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Automated estimation and tools to extract positions, velocities, breaks, and seasonal terms from daily GNSS measurements: illuminating nonlinear Salton Trough deformation / Michael B. Heflin in Earth and space science, vol 7 n° 7 (July 2020)
[article]
Titre : Automated estimation and tools to extract positions, velocities, breaks, and seasonal terms from daily GNSS measurements: illuminating nonlinear Salton Trough deformation Type de document : Article/Communication Auteurs : Michael B. Heflin, Auteur ; Andrea Donnellan, Auteur ; Jay Parker, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 10 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] chaîne de traitement
[Termes IGN] champ de vitesse
[Termes IGN] déformation horizontale de la croute terrestre
[Termes IGN] données GNSS
[Termes IGN] dorsale
[Termes IGN] faille géologique
[Termes IGN] modèle géologique
[Termes IGN] positionnement par GNSS
[Termes IGN] série temporelle
[Termes IGN] sismologie
[Termes IGN] station GPS
[Termes IGN] valeur aberrante
[Termes IGN] variation saisonnièreRésumé : (auteur) This paper describes the methods used to estimate positions, velocities, breaks, and seasonalterms from daily Global Navigation Satellite System (GNSS) measurements. Break detection and outlierremoval have been automated so that decades of daily measurements from thousands of stations can beprocessed in a few hours. New measurements are added, and parameters are updated every week. Modelparameters allow separation of interseismic, annual, coseismic, and postseismic signals. Tools availablethrough GeoGateway (http://geo-gateway.org) allow rapid visualization and analysis of these terms forresults that can be subsetted in time or space. Results show highly variable and nonlinear motion for GPSstations in southern California. The variable motion is related to seasonal motions, distributed tectonicmotion, earthquakes, and postseismic motions that can continue for years. In some areas results suggest thatadditional processes are responsible for the observed motions. In general, following earthquakes, stationsreturn to their longterm motions after 2–3 years, though some exceptions occur. The use of the tools showsnonlinear motion in the Salton Trough of southern California related to the 2010 M7.2 El MayorCucapahearthquake, 2012 Brawley earthquake swarm, and a creep event on the Superstition Hills fault in 2017. Numéro de notice : A2020-446 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1029/2019EA000644 Date de publication en ligne : 18/05/2020 En ligne : https://doi.org/10.1029/2019EA000644 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95516
in Earth and space science > vol 7 n° 7 (July 2020) . - 10 p.[article]Joint inversion of GPS and high-resolution GRACE gravity data for the 2012 Wharton basin earthquakes / Michel Diament in Journal of geodynamics, vol 136 (May 2020)
[article]
Titre : Joint inversion of GPS and high-resolution GRACE gravity data for the 2012 Wharton basin earthquakes Type de document : Article/Communication Auteurs : Michel Diament , Auteur ; Valentin O. Mikhailov, Auteur ; Elena P. Timoshkina, Auteur Année de publication : 2020 Projets : TOSCA / Article en page(s) : n° 101722 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] coordonnées GPS
[Termes IGN] déformation de la croute terrestre
[Termes IGN] données GRACE
[Termes IGN] élasticité
[Termes IGN] Indien (océan)
[Termes IGN] séisme
[Termes IGN] viscositéRésumé : (auteur) The Wharton basin is situated in the north-eastern part of the Indian Ocean. In 2012 it hosted the largest intraplate strike-slip earthquakes ever recorded by geophysical networks. The Mw 8.6 earthquake of April 11, 2012, was preceded by a major foreshock (Mw 7.2) on January 10 and was followed two hours afterward by a Mw 8.2 event. These three large events occurred at the diffuse boundary between the Indian and Australian plates and were almost pure strike-slips on sub-vertical rupture surfaces. Using GRACE data, we first extracted the coseismic and postseismic gravity signals caused by these earthquakes. Then we fitted both GPS and the highest available spatial resolution of GRACE data using the geometry of the fault system suggested by Hill et al. (2015). We propose a regularization, which allows to solve for a linear problem in order to invert GPS