[ { "id": "authors:7586w-33803", "collection": "authors", "collection_id": "7586w-33803", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20190926-153914557", "type": "article", "title": "Ionospheric Correction of InSAR Time Series Analysis of C-band Sentinel-1 TOPS Data", "author": [ { "family_name": "Liang", "given_name": "Cunren", "orcid": "0000-0003-3938-426X", "clpid": "Liang-Cunren" }, { "family_name": "Agram", "given_name": "Piyush", "clpid": "Agram-P-S" }, { "family_name": "Simons", "given_name": "Mark", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" }, { "family_name": "Fielding", "given_name": "Eric J.", "orcid": "0000-0002-6648-8067", "clpid": "Fielding-E-J" } ], "abstract": "The Copernicus Sentinel-1A/B satellites operating at C-band in terrain observation by progressive scans (TOPS) mode bring unprecedented opportunities for measuring large-scale tectonic motions using interferometric synthetic aperture radar (InSAR). Although the ionospheric effects are only about one-sixteenth of those at L-band, the measurement accuracy might still be degraded by long-wavelength signals due to the ionosphere. We implement the range split-spectrum method for correcting ionospheric effects in InSAR with C-band Sentinel-1 TOPS data. We perform InSAR time series analysis and evaluate these ionospheric effects using data acquired on both ascending (dusk-side of the Sentinel-1 dawn-dusk orbit) and descending (dawn-side) tracks over representative midlatitude and low-latitude (geomagnetic latitude) areas. We find that the ionospheric effects are very strong for data acquired at low latitudes on ascending tracks. For other cases, ionospheric effects are not strong or even negligible. The application of the range split-spectrum method, despite some implementation challenges, largely removes ionospheric effects, and thus improves the InSAR time series analysis results.", "doi": "10.1109/tgrs.2019.2908494", "issn": "0196-2892", "publisher": "IEEE", "publication": "IEEE Transactions on Geoscience and Remote Sensing", "publication_date": "2019-09", "series_number": "9", "volume": "57", "issue": "9", "pages": "6755-6773" }, { "id": "authors:ewmwp-gje50", "collection": "authors", "collection_id": "ewmwp-gje50", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20181108-155745164", "type": "book_section", "title": "The InSAR Scientific Computing Environment 3.0: A Flexible Framework for NISAR Operational and User-Led Science Processing", "book_title": "2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2018)", "author": [ { "family_name": "Rosen", "given_name": "Paul A.", "clpid": "Rosen-P-A" }, { "family_name": "Gurrola", "given_name": "Eric M.", "clpid": "Gurrola-E-M" }, { "family_name": "Agram", "given_name": "Piyush", "clpid": "Agram-P-S" }, { "family_name": "Cohen", "given_name": "Joshua", "clpid": "Cohen-J" }, { "family_name": "Lavalle", "given_name": "Marco", "clpid": "Lavalle-M" }, { "family_name": "Riel", "given_name": "Bryan V.", "orcid": "0000-0003-1940-3910", "clpid": "Riel-B" }, { "family_name": "Fattahi", "given_name": "Heresh", "orcid": "0000-0001-6926-4387", "clpid": "Fattahi-H" }, { "family_name": "Aivazis", "given_name": "Michael A. G.", "clpid": "Aivazis-M-A-G" }, { "family_name": "Simons", "given_name": "Mark", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" }, { "family_name": "Buckley", "given_name": "Sean M.", "clpid": "Buckley-S-M" } ], "abstract": "The InSAR Scientific Computing Environment (ISCE) was first developed under the NASA Advanced Information Systems Technology as a flexible, extensible object-oriented framework for Interferometric Synthetic Aperture Radar (InSAR) processing. The ISCE framework uses Python 3 at the workflow level, controlling modules of compiled code for functional processing, and managing inputs, outputs, and other flow control services. The currently released version, called ISCE 2.1, is distributed to the research community through the Western North America InSAR Consortium under a research license. The ISCE team is working on the next generation of the code in order to prepare for the NASA-ISRO SAR (NISAR) mission operational processing. Innovations in this code include augmentation or conversion of the custom Python framework elements in ISCE with the Pyre framework, new workflows for interferometric and polarimetric stack processing, a more intuitive and graphically based user interface, and flow control for hybrid computing environments including CPU/GPU clusters, logging and error tracking facilities, and new more efficient computational modules that exploit graphical processor units (GPUs) when available. The ISCE 3.0 framework is designed to work in an operational environment as well as on a single user's laptop or compute cluster, with services to discover capabilities and scale computations accordingly.", "doi": "10.1109/IGARSS.2018.8517504", "isbn": "978-1-5386-7150-4", "publisher": "IEEE", "place_of_publication": "Piscataway, NJ", "publication_date": "2018-07", "pages": "4897-4900" }, { "id": "authors:z1811-29e70", "collection": "authors", "collection_id": "z1811-29e70", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20180808-081056969", "type": "article", "title": "Quantifying Ground Deformation in the Los Angeles and Santa Ana Coastal Basins Due to Groundwater Withdrawal", "author": [ { "family_name": "Riel", "given_name": "Bryan", "orcid": "0000-0003-1940-3910", "clpid": "Riel-B" }, { "family_name": "Simons", "given_name": "Mark", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" }, { "family_name": "Ponti", "given_name": "Daniel", "orcid": "0000-0002-2437-5144", "clpid": "Ponti-D" }, { "family_name": "Agram", "given_name": "Piyush", "clpid": "Agram-P-S" }, { "family_name": "Jolivet", "given_name": "Romain", "orcid": "0000-0002-9896-3651", "clpid": "Jolivet-R" } ], "abstract": "We investigate complex surface deformation within the Los Angeles and Santa Ana Coastal Basins due to groundwater withdrawal and subsequent aquifer compaction/expansion. We analyze an 18 year interferometric synthetic aperture radar (InSAR) time series of 881 interferograms in conjunction with global positioning system (GPS) data within the groundwater basins. The large data set required the development of a distributed time series analysis framework able to automatically decompose both the InSAR and GPS time series into short\u2010term and long\u2010term signals. We find that short\u2010term, seasonal oscillations of ground elevations due to annual groundwater withdrawal and recharge are unsteady due to changes in seasonal withdrawal by major water districts. The spatial pattern of seasonal ground deformation near the center of the basin corresponds to a diffusion process with peak deformation occurring at locations with highest groundwater production. Long\u2010term signals occur over broader areas and are ultimately caused by long\u2010term changes in groundwater production. Comparison of the geodetic data with hydraulic head data from major water districts suggests that different regions of the groundwater system are responsible for different temporal components in the observed ground deformation. Short\u2010term, seasonal ground deformation is caused by compaction of shallower aquifers used for the majority of groundwater production whereas long\u2010term ground deformation is correlated with delayed compaction of deeper aquifers and potential compressible clay layers. These results demonstrate the potential for geodetic analysis to be an important tool for groundwater management to maintain sustainable pumping practices.", "doi": "10.1029/2017WR021978", "issn": "0043-1397", "publisher": "American Geophysical Union", "publication": "Water Resources Research", "publication_date": "2018-05", "series_number": "5", "volume": "54", "issue": "5", "pages": "3557-3582" }, { "id": "authors:b3y86-9na27", "collection": "authors", "collection_id": "b3y86-9na27", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20180104-155549103", "type": "article", "title": "Big Remotely Sensed Data: tools, applications and experiences", "author": [ { "family_name": "Casu", "given_name": "F.", "clpid": "Casu-F" }, { "family_name": "Manunta", "given_name": "M.", "clpid": "Manunta-M" }, { "family_name": "Agram", "given_name": "P. S.", "clpid": "Agram-P-S" }, { "family_name": "Crippen", "given_name": "R. E.", "clpid": "Crippen-R-E" } ], "abstract": "The increased availability of large remote sensing datasets is generating heightened interest within the geoscience community, and more generally within human society. Indeed, remote sensing datasets that have commonly been analyzed as single scenes, or neighboring scenes, or temporally sequential scenes can now be analyzed en masse. This is due to the accumulation of large data volumes through time by increasing numbers of satellites, data access efficiencies due to technical advances and policy changes, and advances in hardware and software processing capabilities.", "doi": "10.1016/j.rse.2017.09.013", "issn": "0034-4257", "publisher": "Elsevier", "publication": "Remote Sensing of Environment", "publication_date": "2017-12-01", "volume": "202", "pages": "1-2" }, { "id": "authors:hf4cp-42b73", "collection": "authors", "collection_id": "hf4cp-42b73", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170726-153646811", "type": "article", "title": "InSAR Time-Series Estimation of the Ionospheric Phase Delay: An Extension of the Split Range-Spectrum Technique", "author": [ { "family_name": "Fattahi", "given_name": "Heresh", "orcid": "0000-0001-6926-4387", "clpid": "Fattahi-H" }, { "family_name": "Simons", "given_name": "Mark", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" }, { "family_name": "Agram", "given_name": "Piyush", "clpid": "Agram-P-S" } ], "abstract": "Repeat pass interferometric synthetic aperture radar (InSAR) observations may be significantly impacted by the propagation delay of the microwave signal through the ionosphere, which is commonly referred to as ionospheric delay. The dispersive character of the ionosphere at microwave frequencies allows one to estimate the ionospheric delay from InSAR data through a split range-spectrum technique. Here, we extend the existing split range-spectrum technique to InSAR time-series. We present an algorithm for estimating a time-series of ionospheric phase delay that is useful for correcting InSAR time-series of ground surface displacement or for evaluating the spatial and temporal variations of the ionosphere's total electron content (TEC). Experimental results from stacks of L-band SAR data acquired by the ALOS-1 Japanese satellite show significant ionospheric phase delay equivalent to 2 m of the temporal variation of InSAR time-series along 445 km in Chile, a region at low latitudes where large TEC