Continuous Global Navigation Satellite System Research Articles

The seismic hazard from the Lembang Fault, Indonesia, derived from InSAR and GNSS data

Abstract. A growing number of large cities are located near poorly understood faults that have not generated a significant earthquake in recent history. The Lembang Fault is one such fault located near the city of Bandung in West Java, Indonesia. The slip rate on this fault is debated, with estimates ranging from 6 to 1.95–3.45 mm yr−1, derived from a GNSS (global navigation satellite system) campaign and geological measurements respectively. In this paper we measure the surface deformation across the Bandung region and resolve the slip rate across the Lembang Fault using radar interferometry (InSAR – interferometric synthetic aperture radar) analysis of 6 years of Sentinel-1 satellite data and continuous GNSS measurements across the fault. Our slip rate estimate for the fault is 4.7 mm yr−1, with the shallow portions of the fault creeping at 2.2 mm yr−1. Previous studies estimated the return period of large earthquakes on the fault to be between 170–670 years. Assuming simplified fault geometries and a reasonable estimate of the seismogenic depth we derive an estimated moment deficit equivalent to magnitude 6.6–7.0 earthquakes, indicating that the fault poses a very real hazard to the local population. Using the Global Earthquake Model OpenQuake engine we calculate ground motions for these two earthquake scenarios and estimate that 1.9–2.7 million people within the Bandung metropolitan region would be exposed to ground shaking greater than 0.3 g. This study highlights the importance of identifying active faults, understanding their past activity, and measuring the current strain rates of smaller crustal active faults located near large cities in seismic zones.

GNSS-Constrained Rupture Kinematics of the 2022 Mw 6.7 Luding, China, Earthquake: Directivity Pulse during the Asymmetrical Bilateral Rupture

Abstract Impulse motion characterized by a large amplitude in the fault-normal direction can be observed at near-fault strong motion sites during strike-slip earthquakes. The large pulse, which always causes high intensity and stronger damage to structures close to faults, is usually attributed to the directivity effect of rupture propagating along strike and the proximity to the fault. We present an analysis of such a large directivity pulse captured by the near-fault high-rate Global Navigation Satellite System (GNSS) during the 2022 Mw 6.7 Luding, China, earthquake—the largest event ever observed by space geodesy on the seismically active Xianshuihe fault in the eastern Tibetan Plateau. We invert the displacement waveforms and offsets derived from the continuous and campaign GNSS for the rupture kinematics. The inferred slip model reveals a rupture zone of 30 km in length above 15 km depth along the Moxi segment, yielding a seismic moment of 1.1×1019 N·m and a source duration of 13 s. The high-rate GNSS (hrGNSS) waveforms suggest an asymmetric bilateral rupture: most slips with long rise time are concentrated on the southern part of the ruptured fault, whereas a short-duration pulse-like slip rate with low final slip propagates during the northward rupture. We found that the directivity pulse observed by the nearest hrGNSS site is controlled primarily by the sharp pulse-like slip rate and rapid rupture velocity approximating the local S-wave velocity. Along with additional local amplification, this large directivity pulse may be responsible for the heavy damage in Moxi town close to the northern ruptured fault.

Detecting outliers in GNSS position time series using machine learning techniques

The Global Navigation Satellite System (GNSS) position time series is applied in studies that require high-precision positioning, such as monitoring tectonic movements and Earth deformation. Outliers in GNSS position time series can significantly impact the accuracy of station positioning and movement parameters, leading to distorted data analysis outcomes. This study investigates the effectiveness of three machine learning techniques, including-Isolation Forest, One-Class Support Vector Machines (O-C SVM), and Local Outlier Factor (LOF) for outlier detection in GNSS position time series, with a specific focus on the SYNT model where outliers account for a substantial proportion (15%). Through comprehensive analysis, our results highlight the exceptional performance of the Isolation Forest method. It demonstrates remarkable accuracy in identifying outliers, effectively detecting the majority of them, and achieving an area under the ROC curve close to 1. In contrast, the LOF method performs less effectively in outlier detection, while the O-C SVM method displays relatively higher accuracy in identifying normal data points. These findings emphasize the significant advantages of leveraging machine learning approaches in processing continuous GNSS measurement data. By effectively identifying and handling outliers, these techniques enhance the accuracy and reliability of data analysis in GNSS position time series, ultimately establishing their superiority in the field of data analysis.