and GRACE data under constraints on the rake angle. Our inversion yields a uniform displacement field on all elements of a given fault plane. Our solution shows that even the main displacement occurred on WNW trending faults, comparable displacement also occurred on a rupture striking NNE. Hence, we show that the deformation in this diffuse plate boundary region in 2012 was accommodated by displacements along both fault-systems. A viscoelastic relaxation of the asthenosphere with a Maxwell viscosity 1019 Pa∙s successfully explains the postseismic displacements at GPS sites and postseismic gravity signals. The limited postseismic aftershock activity suggests small postseismic slip in the area of the 2012 Wharton earthquakes contrary to what is often observed after large subduction event. Because a part of the observed signal could be related to afterslip, our obtained Maxwell viscosity value should be considered as a lower limit of the asthenospheric viscosity below the Wharton basin. Numéro de notice : A2020-876 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jog.2020.101722 Date de publication en ligne : 20/03/2020 En ligne : https://doi.org/10.1016/j.jog.2020.101722 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99670
in Journal of geodynamics > vol 136 (May 2020) . - n° 101722[article]Performance of real-time undifferenced precise positioning assisted by remote IGS multi-GNSS stations / Zhiqiang Liu in GPS solutions, vol 24 n° 2 (April 2020)
[article]
Titre : Performance of real-time undifferenced precise positioning assisted by remote IGS multi-GNSS stations Type de document : Article/Communication Auteurs : Zhiqiang Liu, Auteur ; Dongjie Yue, Auteur ; Zhangyu Huang, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] décalage d'horloge
[Termes IGN] filtre de Kalman
[Termes IGN] horloge du satellite
[Termes IGN] international GPS service for geodynamics
[Termes IGN] Nouvelle-Zélande
[Termes IGN] onde sismique
[Termes IGN] positionnement ponctuel précis
[Termes IGN] précision du positionnement
[Termes IGN] retard troposphérique zénithal
[Termes IGN] séisme
[Termes IGN] temps de convergence
[Termes IGN] temps réelRésumé : (auteur) The heavy reliance of real-time precise point positioning (RTPPP) on external satellite clock products may lead to discontinuity or even failure in time-critical applications. We present an alternative approach of real-time undifferenced precise positioning (RUP) that, by combining satellite clock estimation and precise point positioning based on the extended Kalman filter, is independent of external satellite clock corrections. The approach is evaluated in simulated real time with the assistance of a variable number of IGS multi-GNSS stations located between 1359.7 and 4852.5 km from the users. The results show that even with a single auxiliary IGS station, RUP is still feasible and able to retain centimeter-level positioning accuracy. Typically, with three auxiliary IGS stations about 2000–3000 km away, an accuracy of about 2 cm in the horizontal and 5 cm in the vertical can be achieved. The performance of RUP is comparable to that of PPP using 5-s satellite clock products and notably exhibits superior short-term precision in dealing with high-rate (1 Hz) GPS/GLONASS observations. The addition of GLONASS observations reduces the convergence time by 56.9% and improves the 3-D position accuracy by 31.8% while increasing the processing latency by a factor of about 1.6. Employing three IGS stations over 2400 km away from the epicenter, RUP is applied for the rapid determination of coseismic displacements and waveforms for the 2016 Kaikoura earthquake, yielding highly consistent results compared to those obtained from post-processed PPP in the global reference frame. We also explore its potential in facilitating real-time online services in terms of real-time precise positioning, zenith tropospheric delay retrieving, and satellite clock estimation. Numéro de notice : A2020-328 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-0972-6 Date de publication en ligne : 12/03/2020 En ligne : https://doi.org/10.1007/s10291-020-0972-6 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95209
in GPS solutions > vol 24 n° 2 (April 2020)[article]Bayesian inversion of convolved hidden Markov models with applications in reservoir prediction / Torstein Fjeldstad in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
