Real-time coseismic deformations from adaptively tight integration of high-rate GNSS and strong motion records

2019 ◽  
Vol 219 (3) ◽  
pp. 1757-1772 ◽  
Author(s):  
Jianfei Zang ◽  
Caijun Xu ◽  
Guanxu Chen ◽  
Qiang Wen ◽  
Shijie Fan

SUMMARY In traditional tight integration of high-rate GNSS and strong motion sensors, an appropriate process variance is crucial for obtaining accurate broad-band coseismic deformations. In this paper, instead of using a subjectively empirical value, we present an approach for determining the process variance adaptively based on the adaptive Kalman filter for real-time use. The performance of the approach was validated by the colocated stations collected during the 2010 Mw 7.2 earthquake in El-Mayor, 2016 Mw 7.8 earthquake in New Zealand and 2016 Mw 6.5 earthquake in central Italy. The results show that this method complements the advantages of GNSS and strong motion accelerometers and can provide more accurate coseismic waveforms especially during the strong shaking period, due to the ability of the method to adjust the process variance in real time according to the actual status of the station. In addition, this method is also free from the influence of the baseline shift. Testing of the new method for the integration of strong motion and multi-GNSS indicates that multi-GNSS has an obvious improvement in the precision while single GPS has a poor observation condition.

2018 ◽  
Vol 10 (8) ◽  
pp. 1201 ◽  
Author(s):  
Francesca Fratarcangeli ◽  
Giorgio Savastano ◽  
Maria D’Achille ◽  
Augusto Mazzoni ◽  
Mattia Crespi ◽  
...  

The goal of this article is the illustration of the new functionalities of the VADASE (Variometric Approach for Displacements Analysis Stand-alone Engine) processing approach. VADASE was presented in previous works as an approach able to estimate in real time the velocities and displacements in a global reference frame (ITRF), using high-rate (1 Hz or more) carrier phase observations and broadcast products (orbits, clocks) collected by a stand-alone GNSS receiver, achieving a displacements accuracy within 1–2 cm (usually better) over intervals up to a few minutes. It has been well known since the very first implementation and testing of VADASE that the estimated displacements might be impacted by two different effects: spurious spikes in the velocities due to outliers (consequently, displacements, obtained through velocities integration, are severely corrupted) and trends in the displacements time series, mainly due to broadcast orbit and clock errors. Two strategies are herein introduced, respectively based on Leave-One-Out cross-validation (VADASE-LOO) for a receiver autonomous outlier detection, and on a network augmentation strategy to filter common trends out (A-VADASE); they are combined (first, VADASE-LOO; second, A-VADASE) for a complete solution. Moreover, starting from this VADASE improved solution, an additional strategy is proposed to estimate in real time the overall coseismic displacement occurring at each GNSS receiver. New VADASE advances are successfully applied to the GPS data collected during the recent three strong earthquakes that occurred in Central Italy on 24 August and 26 and 30 October 2016, and the results are herein presented and discussed. The VADASE real-time estimated coseismic displacements are compared to the static ones derived from the daily solutions obtained within the standard post-processing procedure by the Istituto Nazionale di Geofisica e Vulcanologia.


2020 ◽  
Vol 110 (6) ◽  
pp. 2647-2660
Author(s):  
Nikolaj Dahmen ◽  
Roland Hohensinn ◽  
John Clinton

ABSTRACT The 2016 Mw 7.0 Kumamoto earthquake resulted in exceptional datasets of Global Navigation Satellite Systems (GNSS) and seismic data. We explore the spatial similarity of the signals and investigate procedures for combining collocated sensor data. GNSS enables the direct observation of the long-period ground displacements, limited by noise levels in regimes of millimeters to several centimeters. Strong-motion accelerometers are inertial sensors and therefore optimally resolve middle- to high-frequency strong ground motion. The double integration from acceleration to displacement amplifies long-period errors introduced by tilt, rotation, noise, and nonlinear instrument responses and can lead to large nonphysical drifts. For the case study of the Kumamoto earthquake, 39 GNSS stations (1  samples/s) with nearby located strong-motion accelerometers (100  samples/s) are investigated. The GNSS waveforms obtained by precise point positioning under real-time conditions prove to be very similar to the postprocessed result. Real-time GNSS and nearby located accelerometers show consistent observations for periods between ∼3–5 and ∼50–100  s. The matching frequency range is defined by the long-period noise of the accelerometer and the low signal-to-noise ratio (SNR) of GNSS, when it comes to small displacements close to its noise level. Current procedures in fusing the data with a Kalman filter are verified for the dataset of this event. Combined data result in a very broadband waveform that covers the optimal frequency range of each sensor. We explore how to integrate fused processing in a real-time network, including event detection and magnitude estimation. Carrying out a statistical test on the GNSS records allows us to identify seismic events and sort out stations with a low SNR, which would otherwise impair the quality of downstream products. The results of this study reinforce the emerging consensus that there is real benefit to collocation GNSS and strong-motion sensors for the monitoring of moderate-to-large earthquakes.