The Flow of the Yangtze River Inverted From a Continuous Global Navigation Satellite System Station

AbstractThe runoff change in a large river is significant for hydrological event monitoring, such as floods and droughts. In this paper, we attempt to invert the river flow change based on the surface displacements observed by the continuous global navigation satellite system (GNSS) stations in the Wuhan section of the Yangtze River (WYR). We establish a two‐dimensional model accounting for deformation from a line load in an elastic half‐space to estimate the annual water load change from the GNSS data. The results show that the inverted line load from the annual maximum displacement change observed by the GNSS is , which is in good agreement with the river load from the hydrological station. This paper demonstrates a low‐cost and practical method to river flow research in local areas, which is also a creative application for the GNSS.

Post-seismic deformation following the 2011 Mw9.0 Tohoku–Oki earthquake and its impact on Northeast Asia

SUMMARY The objective of this study was to examine co- and post-seismic deformation following the 2011 Mw9.0 Tohoku–Oki earthquake and its impact on Northeast Asia. Large-scale, long-term post-seismic deformation caused by the earthquake was extracted according to the continuous Global Navigation Satellite Systems (GNSS) observation data for Japan, South Korea, Northeast China and the Far East Russia. The present research adopted a 2-D viscoelastic model to simulate the observed large-scale seismic deformation, considering the subducting slab in the western Pacific. The duration of the after-slip in the northwest of the main rupture area was found to be greater than that in the south of the main rupture area (approximately 6 yr). The steady-state viscosity coefficient of the continental mantle was found to be 8 × 1018 Pa·s. Post-seismic deformation in Northeast Asia was primarily caused by viscoelastic relaxation of the mantle, and observations on the west side of the Tan-Lu fault were smaller than simulation, revealing the heterogeneity in viscosity structures in NE China.

Estimation of Height Changes of Continuous GNSS Stations in the Eastern Anatolia Region during the Seasonal Variation

Estimating the height component of Global Navigation Satellite System (GNSS) stations is widely known to be more challenging than estimating the horizontal position. In this study, we utilized height time series data from 37 continuous GNSS stations that were part of the Turkish RTK CORS Network called TUSAGA-Active (Turkish National Permanent GNSS Network Active). The data covered the period from 2014 to 2019, and the selection of stations focused on the Eastern Anatolia region of Turkey due to its topographic characteristics and the pronounced influence of seasonal changes, which facilitated the interpretation of the effects on the height component. The daily coordinates of the GNSS stations were derived using the GAMIT/GLOBK software solution. We identified statistically significant trends, periodic variations, and stochastic components associated with the stations by applying time series analysis to these daily coordinate values. As a result, the vertical velocities of the GNSS stations were determined, along with their corresponding standard deviations. Furthermore, examining the height components of the continuous GNSS stations revealed seasonal effects. We aimed to investigate the potential relationship between these height components and meteorological parameters. The study provides evidence of the interconnectedness between the height components of continuous GNSS stations and various meteorological parameters. Simple linear regression analysis and ARMA time series modeling were utilized to establish this relationship.

GNSS land subsidence observations along the northern coastline of Java, Indonesia

Land subsidence in cities along the northern coastline of Java has been at a worrying level. Monitoring efforts using geodetic data reveal that Jakarta, Pekalongan, Semarang, and Demak subside at least ~9x faster than the present-day rate of global sea level rise, which affects the cities’ future urban viability. In this study, we publish a time series of the precise 3D displacements observed by twenty continuous Global Navigation Satellite System (GNSS) stations between 2010 and 2021. These are the first open-to-the-public and rigorously processed GNSS datasets that are useful for accurately quantifying land subsidence in the densely populated sinking cities in Java. The data also provides a way to tie other geodetic observations, such as Interferometric Synthetic Aperture Radar (InSAR), to a global reference frame in an attempt to build worldwide observations of coastal land subsidence.

Crustal displacement in Vietnam using CORS data during 2018 - 2021

Continuously Operation Reference Stations (CORS) networks provide surveying, mapping, and positioning services and play a crucial role in determining crustal displacement. This study processed the continuous Global Navigation Satellite System (GNSS) data collected from 55 CORS stations in the TAST’s CORS in Vietnam to determine the crustal displacement in Vietnam from 2018 to 2021. The processing was performed using online Precise Point Positioning (PPP) services and the displacement model to estimate the velocity of the position time series. The result showed that the horizontal velocity field of all CORS stations is uniform in magnitude and direction, ranging from 25.3 to 42.6 mm/year with accuracy from ±0.1 to ±1.0 mm/year in the south-east direction in the International Terrestrial Reference Frame 2014 (ITRF2014). This study confirms the stability and accuracy of GNSS data from the TAST’s CORS network for crustal displacement analysis.