variations are common. The observed delay is significantly smaller, with a maximum of 10 cm over 160 km, in California. The estimation and correction of ionospheric delay reduces the temporal variation of the InSAR time-series to centimeter levels in Chile. The ionospheric delay correction of the InSAR time-series reveals earthquake-induced ground displacement, which otherwise could not be detected. A comparison with independent GPS time-series demonstrates an order of magnitude reduction in the root mean square difference between GPS and InSAR after correcting for ionospheric delay. The results show that the presented algorithm significantly improves the accuracy of InSAR time-series and should become a routine component of InSAR time-series analysis.", "doi": "10.1109/TGRS.2017.2718566", "issn": "0196-2892", "publisher": "IEEE", "publication": "IEEE Transactions on Geoscience and Remote Sensing", "publication_date": "2017-10-10", "series_number": "10", "volume": "55", "issue": "10", "pages": "5984-5996" }, { "id": "authors:d01vb-pwk55", "collection": "authors", "collection_id": "d01vb-pwk55", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170705-164235369", "type": "article", "title": "Geodetic Imaging of Time-Dependent Three-Component Surface Deformation: Application to Tidal-Timescale Ice Flow of Rutford Ice Stream, West Antarctica", "author": [ { "family_name": "Milillo", "given_name": "Pietro", "orcid": "0000-0002-1171-3976", "clpid": "Milillo-P" }, { "family_name": "Minchew", "given_name": "Brent", "orcid": "0000-0002-5991-3926", "clpid": "Minchew-B-M" }, { "family_name": "Simons", "given_name": "Mark", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" }, { "family_name": "Agram", "given_name": "Piyush", "clpid": "Agram-P-S" }, { "family_name": "Riel", "given_name": "Bryan", "orcid": "0000-0003-1940-3910", "clpid": "Riel-B" } ], "abstract": "We present a method for inferring time-dependent three-component surface deformation fields given a set of geodetic images of displacements collected from multiple viewing geometries. Displacements are parameterized in time with a dictionary of displacement functions. The algorithm extends an earlier single-component (i.e., single line of sight) framework for time-series analysis to three spatial dimensions using combinations of multitemporal, multigeometry interferometic synthetic aperture radar (InSAR) and/or pixel offset (PO) maps. We demonstrate this method with a set of 101 pairs of azimuth and range PO maps generated for a portion of the Rutford Ice Stream, West Antarctica, derived from data collected by the COSMO-SkyMed satellite constellation. We compare our results with previously published InSAR mean velocity fields and selected GPS time series and show that our resulting three-component surface displacements resolve both secular motion and tidal variability.", "doi": "10.1109/TGRS.2017.2709783", "issn": "0196-2892", "publisher": "IEEE", "publication": "IEEE Transactions on Geoscience and Remote Sensing", "publication_date": "2017-10", "series_number": "10", "volume": "55", "issue": "10", "pages": "5515-5524" }, { "id": "authors:pc0wj-x7263", "collection": "authors", "collection_id": "pc0wj-x7263", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20161025-121510576", "type": "article", "title": "A Network-Based Enhanced Spectral Diversity Approach for TOPS Time-Series Analysis", "author": [ { "family_name": "Fattahi", "given_name": "Heresh", "orcid": "0000-0001-6926-4387", "clpid": "Fattahi-H" }, { "family_name": "Agram", "given_name": "Piyush", "clpid": "Agram-P-S" }, { "family_name": "Simons", "given_name": "Mark", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" } ], "abstract": "For multitemporal analysis of synthetic aperture radar (SAR) images acquired with a terrain observation by progressive scan (TOPS) mode, all acquisitions from a given satellite track must be coregistered to a reference coordinate system with accuracies better than 0.001 of a pixel (assuming full SAR resolution) in the azimuth direction. Such a high accuracy can be achieved through geometric coregistration, using precise satellite orbits and a digital elevation model, followed by a refinement step using a time-series analysis of coregistration errors. These errors represent the misregistration between all TOPS acquisitions relative to the reference coordinate system. We develop a workflow to estimate the time series of azimuth misregistration using a network-based enhanced spectral diversity (NESD) approach, in order to reduce the impact of temporal decorrelation on coregistration. Example time series of misregistration inferred for five tracks of Sentinel-1 TOPS acquisitions indicates a maximum relative azimuth misregistration of less than 0.01 of the full azimuth resolution between the TOPS acquisitions in the studied areas. Standard deviation of the estimated misregistration time series for different stacks varies from 1.1e-3 to 2e-3 of the azimuth resolution, equivalent to 1.6-2.8 cm orbital uncertainty in the azimuth direction. These values fall within the 1-sigma orbital uncertainty of the Sentinel-1 orbits and imply that orbital uncertainty is most likely the main source of the constant azimuth misregistration between different TOPS acquisitions. We propagate the uncertainty of individual misregistration estimated with ESD to the misregistration time series estimated with