2019 ◽  
Vol 51 ◽  
pp. 1-14 ◽  
Author(s):  
Nicola Cenni ◽  
Jacopo Boaga ◽  
Filippo Casarin ◽  
Giancarlo De Marchi ◽  
Maria Rosa Valluzzi ◽  
...  

Abstract. Modern seismic ground-motion sensors have reached an excellent performance quality in terms of dynamic range and bandwidth resolution. The weakest point in the recording of seismic events remains spatial sampling and spatial resolution, due to the limited number of installed sensors. A significant improvement in spatial resolution can be achieved by the use of non-conventional motion sensors, such as low-cost distributed sensors arrays or positioning systems, capable of increasing the density of classical seismic recording networks. In this perspective, we adopted micro-electro mechanical system (MEMS) sensors to integrate the use of standard accelerometers for moderate-to-strong seismic events. In addition, we analyse high-rate distributed positioning system data that also record soil motion. In this paper, we present data from the 2016 Central Italy earthquakes as recorded by a spatially dense prototype MEMS array installed in the proximity of the epicentral area, and we compare the results to the signal of local 1s GPS stations. We discuss advantages and limitations of this joint approach, reaching the conclusion that such low-cost sensors and the use of high rate GPS signal could be an effective choice for integrate the spatial density of stations providing strong-motion parameters.


2021 ◽  
Author(s):  
Emilied Klein ◽  
Bertrand Potin ◽  
Francisco Pasten-Araya ◽  
Roxane Tissandier ◽  
Kellen Azua ◽  
...  

An earthquake sequence occurred in the Atacama region of Chile throughout September 2020. The sequence initiated by a mainshock of magnitude Mw6.9, followed 17 hours later by a Mw6.4 aftershock. The sequence lasted several weeks, during which more than a thousand events larger than Ml 1 occurred, including several larger earthquakes of magnitudes between 5.5 and 6.4. Using a dense network that includes broad-band, strong motion and GPS sites, we study in details the seismic sources of the mainshock and its largest aftershock, the afterslip they generate and their aftershock, shedding light of the spatial temporal evolution of seismic and aseismic slip during the sequence. Dynamic inversions show that the two largest earthquakes are located on the subduction interface and have a stress drop and rupture times which are characteristics of subduction earthquakes. The mainshock and the aftershocks, localised in a 3D velocity model, occur in a narrow region of interseismic coupling (ranging 40%-80%), i.e. between two large highly coupled areas, North and South of the sequence, both ruptured by the great Mw~8.5 1922 megathrust earthquake. High rate GPS data (1 Hz) allow to determine instantaneous coseismic displacements and to infer coseismic slip models, not contaminated by early afterslip. We find that the total slip over 24 hours inferred from precise daily solutions is larger than the sum of the two instantaneous coseismic slip models. Differencing the two models indicates that rapid aseismic slip developed up-dip the mainshock rupture area and down-dip of the largest aftershock. During the 17 hours separating the two earthquakes, micro-seismicity migrated from the mainshock rupture area up-dip towards the epicenter of the Mw6.4 aftershocks and continued to propagate upwards at ~0.7 km/day. The bulk of the afterslip is located up-dip the mainshock and down-dip the largest aftershock, and is accompanied with the migration of seismicity, from the mainshock rupture to the aftershock area, suggesting that this aseismic slip triggered the Mw6.4 aftershock. Unusually large post-seismic slip, equivalent to Mw6.8 developed during three weeks to the North, in low coupling areas located both up-dip and downdip the narrow strip of higher coupling, and possibly connecting to the area of the deep Slow Sleep Event detected in the Copiapo area in 2014. The sequence highlights how seismic and aseismic slip interacted and witness short scale lateral variations of friction properties at the megathrust.


2016 ◽  
Vol 59 ◽  
Author(s):  
Antonio Avallone ◽  
Diana Latorre ◽  
Enrico Serpelloni ◽  
Adriano Cavaliere ◽  
André Herrero ◽  
...  

<p>We used High-Rate sampling Global Positioning System (HRGPS) data from 52 permanent stations to retrieve the coseismic dynamic displacements related to the 2016 August 24 <em>M<sub>w</sub></em> 6.0 Amatrice earthquake. The HRGPS position time series (named hereinafter "GPSgrams") were obtained with two different analysis strategies of the raw GPS measurements (Precise Point Positioning [PPP] and Double-Difference [DD] positioning approaches using the Gipsy-Oasis II and the TRACK (GAMIT/GLOBK) software, respectively). These GPSgrams show RMS accuracies mostly within 0.3 cm and, for each site, an agreement within 0.5 cm between the two solutions. By using cross-correlation technique, the GPSgrams are also compared to the doubly-integrated strong motion data at sites where the different instrumentations are co-located in order to recognize in the GPSgrams the seismic waves movements. The high values (mostly greater than 0.6) of the cross-correlation functions between these differently-generated waveforms (GPSgrams and the SM displacement time-histories) at the co-located sites confirm the ability of GPS in providing reliable waveforms for seismological applications.</p>


Author(s):  
Giuseppe Placidi ◽  
Danilo Avola ◽  
Luigi Cinque ◽  
Matteo Polsinelli ◽  
Eleni Theodoridou ◽  
...  