Long-term slow slip events with and without tremor activation in the Bungo Channel and Hyuganada, southwest Japan

Slow slip events (SSEs) lasting for approximately 1 year occur every 6–8 years around the Bungo Channel in the southwest Japan subduction zone. The slip time evolution of the latest Bungo Channel SSE that occurred in 2018–2019 has been studied; however, the detailed spatial and temporal relationship between the slip process and other nearby phenomena, such as tectonic tremors and SSEs, is not well understood. Moreover, the migration of such long-term SSEs from Hyuganada to Shikoku through the Bungo Channel has been suggested, but a slip process connecting the SSEs has not been observed. In this study, we utilized 21 continuous global navigation satellite system (GNSS) stations around the Bungo Channel and Hyuganada that have been installed by us since 2014 in addition to GNSS Earth Observation System (GEONET) stations to improve the spatial resolution of such interplate slip. Based on these data, we estimate the spatial and temporal slip evolutions of the major SSE in 2018–2019, which was accompanied by tremor activity in the deep episodic tremor and slip (ETS) zone, and a smaller SSE in 2015–2016 without tremor activity. We show that the slip area of the major SSE overlaps the ETS zone, whereas that of the smaller SSE does not. This strongly suggests that synchronized tremor activity with an SSE requires a slip close to or overlapping the ETS zone. We also show two distinct slip propagation paths from the Oita area during the 2018–2019 sequence: one is a southward propagation to the Miyazaki area, leading to an SSE around the Miyazaki Plain, and the other is an eastward propagation to an area close to Cape Ashizuri, where “invading slip” is proposed to propagate from the ETS zone to a shallower megathrust source area. These slip propagations may be two of fundamental slip modes that connect slow-slip patch-like areas around the Bungo Channel and Hyuganada.Graphic

A methodology for long-term offshore structural health monitoring using stand-alone GNSS: case study in the Gulf of Mexico

This article presents a robust methodology for long-term offshore structural health monitoring (SHM) using the Global Navigation Satellite Systems (GNSS). The methodology relies on recently developed regional reference frames and single-receiver phase-ambiguity-fixed Precise Point Positioning techniques. The stable Gulf of Mexico Reference Frame 2020 (GOM20) provides a robust and consistent reference system for long-term offshore SHM in the Gulf of Mexico (GOM). Continuous GNSS observations (DEV1, 2010–2020) on a fixed platform in the Eugene Island 330 oil field are used to illustrate the methodology. The platform was installed in 1982 in 82-m water about 130 km away from the Mississippi Delta coastline. The major monitoring items include horizontal movements, seafloor subsidence, structure submergence, and seasonal oscillations. The stand-alone GNSS monitoring achieves 3- to 4-mm root-mean-square accuracy in the horizontal direction and 7 mm in the vertical direction for daily positions in the GOM region. According to this study, the GNSS antenna (DEV1) has moved 6 cm toward the northeast with respect to GOM20 since 2010; the ongoing structure submergence rate in the Eugene Island 330 oil field area is approximately 15 mm/year, a combination of seafloor subsidence (12 mm/year) and sea-level rise (2.6 mm/year) with respect to GOM20. The submergence in the future 40 years (2021–2060) would be greater than 0.6 m, likely between 0.8 and 1.0 m, but is unlikely to exceed 1.3 m. The peak-to-trough amplitudes of the seasonal movements at the top of the platform are below 5 mm in all three directions, comparable with the seasonal movements recorded by onshore GNSS in the Louisiana coastal region. The methodology introduced in this article can be applied to SHM in other offshore regions where stable regional reference frames are available.

A post-correlation graphical way for continuous GNSS spoofing detection

Global navigation satellite system (GNSS) receivers are under the threat of spoofing attacks. The signal quality monitoring (SQM) technique is effective in monitoring the distorted auto-correlation function (ACF). However, it has limited detection effectiveness in detecting spoofing signals that are greatly overpowered and with significant code phase shifts. This paper introduces a new metric called ACF similarity to characterize the ACF distortion and power abnormality in the tracking loop based on image feature extraction techniques. The spoofing detection algorithm and the optimal threshold utilizing the generalized likelihood ratio test (GLRT) are further developed. The performance of the proposed detector has been verified by utilizing the Texas Spoofing Test Battery (TEXBAT) dataset and Monte Carlo simulation tests. Results show that with 1% false alarm rate, the proposed detector achieves a detection probability of 87% in the TEXBAT datasets and provides better detection sensitivity than the conventional SQM metrics.