[article]
Titre : Bayesian inversion of convolved hidden Markov models with applications in reservoir prediction Type de document : Article/Communication Auteurs : Torstein Fjeldstad, Auteur ; Henning Omre, Auteur Année de publication : 2020 Article en page(s) : pp 1957 - 1968 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] amplitude
[Termes IGN] analyse mathématique
[Termes IGN] approximation
[Termes IGN] chaîne de Markov
[Termes IGN] filtrage numérique d'image
[Termes IGN] lithologie
[Termes IGN] méthode de Monte-Carlo par chaînes de Markov
[Termes IGN] méthode du maximum de vraisemblance (estimation)
[Termes IGN] modèle d'inversion
[Termes IGN] modèle mathématique
[Termes IGN] processus gaussien
[Termes IGN] sismicitéRésumé : (Auteur) The efficient assessment of convolved hidden Markov models is discussed. The bottom layer is defined as an unobservable categorical first-order Markov chain, whereas the middle layer is assumed to be a Gaussian spatial variable conditional on the bottom layer. Hence, this layer appears marginally as a Gaussian mixture spatial variable. We observe the top layer as a convolution of the middle layer with Gaussian errors. The focus is on assessing the categorical and Gaussian mixture variables given the observations, and we operate in a Bayesian inversion framework. The model is defined to perform the inversion of subsurface seismic amplitude-versus-offset data into lithology/fluid classes and to assess the associated seismic material properties. Due to the spatial coupling in the likelihood functions, evaluation of the posterior normalizing constant is computationally demanding, and brute-force, single-site updating Markov chain Monte Carlo (MCMC) algorithms converge far too slowly to be useful. We construct two classes of approximate posterior models, which we assess analytically and efficiently using the recursive forward–backward algorithm. These approximate posterior densities are used as proposal densities in an independent proposal MCMC algorithm to determine the correct posterior model. A set of synthetic realistic examples is presented. The proposed approximations provide efficient proposal densities, which results in acceptance probabilities in the range 0.10–0.50 in the MCMC algorithm. A case study of lithology/fluid seismic inversion is presented. The lithology/fluid classes and the seismic material properties can be reliably predicted. Numéro de notice : A2020-093 Affiliation des auteurs : non IGN Thématique : IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2951205 Date de publication en ligne : 26/11/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2951205 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94667
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 3 (March 2020) . - pp 1957 - 1968[article]Poststack seismic data denoising based on 3-D convolutional neural network / Dawei Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
[article]
Titre : Poststack seismic data denoising based on 3-D convolutional neural network Type de document : Article/Communication Auteurs : Dawei Liu, Auteur ; Dawei Liu, Auteur ; Xiaokai Wang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1598 - 1629 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] apprentissage profond
[Termes IGN] bruit blanc
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données localisées 3D
[Termes IGN] échantillonnage
[Termes IGN] filtrage du bruit
[Termes IGN] filtre de Gauss
[Termes IGN] post-stratification de données
[Termes IGN] séisme
[Termes IGN] sismologieRésumé : (Auteur) Deep learning has been successfully applied to image denoising. In this study, we take one step forward by using deep learning to suppress random noise in poststack seismic data from the aspects of network architecture and training samples. On the one hand, poststack seismic data denoising mainly aims at 3-D seismic data. We designed an end-to-end 3-D denoising convolutional neural network (3-D-DnCNN) that takes raw 3-D cubes as input in order to better extract the features of the 3-D spatial structure of poststack seismic data. On the other hand, denoising images with deep learning require noisy–clean sample pairs for training. In the field of seismic data processing, researchers usually try their best to suppress noise by using complex processes that combine different