NESD and investigate the different challenges for operationalizing NESD.", "doi": "10.1109/TGRS.2016.2614925", "issn": "0196-2892", "publisher": "IEEE", "publication": "IEEE Transactions on Geoscience and Remote Sensing", "publication_date": "2017-02", "series_number": "2", "volume": "55", "issue": "2", "pages": "777-786" }, { "id": "authors:z8aqv-9mm32", "collection": "authors", "collection_id": "z8aqv-9mm32", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170317-084759208", "type": "book_section", "title": "3D velocity field time series using synthetic aperture radar: application to tidal-timescale ice-flow variability in Rutford Ice Stream, West Antarctica", "book_title": "SAR Image Analysis, Modeling, and Techniques XVI", "author": [ { "family_name": "Milillo", "given_name": "Pietro", "orcid": "0000-0002-1171-3976", "clpid": "Milillo-P" }, { "family_name": "Minchew", "given_name": "Brent", "orcid": "0000-0002-5991-3926", "clpid": "Minchew-B-M" }, { "family_name": "Agram", "given_name": "Piyush", "clpid": "Agram-P-S" }, { "family_name": "Riel", "given_name": "Bryan", "orcid": "0000-0003-1940-3910", "clpid": "Riel-B" }, { "family_name": "Simons", "given_name": "Mark", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" } ], "contributor": [ { "family_name": "Notarnicola", "given_name": "Claudia", "clpid": "Notarnicola-C" }, { "family_name": "Paloscia", "given_name": "Simonetta", "clpid": "Paloscia-S" }, { "family_name": "Pierdicca", "given_name": "Nazzareno", "clpid": "Pierdicca-N" }, { "family_name": "Mitchard", "given_name": "Edward", "clpid": "Mitchard-E" } ], "abstract": "We present a general method for retrieving time-series of three component surface velocity field vector given a set of continuous synthetic aperture radar (SAR) acquisitions collected from multiple geometries. Our algorithm extends the single-line-of-sight mathematical framework developed for time-series analysis using interferometric SAR (InSAR) to three spatial dimensions. The inversion is driven by a design matrix corresponding to a dictionary of displacement functions parameterized in time. The resulting model minimizes a cost function using a non-regularized least-squares method. We applied our method to Rutford ice stream (RIS), West Antarctica, using a set of 101 multi-track multi-angle COSMO-SkyMed displacement maps generating azimuth and range pixel offsets.", "doi": "10.1117/12.2241617", "isbn": "9781510604100", "publisher": "Society of Photo-Optical Instrumentation Engineers", "place_of_publication": "Bellingham, WA", "publication_date": "2016-10-28", "pages": "Art. No. 1000309" }, { "id": "authors:6srgx-sgn93", "collection": "authors", "collection_id": "6srgx-sgn93", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20161115-084858641", "type": "book_section", "title": "Recent rapid disaster response products derived from COSMO-Skymed synthetic aperture radar data", "book_title": "2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)", "author": [ { "family_name": "Yun", "given_name": "Sang-Ho", "orcid": "0000-0001-6952-6156", "clpid": "Yun-Sang-Ho" }, { "family_name": "Owen", "given_name": "Susan", "clpid": "Owen-S-E" }, { "family_name": "Webb", "given_name": "Frank", "clpid": "Webb-F-H" }, { "family_name": "Hua", "given_name": "Hook", "clpid": "Hua-Hook" }, { "family_name": "Milillo", "given_name": "Pietro", "orcid": "0000-0002-1171-3976", "clpid": "Milillo-P" }, { "family_name": "Fielding", "given_name": "Eric", "orcid": "0000-0002-6648-8067", "clpid": "Fielding-E-J" }, { "family_name": "Simons", "given_name": "Mark", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" }, { "family_name": "Agram", "given_name": "Piyush", "clpid": "Agram-P-S" }, { "family_name": "Liang", "given_name": "Cunren", "orcid": "0000-0003-3938-426X", "clpid": "Liang-Cunren" }, { "family_name": "Moore", "given_name": "Angelyn", "orcid": "0000-0003-1715-6338", "clpid": "Moore-A-W" }, { "family_name": "Sacco", "given_name": "Patrizia", "clpid": "Sacco-P" }, { "family_name": "Gurrola", "given_name": "Eric", "clpid": "Gurrola-E" }, { "family_name": "Manipon", "given_name": "Gerald", "clpid": "Manipon-G" }, { "family_name": "Rosen", "given_name": "Paul", "clpid": "Rosen-P-A" }, { "family_name": "Lundgren", "given_name": "Paul", "orcid": "0000-0002-6771-2876", "clpid": "Lundgren-P" }, { "family_name": "Coletta", "given_name": "Alessandro", "clpid": "Coletta-A" } ], "abstract": "The April 25, 2015 M7.8 Gorkha earthquake caused more than 8,000 fatalities and widespread building damage in central Nepal. Four days after the earthquake, the Italian Space Agency's (ASI's) COSMO-SkyMed Synthetic Aperture Radar (SAR) satellite acquired data over Kathmandu area. Nine days after the earthquake, the Japan Aerospace Exploration Agency's (JAXA's) ALOS-2 SAR satellite covered larger area. Using these radar observations, we rapidly produced damage proxy maps derived from temporal changes in Interferometric SAR (InSAR) coherence. These maps were qualitatively validated through comparison with independent damage analyses by National Geospatial-Intelligence Agency (NGA) and the UNITAR's (United Nations Institute for Training and Research's) Operational Satellite Applications Programme (UNOSAT), and based on our own visual inspection of DigitalGlobe's WorldView optical pre- vs. post-event imagery. Our maps were quickly released to responding agencies and the public, and