A Cost-Effective GNSS Solution for Continuous Monitoring of Landslides

The development of low-cost dual-frequency global navigation satellite system (GNSS) receivers in recent years has enabled the use of these devices in numerous applications. In the monitoring of natural hazards, such as landslides, these devices can be considered suitable sensors. In this work, dual-frequency GNSS receivers and antennas were used for setting up near-real-time continuous low-cost GNSS monitoring systems (LGMSs) under field conditions. The SimpleRTK2B board, which integrates the u-blox ZED-F9P dual-frequency GNSS chip and the survey-calibrated GNSS antenna are the main components of the GNSS system. The LGMS was installed and tested for six months in the Laze landslide located in the northwestern part of Slovenia. A total of four GNSS systems were deployed, three of which were located in pillars in the landslide itself and one in a stable area. Open-source software was used to postprocess the acquired data, providing daily coordinates in static relative and precise point positioning (PPP) positioning modes. The results of six months of near-real-time monitoring showed that the Laze landslide was stable during this period, with only minor changes in the vertical component. The trend of decreasing ellipsoid height was evident at all stations, although it was in the range of a few millimeters. To validate the results in static relative positioning mode, the coordinate differences between low-cost and high-end geodetic GNSS instruments were estimated and found to be in the range of 5 mm or less, while the difference between horizontal and spatial positions was less than 7 mm for all stations. The same data were processed in PPP, vertical displacements were not detected as in the static relative positioning mode due to the lower accuracy of the method itself. Considering the six-month performance of a low-cost GNSS system under field conditions, it can be emphasized that these devices are capable of performing near real-time continuous monitoring of slow movements with high accuracy and decreased costs. In addition, an experimental test was performed to identify the size of detected displacements in real-time kinematic (RTK). Based on the achieved results, it was concluded that 20 mm spatial displacements are detectable with LGMSs in RTK considering only 15 s of observations.

Iceland Kinematics From InSAR

AbstractLarge‐scale ground deformation in Iceland is dominated by extensional plate‐boundary deformation, where the Mid‐Atlantic Ridge crosses the island, and by uplift due to glacial isostatic adjustment (GIA) from thinning and retreat of glaciers. While this deformation is mostly steady over multiple years, it is modulated by smaller‐scale transient deformation associated with, for example, earthquakes, volcanic unrest, and geothermal exploitation. Here, we combine countrywide Sentinel‐1 interferometric synthetic aperture radar (InSAR) data (from six tracks) from 2015 to 2021 with continuous Global Navigation Satellite System observations to produce time series of displacements across Iceland. The InSAR results were improved in a two‐step tropospheric mitigation procedure, using (a) global atmospheric models to reduce long‐wavelength and topography‐correlated tropospheric signals, and (b) modeling of the stochastic properties of the residual troposphere. Our results significantly improve upon earlier countrywide InSAR results, which were based on InSAR stacking, as we use more data, better data weighting, and advanced InSAR corrections to produce time series of ground displacements instead of just velocities. We fuse the three ascending and three descending track results to estimate maps of East and Up velocities, which clearly show the large‐scale extension and GIA deformation. Using revised plate‐spreading and GIA models, based on these new ground velocity maps, we remove the large‐scale and steady deformation from the InSAR time series and analyze the remaining transient deformations. Our results demonstrate the importance of (a) mitigating InSAR tropospheric signals over Iceland and of (b) solving for time series of deformation, not just velocities, as multiple transient deformation processes are present.

Geodetic evidence of land subsidence in Cirebon, Indonesia

The subsidence phenomena occur in numerous cities in Indonesia (Jakarta, Bandung, and Semarang) and have been observed over the last few decades using geodetic techniques such as interferometric synthetic aperture radar (InSAR) and the Global Navigation Satellite System (GNSS). Three variables are considered the leading causes of substantial subsidence in those cities: urban development, excessive groundwater removal, and geological context. Considering these considerations, we assess surface displacement in the surrounding area of Cirebon, Indonesia, which has similar background circumstances. We used 43 Sentinel-1A images covering from 2014 to 2021 and processed them using the small baseline subset (SBAS) method obtaining 78 interferograms for time series analysis. A weighted correction from two weather models was used to correct tropospheric errors. The results from the InSAR time series were compared with the continuous GNSS time series (2010–2021) processed using GAMIT/GLOBK GNSS processing softwares. Cirebon experienced a slow land subsidence rate with an average magnitude of -2.6 mm/yr. Furthermore, we underline that more significant subsidence rates were found in several locations. Conic-shaped subsidence with a diameter of around 1 km was observed in a highly inhabited area, with a maximum rate of up to -17 mm/yr near the cone’s center. We also found more prominent land subsidence along the coastline with magnitudes up to -25 mm/yr. Surface lowering with a magnitude of up to -32 mm/yr also affects power plant regions close to Cirebon city. Meanwhile, the fastest subsidence rate was observed over the salt evaporation field area of about -50 mm/yr. We attribute the natural and anthropogenic factors to causing the subsidence in this area.