methods, but clean labels of seismic data are not available. In addition, building training samples in field seismic data has become an interesting but challenging problem. Therefore, we propose a training sample selection method that contains a complex workflow to produce comparatively ideal training samples. Experiments in this study demonstrate that deep learning can directly learn the ability to denoise field seismic data from selected samples. Although the building of the training samples may occur through a complex process, the experimental results of synthetic seismic data and field seismic data show that the 3-D-DnCNN has learned the ability to suppress the Gaussian noise and super-Gaussian noise from different training samples. Moreover, the 3-D-DnCNN network has better denoising performance toward arc-like imaging noise. In addition, we adopt residual learning and batch normalization in order to accelerate the training speed. After network training is satisfactorily completed, its processing efficiency can be significantly higher than that of conventional denoising methods. Numéro de notice : A2020-087 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2947149 Date de publication en ligne : 06/11/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2947149 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94661
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 3 (March 2020) . - pp 1598 - 1629[article]Complex deformation at shallow depth during the 30 October 2016 Mw6.5 Norcia earthquake: interferencebetween tectonic and gravity processes? / Arthur Delorme in Tectonics, vol 39 n° 2 (February 2020)PermalinkLand use and land cover change modeling and future potential landscape risk assessment using Markov-CA model and analytical hierarchy process / Biswajit Nath in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)PermalinkSome thoughts on measuring earthquake deformation using optical imagery / Min Huang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)PermalinkVolcano-seismic transfer learning and uncertainty quantification with bayesian neural networks / Angel Bueno in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)PermalinkLow-frequency desert noise intelligent suppression in seismic data based on multiscale geometric analysis convolutional neural network / Yuxing Zhao in IEEE Transactions on geoscience and remote sensing, vol 58 n° 1 (January 2020)PermalinkPermalinkModelling of the timeseries of GNSS coordinates and their interaction with average magnitude earthquakes / Sanja Tucikesic in Geodetski vestnik, Vol 63 n° 4 (December 2019)PermalinkIntroducing a vertical land motion model for improving estimates of sea level rates derived from tide gauge records affected by earthquakes / Anna Klos in GPS solutions, vol 23 n° 4 (October 2019)PermalinkOptimal segmentation of high spatial resolution images for the classification of buildings using random forests / James Bialas in International journal of applied Earth observation and geoinformation, vol 82 (October 2019)PermalinkCo-seismic displacement and waveforms of the 2018 Alaska earthquake from high-rate GPS PPP velocity estimation / Shuanggen Jin in Journal of geodesy, vol 93 n° 9 (September 2019)PermalinkIntegration of LiDAR and multispectral images for rapid exposure and earthquake vulnerability estimation. Application in Lorca, Spain / Yolanda Torres in International journal of applied Earth observation and geoinformation, vol 81 (September 2019)PermalinkSensitivity of acoustic emission triggering to small pore pressure cycling perturbations during brittle creep / Kristel Chanard in Geophysical research letters, vol 46 n° 13 (16 July 2019)PermalinkThe cause of the 2011 Hawthorne (Nevada) earthquake swarm constrained by seismic and InSAR methods / Xianjie Zha in Journal of geodesy, vol 93 n°6 (June 2019)PermalinkMonitoring suspended particle matter using GOCI satellite data after the Tohoku (Japan) tsunami in 2011 / Audrey Minghelli in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol 12 n° 2 (February 2019)PermalinkPermalinkDPOD2014 : A new DORIS extension of ITRF2014 for precise orbit determination / Guilhem Moreaux in Advances in space research, vol 63 n° 1 (1 January 2019)PermalinkPermalinkReal-time capturing of seismic waveforms using high-rate BDS, GPS and GLONASS observations: the 2017 Mw 6.5 Jiuzhaigou earthquake in