used for damage assessment, determining inspection/imaging priorities, and reconnaissance fieldwork.", "doi": "10.1109/IGARSS.2016.7729533", "isbn": "978-1-5090-3332-4", "publisher": "IEEE", "place_of_publication": "Piscataway, NJ", "publication_date": "2016-07", "pages": "2066-2069" }, { "id": "authors:eyccb-ygb50", "collection": "authors", "collection_id": "eyccb-ygb50", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20150409-073405847", "type": "article", "title": "High interseismic coupling in the Eastern Makran (Pakistan) subduction zone", "author": [ { "family_name": "Lin", "given_name": "Y. N.", "clpid": "Lin-Y-N" }, { "family_name": "Jolivet", "given_name": "R.", "orcid": "0000-0002-9896-3651", "clpid": "Jolivet-R" }, { "family_name": "Simons", "given_name": "M.", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" }, { "family_name": "Agram", "given_name": "P. S.", "clpid": "Agram-P-S" }, { "family_name": "Martens", "given_name": "H. R.", "orcid": "0000-0003-2860-9013", "clpid": "Martens-H-R" }, { "family_name": "Li", "given_name": "Z.", "clpid": "Li-Z" }, { "family_name": "Lodi", "given_name": "S. H.", "clpid": "Lodi-S-H" } ], "abstract": "Estimating the extent of interseismic coupling along subduction zone megathrusts is essential for quantitative assessments of seismic and tsunami hazards. Up to now, quantifying the seismogenic potential of the eastern Makran subduction zone at the northern edge of the Indian ocean has remained elusive due to a paucity of geodetic observations. Furthermore, non-tectonic processes obscure the signature of accumulating elastic strain. Historical earthquakes of magnitudes greater than 7 have been reported. In particular, the 1945 Mw 8.1 earthquake resulted in a significant tsunami that swept the shores of the Arabian Sea and the Indian Ocean. A quantitative estimate of elastic strain accumulation along the subduction plate boundary in eastern Makran is needed to confront previous indirect and contradictory conclusions about the seismic potential in the region. Here, we infer the distribution of interseismic coupling on the eastern Makran megathrust from time series of satellite Interferometric Synthetic Aperture Radar (InSAR) images acquired between 2003 and 2010, applying a consistent series of corrections to extract the low amplitude, long wavelength deformation signal associated with elastic strain on the megathrust. We find high interseismic coupling (i.e. the megathrust does not slip and elastic strain accumulates) in the central section of eastern Makran, where the 1945 earthquake occurred, while lower coupling coincides spatially with the subduction of the Sonne Fault Zone. The inferred accumulation of elastic strain since the 1945 earthquake is consistent with the future occurrence of magnitude 7+ earthquakes and we cannot exclude the possibility of a multi-segment rupture (Mw 8+). However, the likelihood for such scenarios might be modulated by partitioning of plate convergence between slip on the megathrust and internal deformation of the overlying, actively deforming, accretionary wedge.", "doi": "10.1016/j.epsl.2015.03.037", "issn": "0012-821X", "publisher": "Elsevier", "publication": "Earth and Planetary Science Letters", "publication_date": "2015-06-15", "volume": "420", "pages": "116-126" }, { "id": "authors:3tqhw-rkk85", "collection": "authors", "collection_id": "3tqhw-rkk85", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20140829-085349671", "type": "article", "title": "Detecting transient signals in geodetic time series using sparse estimation techniques", "author": [ { "family_name": "Riel", "given_name": "Bryan", "orcid": "0000-0003-1940-3910", "clpid": "Riel-B" }, { "family_name": "Simons", "given_name": "Mark", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" }, { "family_name": "Agram", "given_name": "Piyush", "clpid": "Agram-P-S" }, { "family_name": "Zhan", "given_name": "Zhongwhen", "orcid": "0000-0002-5586-2607", "clpid": "Zhan-Zhongwen" } ], "abstract": "We present a new method for automatically detecting transient deformation signals from geodetic time series. We cast the detection problem as a least squares procedure where the design matrix corresponds to a highly overcomplete, nonorthogonal dictionary of displacement functions in time that resemble transient signals of various timescales. The addition of a sparsity-inducing regularization term to the cost function limits the total number of dictionary elements needed to reconstruct the signal. Sparsity-inducing regularization enhances interpretability of the resultant time-dependent model by localizing the dominant timescales and onset times of the transient signals. Transient detection can then be performed using convex optimization software where detection sensitivity is dependent on the strength of the applied sparsity-inducing regularization. To assess uncertainties associated with estimation of the dictionary coefficients, we compare solutions with those found through a Bayesian inference approach to sample the full model space for each dictionary element. In addition to providing uncertainty bounds on the coefficients and confirming the optimization results, Bayesian sampling reveals trade-offs between dictionary elements that have nearly equal probability in modeling a transient signal. Thus, we can rigorously assess the probabilities of the occurrence of transient signals and