Toward sustainable inland aquaculture: Coastal subsidence monitoring in Taiwan

Inland aquaculture is a major industry that provides fish to reduce the stress of oceans in supplying global protein consumption. Developed and developing nations house their inland aquaculture industries largely in coastal areas, where groundwater is pumped to supply the needed water in a non-sustainable way that leads to coastal land subsidence. This study shows a comprehensive picture of land subsidence in Pingtung, a coastal plain in southern Taiwan, where, after the gradual abandonment of rice cultivation, huge groundwater exploitation has occurred since the 1970s to feed inland aquaculture. Integrated interpretation of multidevice monitoring results has improved knowledge of land subsidence associated with land uses and groundwater pumping. Results indicate a maximum cumulative subsidence of 350 cm from 1972 to 2019 near the aquaculture-rich township of Linbian. Sub-surface displacement measurements using multilayer compaction wells identified the de-watered layers responsible for the land subsidence in four sinking-affected coastal areas, where different groundwater usage patterns lead to different patterns of aquifer-system compactions at varying depths. The use of SAR interferometry with high spatial resolution and frequent revisit times has made it possible to overcome the inherent limitations of ground-based measurement methodologies such as leveling, continuous global navigation satellite system, and multilayer compaction wells, which while very accurate do not allow for adequate monitoring of subsidence in the Pingtung coastland due to the high dynamics and spatial variability of the process. Based on the results of this study, several sustainable aquaculture-related actions are being implemented or have been proposed to reduce the risks of land subsidence, flooding, and salinization in Pingtung. These include the use of InSAR monitoring for conventional sensors to continuously and timely monitor land subsidence.

Investigation of the trade-off between the complexity of the accelerometer bias model and the state estimation accuracy in INS/GNSS integration

Abstract The integration of Inertial Navigation Systems and Global Navigation Satellite Systems (GNSS) represents the core navigation unit for mobile platforms in open sky environments. A realistic assessment of the accuracy of the navigation solution depends on the accurate modelling of inertial sensor errors. Sensor noise and biases contribute most to short-term navigation errors. For the latter, different models can be used, varying in complexity. This paper investigates how the use of two different models for the accelerometer bias affects the accuracy of the state estimate in an extended Kalman filter. For this purpose, the Allan variance technique is applied to a data sequence from a specific inertial sensor to identify and quantify the underlying noise processes. The estimated noise parameters are used to characterise a bias model for the accelerometers that in addition to the static bias model takes non-white noise processes of the inertial sensor under investigation into account. This detailed accelerometer bias model is compared to a classical modelling approach that only considers static biases. Both approaches are evaluated based on simulation studies for continuous and intermittent GNSS coverages. The results show no significant difference between the two modelling approaches in terms of horizontal position and attitude precision. Furthermore, the correctness of the accelerometer bias estimates is not significantly affected by the modelling approach. All in all, it can be concluded that a detailed bias model of the accelerometers does not outperform the classical modelling approach.

Improving the Wet Refractivity Estimation Using the Extremely Learning Machine (ELM) Technique