China / Xingxing Li in GPS solutions, vol 23 n° 1 (January 2019)PermalinkPermalinkAnalyzing the effect of earthquakes on OpenStreetMap contribution patterns and tweeting activities / Ahmed Ahmouda in Geo-spatial Information Science, vol 21 n° 3 (October 2018)PermalinkDoes long-term GPS in the Western Alps finally confirm earthquake mechanisms? / Andrea Walpersdorf in Tectonics, vol 37 n° 10 (October 2018)PermalinkThe 2015 Mw 6.4 Pishan earthquake, China: geodetic modelling inferred from Sentinel-1A TOPS interferometry / Yongsheng Li in Survey review, vol 50 n° 363 (September 2018)PermalinkWestern Pyrenees geodetic deformation study using the Guipuzcoa GNSS network / Adriana Martin in Journal of applied geodesy, vol 12 n° 3 (July 2018)PermalinkMigrating pattern of deformation prior to the Tohoku-Oki earthquake revealed by GRACE data / Isabelle Panet in Nature geoscience, vol 11 n° 5 (May 2018)PermalinkActive tectonics of the onshore Hengchun Fault using UAS DSM combined with ALOS PS-InSAR time series (Southern Taiwan) / Benoit Deffontaines in Natural Hazards and Earth System Sciences, vol 18 n° 3 ([01/03/2018])PermalinkDéformation saisonnière de la Terre : observations, modélisations et implications / Kristel Chanard (2018)PermalinkSurveillance des déformations des volcans avec des réseaux de Géocubes : expériences et leçons d’un déploiement sur l’Etna / Mohamed-Amjad Lasri (2018)PermalinkL'ITRF2014 et la modélisation des mouvements non linéaires des stations / Zuheir Altamimi in XYZ, n° 153 (décembre 2017 - février 2018)PermalinkCartographie de la vulnérabilité des bâtiments au risque sismique / Valerio Baiocchi in Géomatique expert, n° 119 (novembre - décembre 2017)PermalinkHydrologically-driven crustal stresses and seismicity in the New Madrid seismic zone / Timothy J. Craig in Nature communications, vol 8 (2017)PermalinkShallow geological structures triggered during the Mw 6.4 Meinong earthquake, southwestern Taiwan / Maryline Le Béon in Terrestrial Atmospheric Oceanic sciences journal, vol 28 n° 5 (October 2017)PermalinkPermalinkCrustal deformation caused by the 2016 Kumamoto earthquake revealed by GEONET / Satoshi Kawamoto in Bulletin of the GeoSpatial Information authority of Japan, vol 64 (December 2016)PermalinkDetection of ground surface deformation caused by the 2016 Kumamoto earthquake by InSAR using ALOS-2 data / Basara Miyahara in Bulletin of the GeoSpatial Information authority of Japan, vol 64 (December 2016)PermalinkGeological structures control on earthquake ruptures: The Mw7.7, 2013, Balochistan earthquake, Pakistan / A. Vallage in Geophysical research letters, vol 43 n° 19 (15 October 2016)PermalinkDisaster debris estimation using high-resolution polarimetric stereo-SAR / Christian N. Koyama in ISPRS Journal of photogrammetry and remote sensing, vol 120 (october 2016)PermalinkBimodal pattern of seismicity detected at the ocean margin of an Antarctic ice shelf / Denis Lombardi in Geophysical journal international, vol 206 n° 2 (August 2016)PermalinkA new computerized ionosphere tomography model using the mapping function and an application to the study of seismic-ionosphere disturbance / Jian Kong in Journal of geodesy, vol 90 n° 8 (August 2016)PermalinkSource model from ALOS-2 ScanSAR of the 2015 Nepal earthquakes / Youtian Liu in Journal of applied geodesy, vol 10 n° 2 (June 2016)PermalinkMonitoring recovery after earthquakes through the integration of remote sensing, GIS, and ground observations: the case of L’Aquila (Italy) / Diana Contreras in Cartography and Geographic Information Science, Vol 43 n° 2 (April - May 2016)PermalinkLe GPS dévoile les liens entre les grands séismes de subduction au Chili / Emilie Klein in XYZ, n° 146 (mars - mai 2016)PermalinkSynchrosqueezing S-transform and its application in seismic spectral decomposition / Zhong-lai Huang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)PermalinkApport de la géodésie française fond de mer à l'évaluation de l'aléa sismique côtier : distancemétrie en mer de Marmara et simulation de GNSS/A aux Antilles / Pierre Sakic-Kieffer (2016)PermalinkDéveloppement d’applications Android en réalité augmentée pour atténuer les risques liés aux séismes / Hugo Baltz (2016)PermalinkEffectiveness of observation-domain sidereal filtering for GPS precise point positioning / Christopher Atkins in GPS solutions, vol 20 n° 1 (January 2016)Permalink