their characteristic temporal evolution. The detection algorithm is applied on several synthetic time series and real observed GPS time series for the Cascadia region. For the latter data set, we incorporate a spatial weighting scheme that self-adjusts to the local network density and filters for spatially coherent signals. The weighting allows for the automatic detection of repeating slow slip events.", "doi": "10.1002/2014JB011077", "issn": "2169-9313", "publisher": "American Geophysical Union", "publication": "Journal of Geophysical Research. Solid Earth", "publication_date": "2014-06", "series_number": "6", "volume": "119", "issue": "6", "pages": "5140-5160" }, { "id": "authors:c8fh7-qxp78", "collection": "authors", "collection_id": "c8fh7-qxp78", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20140515-083746685", "type": "article", "title": "Accounting for prediction uncertainty when inferring subsurface fault slip", "author": [ { "family_name": "Duputel", "given_name": "Zacharie", "clpid": "Duputel-Z" }, { "family_name": "Agram", "given_name": "Piyush S.", "clpid": "Agram-P-S" }, { "family_name": "Simons", "given_name": "Mark", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" }, { "family_name": "Minson", "given_name": "Sarah E.", "orcid": "0000-0001-5869-3477", "clpid": "Minson-S-E" }, { "family_name": "Beck", "given_name": "James L.", "clpid": "Beck-J-L" } ], "abstract": "This study lays the groundwork for a new generation of earthquake source models based on a general formalism that rigorously quantifies and incorporates the impact of uncertainties in fault slip inverse problems. We distinguish two sources of uncertainty when considering the discrepancy between data and forward model predictions. The first class of error is induced by imperfect measurements and is often referred to as observational error. The second source of uncertainty is generally neglected and corresponds to the prediction error, that is the uncertainty due to imperfect forward modelling. Yet the prediction error can be shown to scale approximately with the size of earthquakes and thus can dwarf the observational error, particularly for large events. Both sources of uncertainty can be formulated using the misfit covariance matrix, C_\u03c7, which combines a covariance matrix for observation errors, C_d and a covariance matrix for prediction errors, C_p, associated with inaccurate model predictions. We develop a physically based stochastic forward model to treat the model prediction uncertainty and show how C_p can be constructed to explicitly account for some of the inaccuracies in the earth model. Based on a first-order perturbation approach, our formalism relates C_p to uncertainties on the elastic parameters of different regions (e.g. crust, mantle, etc.). We demonstrate the importance of including C_p using a simple example of an infinite strike-slip fault in the quasi-static approximation. In this toy model, we treat only uncertainties in the 1-D depth distribution of the shear modulus. We discuss how this can be extended to general 3-D cases and applied to other parameters (e.g. fault geometry) using our formalism for C_p. The improved modelling of C_p is expected to lead to more reliable images of the earthquake rupture, that are more resistant to overfitting of data and include more realistic estimates of uncertainty on inferred model parameters.", "doi": "10.1093/gji/ggt517", "issn": "0956-540X", "publisher": "Royal Astronomical Society", "publication": "Geophysical Journal International", "publication_date": "2014-04", "series_number": "1", "volume": "197", "issue": "1", "pages": "464-482" }, { "id": "authors:ynsa3-d4e04", "collection": "authors", "collection_id": "ynsa3-d4e04", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20140611-105010798", "type": "article", "title": "Improving InSAR geodesy using Global Atmospheric Models", "author": [ { "family_name": "Jolivet", "given_name": "Romain", "orcid": "0000-0002-9896-3651", "clpid": "Jolivet-R" }, { "family_name": "Agram", "given_name": "Piyush Shanker", "clpid": "Agram-P-S" }, { "family_name": "Lin", "given_name": "Nina Y.", "clpid": "Lin-Nina-Y" }, { "family_name": "Simons", "given_name": "Mark", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" }, { "family_name": "Doin", "given_name": "Marie-Pierre", "clpid": "Doin-M-P" }, { "family_name": "Peltzer", "given_name": "Gilles", "clpid": "Peltzer-G" }, { "family_name": "Li", "given_name": "Zhenghong", "clpid": "Li-Zhenghong" } ], "abstract": "Spatial and temporal variations of pressure, temperature, and water vapor content in the\natmosphere introduce significant confounding delays in interferometric synthetic aperture radar (InSAR)\nobservations of ground deformation and bias estimates of regional strain rates. Producing robust estimates\nof tropospheric delays remains one of the key challenges in increasing the accuracy of ground deformation\nmeasurements using InSAR. Recent studies revealed the efficiency of global atmospheric reanalysis to\nmitigate the impact of tropospheric delays, motivating further exploration of their potential. Here we\nexplore the effectiveness of these models in several geographic and tectonic settings on both single\ninterferograms and time series analysis products. Both hydrostatic and wet contributions to the phase\ndelay are important to account for. We validate these path delay