm radar wavelength). We find that both data can be used to detect sub-centimeter/yr deformation rates using Persistent Scatterer Interferometry (PSInSAR). We assess the precision of the inferred rates through comparisons with limited ground survey data and between satellites. PSInSAR selects only reliable pixels, aka persistent scatterers (PS), to be analyzed at the full spatial resolution of the data. Generally, man-made objects, buildings, pipes, roads, etc., are persistent scatterers whereas vegetation cover, fields, bare soil are excluded from further analysis. An analysis with snow-/rain-free TSX data showed that while removing snow covered and rainy images increases the PS population up to two times, the points are concentrated at locations that already have denser PS points. Further, snow-/rain-free images estimate almost the same deformation behavior as the full-stack data set does. In an area of known ground subsidence above an underground mine in Lansing, NY, our analysis revealed that TSX provides more PS points compared to S1. Although both datasets show inter-annual deformation rates that agree with the in situ observations, S1 possessed a higher noise level. With this lower precision level, S1 can be a reliable monitoring tool in the ESH area if the expected deformation is larger than 4-5 mm/yr and if the deforming area extends to at least 300 meters around the drilling site. Otherwise, TSX data should be considered for ground surface monitoring in the area. Based on our comparison with ground control points, we can expect to measure deformation rates of 1-2 mm/yr with TSX PSInSAR.Cornell Atkinson Center for Sustainability Academic Venture Fun

Surface materials and landforms as controls on InSAR permanent and transient responses to precipitation events in a hyperarid desert, Chile

Ground-based monitoring and remote sensing of extreme rain events in the hyperarid Atacama Desert, Chile, reveal a complex relationship between precipitation, soil types and interferometric synthetic aperture radar (InSAR) coherence. These integrated analyses allow examination of temporal and spatial variations of the soil moisture response between locations dominated by sulfate soils and those with immature, silicate-mineral soils. The radar dataset captures at least four separate rain events within the 2015-2017 timeframe, two of which were regionally devastating. The lack of vegetation in this region allows us to discriminate between contributions to the InSAR coherence from permanent changes of the landscape (e.g., erosion or deposition) and transient changes associated with soil moisture variability. The spatial distribution and character of the transient InSAR response depends strongly on soil type, and is remarkably repeatable between rain events. The areas that experienced permanent changes included river channels, steep slopes, playas, and sites of anthropogenic activity, such as roads, mines, or telescope construction. Ground-based observations of soil moisture after each event also exhibit a strong dependence on soil type. The observations presented here demonstrate how InSAR data can constrain variations in soil moisture with high spatial resolution over large regions, complementing the higher-sensitivity but sparser field sites and enabling discrimination of inter-event variability and analysis of longer-term changes in soil mineralogy in arid regions.Chile's CONICYT (Comisión Nacional de Investigación Científica y Tecnológica, Chile) Anillo ACT1203 National Aeronautics & Space Administration (NASA) NNX16AK57