AbstractVirtual Glove (VG) is a low-cost computer vision system that utilizes two orthogonal LEAP motion sensors to provide detailed 4D hand tracking in real–time. VG can find many applications in the field of human-system interaction, such as remote control of machines or tele-rehabilitation. An innovative and efficient data-integration strategy, based on the velocity calculation, for selecting data from one of the LEAPs at each time, is proposed for VG. The position of each joint of the hand model, when obscured to a LEAP, is guessed and tends to flicker. Since VG uses two LEAP sensors, two spatial representations are available each moment for each joint: the method consists of the selection of the one with the lower velocity at each time instant. Choosing the smoother trajectory leads to VG stabilization and precision optimization, reduces occlusions (parts of the hand or handling objects obscuring other hand parts) and/or, when both sensors are seeing the same joint, reduces the number of outliers produced by hardware instabilities. The strategy is experimentally evaluated, in terms of reduction of outliers with respect to a previously used data selection strategy on VG, and results are reported and discussed. In the future, an objective test set has to be imagined, designed, and realized, also with the help of an external precise positioning equipment, to allow also quantitative and objective evaluation of the gain in precision and, maybe, of the intrinsic limitations of the proposed strategy. Moreover, advanced Artificial Intelligence-based (AI-based) real-time data integration strategies, specific for VG, will be designed and tested on the resulting dataset.


Author(s):  
D Spallarossa ◽  
M Cattaneo ◽  
D Scafidi ◽  
M Michele ◽  
L Chiaraluce ◽  
...  

Summary The 2016–17 central Italy earthquake sequence began with the first mainshock near the town of Amatrice on August 24 (MW 6.0), and was followed by two subsequent large events near Visso on October 26 (MW 5.9) and Norcia on October 30 (MW 6.5), plus a cluster of 4 events with MW &gt; 5.0 within few hours on January 18, 2017. The affected area had been monitored before the sequence started by the permanent Italian National Seismic Network (RSNC), and was enhanced during the sequence by temporary stations deployed by the National Institute of Geophysics and Volcanology and the British Geological Survey. By the middle of September, there was a dense network of 155 stations, with a mean separation in the epicentral area of 6–10 km, comparable to the most likely earthquake depth range in the region. This network configuration was kept stable for an entire year, producing 2.5 TB of continuous waveform recordings. Here we describe how this data was used to develop a large and comprehensive earthquake catalogue using the Complete Automatic Seismic Processor (CASP) procedure. This procedure detected more than 450,000 events in the year following the first mainshock, and determined their phase arrival times through an advanced picker engine (RSNI-Picker2), producing a set of about 7 million P- and 10 million S-wave arrival times. These were then used to locate the events using a non-linear location (NLL) algorithm, a 1D velocity model calibrated for the area, and station corrections and then to compute their local magnitudes (ML). The procedure was validated by comparison of the derived data for phase picks and earthquake parameters with a handpicked reference catalogue (hereinafter referred to as ‘RefCat’). The automated procedure takes less than 12 hours on an Intel Core-i7 workstation to analyse the primary waveform data and to detect and locate 3000 events on the most seismically active day of the sequence. This proves the concept that the CASP algorithm can provide effectively real-time data for input into daily operational earthquake forecasts, The results show that there have been significant improvements compared to RefCat obtained in the same period using manual phase picks. The number of detected and located events is higher (from 84,401 to 450,000), the magnitude of completeness is lower (from ML 1.4 to 0.6), and also the number of phase picks is greater with an average number of 72 picked arrival for a ML = 1.4 compared with 30 phases for RefCat using manual phase picking. These propagate into formal uncertainties of ± 0.9km in epicentral location and ± 1.5km in depth for the enhanced catalogue for the vast majority of the events. Together, these provide a significant improvement in the resolution of fine structures such as local planar structures and clusters, in particular the identification of shallow events occurring in parts of the crust previously thought to be inactive. The lower completeness magnitude provides a rich data set for development and testing of analysis techniques of seismic sequences evolution, including real-time, operational monitoring of b-value, time-dependent hazard evaluation and aftershock forecasting.


2007 ◽  
Vol 7 (2) ◽  
pp. 2-16 ◽  
Author(s):  
Hiroyuki FUJIWARA ◽  
Takashi KUNUGI ◽  
Shigeki ADACHI ◽  
Shin AOI ◽  
Nobuyuki MORIKAWA

Sign in / Sign up

Export Citation Format

Share Document