corrections by comparing with estimates\nof vertically integrated atmospheric water vapor content derived from the passive multispectral imager\nMedium-Resolution Imaging Spectrometer, onboard the Envisat satellite. Generally, the performance of the\nprediction depends on the vigor of atmospheric turbulence. We discuss (1) how separating atmospheric\nand orbital contributions allows one to better measure long-wavelength deformation and (2) how\natmospheric delays affect measurements of surface deformation following earthquakes, and (3) how such a\nmethod allows us to reduce biases in multiyear strain rate estimates by reducing the influence of unevenly\nsampled seasonal oscillations of the tropospheric delay.", "doi": "10.1002/2013JB010588", "issn": "2169-9313", "publisher": "American Geophysical Union", "publication": "Journal of Geophysical Research. Solid Earth", "publication_date": "2014-03", "series_number": "3", "volume": "119", "issue": "3", "pages": "2324-2341" }, { "id": "authors:0sb7c-vdq86", "collection": "authors", "collection_id": "0sb7c-vdq86", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20150924-082128270", "type": "article", "title": "Rapid Imaging of Earthquake Ruptures with Combined Geodetic and Seismic Analysis", "author": [ { "family_name": "Fielding", "given_name": "Eric J.", "orcid": "0000-0002-6648-8067", "clpid": "Fielding-E-J" }, { "family_name": "Simons", "given_name": "Mark", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" }, { "family_name": "Owen", "given_name": "Susan", "clpid": "Owen-S-E" }, { "family_name": "Lundgren", "given_name": "Paul", "orcid": "0000-0002-6771-2876", "clpid": "Lundgren-P" }, { "family_name": "Hua", "given_name": "Hook", "clpid": "Hua-Hook" }, { "family_name": "Agram", "given_name": "Piyush", "clpid": "Agram-P-S" }, { "family_name": "Liu", "given_name": "Zhen", "orcid": "0000-0002-6313-823X", "clpid": "Liu-Zhen" }, { "family_name": "Moore", "given_name": "Angelyn", "orcid": "0000-0003-1715-6338", "clpid": "Moore-A-W" }, { "family_name": "Milillo", "given_name": "Pietro", "orcid": "0000-0002-1171-3976", "clpid": "Milillo-P" }, { "family_name": "Polet", "given_name": "Jascha", "clpid": "Polet-J" }, { "family_name": "Samsonov", "given_name": "Sergey", "clpid": "Samsonov-S" }, { "family_name": "Rosen", "given_name": "Paul", "clpid": "Rosen-P-A" }, { "family_name": "Webb", "given_name": "Frank", "clpid": "Webb-F" }, { "family_name": "Milillo", "given_name": "Giovanni", "clpid": "Milillo-G" } ], "abstract": "Rapid determination of the location and extent of earthquake ruptures is helpful for disaster response, as it allows prediction of the likely area of major damage from the earthquake and can help with rescue and recovery planning. With the increasing availability of near real-time data from the Global Positioning System (GPS) and other global navigation satellite system receivers in active tectonic regions, and with the shorter repeat times of many recent and newly launched satellites, geodetic data can be obtained quickly after earthquakes or other disasters. We have been building a data system that can ingest, catalog, and process geodetic data and combine it with seismic analysis to estimate the fault rupture locations and slip distributions for large earthquakes.", "doi": "10.1016/j.protcy.2014.10.038", "issn": "2212-0173", "publisher": "Elsevier", "publication": "Procedia Technology", "publication_date": "2014", "volume": "16", "pages": "876-885" }, { "id": "authors:rdanm-wft34", "collection": "authors", "collection_id": "rdanm-wft34", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20130605-145120501", "type": "article", "title": "New Radar Interferometric Time Series Analysis Toolbox Released", "author": [ { "family_name": "Agram", "given_name": "P. S.", "clpid": "Agram-P-S" }, { "family_name": "Jolivet", "given_name": "R.", "orcid": "0000-0002-9896-3651", "clpid": "Jolivet-R" }, { "family_name": "Riel", "given_name": "B.", "orcid": "0000-0003-1940-3910", "clpid": "Riel-B" }, { "family_name": "Lin", "given_name": "Y. N.", "clpid": "Lin-Y-N" }, { "family_name": "Simons", "given_name": "M.", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" }, { "family_name": "Hetland", "given_name": "E.", "clpid": "Hetland-E-A" }, { "family_name": "Doin", "given_name": "M.-P.", "clpid": "Doin-M-P" }, { "family_name": "Lasserre", "given_name": "C.", "clpid": "Lasserre-C" } ], "abstract": "Interferometric synthetic aperture radar (InSAR) has become an important geodetic\ntool for measuring deformation of Earth's surface due to various geophysical phenomena,\nincluding slip on earthquake faults, subsurface migration of magma, slow\u2010moving\nlandslides, movement of shallow crustal fluids (e.g., water and oil), and glacier flow.\nAirborne and spaceborne synthetic aperture radar (SAR) instruments transmit microwaves\ntoward Earth's surface and detect the returning reflected waves. The phase of the\nreturned wave depends on the distance between the satellite and the surface, but it is\nalso altered by atmospheric and other effects. InSAR provides measurements of surface\ndeformation by combining amplitude and phase information from two SAR images of\nthe same location taken at different times to create an interferogram. Several existing\nopen\u2010source analysis tools [Rosen et al., 2004; Rosen et al., 2011; Kampes et al., 2003 ;\nSandwell et al., 2011] enable scientists to exploit observations from radar satellites\nacquired at two different epochs to produce a surface displacement map.", "doi": "10.1002/2013EO070001", "issn": "0096-3941", "publisher": "American Geophysical Union", "publication": "Eos", "publication_date": "2013-02-12", "series_number": "7", "volume": "94", "issue": "7", "pages": "69-70" }, { "id": "authors:95d9q-zx527", "collection": "authors", "collection_id": "95d9q-zx527", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20120328-070721528", "type": "article", "title": "Multiscale InSAR Time Series (MInTS) analysis of surface deformation", "author": [ { "family_name": "Hetland", "given_name": "E. A.", "clpid": "Hetland-E-A" }, { "family_name": "Mus\u00e9", "given_name": "P.", "clpid": "Mus\u00e9-P" }, { "family_name": "Simons", "given_name": "M.", "orcid": "0000-0003-1412-6395", "clpid": "Simons-M" }, { "family_name": "Lin", "given_name": "Y. N.", "clpid": "Lin-Y-N" }, { "family_name": "Agram", "given_name": "P. S.", "clpid": "Agram-P-S" }, { "family_name": "DiCaprio", "given_name": "C. J.", "clpid": "DiCaprio-C-J" } ], "abstract": "We present a new approach to extracting spatially and temporally continuous ground deformation fields from interferometric synthetic aperture radar (InSAR) data. We focus on unwrapped interferograms from a single viewing geometry, estimating ground deformation along the line-of-sight. Our approach is based on a wavelet decomposition in space and a general parametrization in time. We refer to this approach as MInTS (Multiscale InSAR Time Series). The wavelet decomposition efficiently deals with commonly seen spatial covariances in repeat-pass InSAR measurements, since the coefficients of the wavelets are essentially spatially uncorrelated. Our time-dependent parametrization is capable of capturing both recognized and unrecognized processes, and is not arbitrarily tied to the times of the SAR acquisitions. We estimate deformation in the wavelet-domain, using a cross-validated, regularized least squares inversion. We include a model-resolution-based regularization, in order to more heavily damp the model during periods of sparse SAR acquisitions, compared to during times of dense acquisitions. To illustrate the application of MInTS, we consider a catalog of 92 ERS and Envisat interferograms, spanning 16 years, in the Long Valley caldera, CA, region. MInTS analysis captures the ground deformation with high spatial density over the Long Valley region.", "doi": "10.1029/2011JB008731", "issn": "0148-0227", "publisher": "American Geophysical Union", "publication": "Journal of Geophysical Research B", "publication_date": "2012-02-18", "volume": "117", "pages": "Art. No. B02404" }, { "id": "authors:je4sx-jpk17", "collection": "authors", "collection_id": "je4sx-jpk17", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20120125-090627347", "type": "article", "title": "High quality InSAR data linked to seasonal change in hydraulic head for an agricultural area in the San Luis Valley, Colorado", "author": [ { "family_name": "Reeves", "given_name": "Jessica A.", "clpid": "Reeves-J-A" }, { "family_name": "Knight", "given_name": "Rosemary", "orcid": "0000-0002-0975-9019", "clpid": "Knight-R" }, { "family_name": "Zebker", "given_name": "Howard A.", "clpid": "Zebker-H-A" }, { "family_name": "Schre\u00fcder", "given_name": "Willem A.", "clpid": "Schre\u00fcder-W-A" }, { "family_name": "Agram", "given_name": "Piyush Shanker", "clpid": "Agram-P-S" }, { "family_name": "Lauknes", "given_name": "Tom R.", "clpid": "Lauknes-T-R" } ], "abstract": "In the San Luis Valley (SLV), Colorado legislation passed in 2004 requires that hydraulic head levels in the confined aquifer system stay within the range experienced in the years 1978\u20132000. While some measurements of hydraulic head exist, greater spatial and temporal sampling would be very valuable in understanding the behavior of the system. Interferometric synthetic aperture radar (InSAR) data provide fine spatial resolution measurements of Earth surface deformation, which can be related to hydraulic head change in the confined aquifer system. However, change in cm-scale crop structure with time leads to signal decorrelation, resulting in low quality data. Here we apply small baseline subset (SBAS) analysis to InSAR data collected from 1992 to 2001. We are able to show high levels of correlation, denoting high quality data, in areas between the center pivot irrigation circles, where the lack of water results in little surface vegetation. At three well locations we see a seasonal variation in the InSAR data that mimics the hydraulic head data. We use measured values of the elastic skeletal storage coefficient to estimate hydraulic head from the InSAR data. In general the magnitude of estimated and measured head agree to within the calculated error. However, the errors are unacceptably large due to both errors in the InSAR data and uncertainty in the measured value of the elastic skeletal storage coefficient. We conclude that InSAR is capturing the seasonal head variation, but that further research is required to obtain accurate hydraulic head estimates from the InSAR deformation measurements.", "doi": "10.1029/2010WR010312", "issn": "0043-1397", "publisher": "American Geophysical Union", "publication": "Water Resources Research", "publication_date": "2011-12-14", "volume": "47", "pages": "Art. No. W12510" } ]