Constructing accurate models that provide information about water vapor content in the troposphere improves the reliability of numerical weather forecasts and the position accuracy of low-cost Global Navigation Satellite System (GNSS) receivers. However, developing models with high spatial-temporal resolution demands compact observational datasets in the regions of interest. Empirical models, such as the Global Pressure and Temperature 3 (GPT3w), have been constructed based on the monthly averaged outputs of numerical weather models. These models are based on the assimilation of existing measurements to provide estimations of atmospheric parameters. Therefore, their accuracy may be reduced over regions with a low resolution of radiosonde or continuous GNSS stations. By emerging and increasing the Low-Earth-Orbiting (LEO) satellites that measure atmospheric parameter profiles using the Radio Occultation (RO) technique, new opportunities have appeared to acquire high-resolution atmospheric observations at different altitudes. This study aims to apply these RO observations to improve the accuracy of the GPT3w model over Iran, which is sparse in terms of long-term GNSS and radiosonde measurements. The temperature, pressure, and water vapor pressure parameters from the GPT3w model have been used as the input layers of the Extremely Learning Machine (ELM) technique. The wet refractivity indices from the RO technique are considered target parameters in the output layer to train the ELM. The RO observations of 2007–2020 are applied for training, and those of 2020–2022 for evaluating the performance of the developed ELM. Our numerical results indicate that the developed ELM decreases the Root-Mean-Square Error (RMSE) values of the wet refractivity indices by about 17 percent, compared to the original GPT3w RMSE values. Additionally, the wet refractivity indices from ELM have revealed correlation coefficients of about 0.64, which is about 1.9 times those related to the original GPT3w model. The performance of ELM has also been examined by comparison with the data of six located radiosonde stations covering the year 2020. This comparison shows an improvement of about 14 percent in the average RMSE values of the estimated wet refractivity indices.

Integrating Qualitative and Quantitative Methods to Evaluate Performance of the Brazilian Network for Continuous Global Navigation Satellite System (GNSS) Monitoring (RBMC)

We discuss a qualitative analysis of the efficiency of the Brazilian Network for Continuous Global Navigation Satellite System Monitoring (RBMC) using the Complex Holographic Assessment of Paradoxical Problems method (CHAP²), whose premise is the organization of intersubjectivity facilitated by the use of visual representation of structured knowledge (conceptual mapping) to increase the degree of consciousness to manage the paradoxes resulting from the complexity of living systems. We also describe a quantitative evaluation using Data Envelopment Analysis (DEA) allowing a ranking in terms of efficiency for further assessment by a professional of the area. The outcome of this study would be useful for IBGE (Brazilian Institute of Geography and Statistics) managers to be aware, for instance, of the suppliers and manufacturers of equipment available (receiver and geodetic antenna, Internet connection and constant supply of electricity) in efficient and ineffective stations, to guide new acquisitions, among other applications.

Refining Rates of Active Crustal Deformation in the Upper Plate of Subduction Zones, Implied by Geological and Geodetic Data: The E-Dipping West Crati Fault, Southern Italy

We investigate crustal deformation within the upper plate of the Ionian Subduction Zone (ISZ) at different time scales by (i) refining geodetic rates of crustal extension from continuous Global Navigation Satellite System (GNSS) measurements and (ii) mapping sequence of Late Quaternary raised marine terraces tectonically deformed by the West Crati normal fault, in northern Calabria. This region experienced damaging earthquakes in 1184 (M 6.75) and 1854 (M 6.3), possibly on the E-dipping West Crati fault (WCF) which, however, is not unanimously considered to be a seismogenic source. We report geodetic measurements of extension and strain rates across the strike of the E-dipping WCF and throughout the northern Calabria obtained by using velocities from 18 permanent GNSS stations with a series length longer than 4.5 years. These results suggest that crustal extension may be seismically accommodated in this region by a few normal faults. Furthermore, by applying a synchronous correlation approach, we refine the chronology of understudied tectonically deformed palaeoshorelines mapped on the footwall and along the strike of the WCF, facilitating calculation of the associated fault-controlled uplift rates. Raised Late Quaternary palaeoshorelines are preserved on the footwall of the WCF indicating that “regional” uplift, likely related to the deformation associated either with the subduction or mantle upwelling processes, is affected by local footwall uplift. We show that GIS-based elevations of Late Quaternary palaeoshorelines, as well as temporally constant uplift rates, vary along the strike of the WCF, implying normal faulting activity through time. This suggests that (i) the fault slip rate governing seismic hazard has also been constant over the Late Quaternary, over multiple earthquake cycles, and (ii) our geodetically derived fault throw rate for the WCF is likely a more than reasonable value to be used over longer time scales for an improved seismic hazard assessment. Overall, we emphasize the importance of mapping crustal deformation within the upper plate above subduction zones to avoid unreliable interpretations relating to the mechanism controlling regional uplift.

Monitoring Megathrust-Earthquake-Cycle-Induced Relative Sea-Level Changes near Phuket, South Thailand, Using (Space) Geodetic Techniques

Temporal changes in vertical land motion (VLM) in and around Phuket Island in southern Thailand following the great 2004 Sumatra–Andaman megathrust earthquake have impacted the relative sea-level change estimates based on tide-gauge (TG) records. To better monitor the VLM, two new continuous global navigation satellite system (GNSS) stations have been installed in the past 5 years, situated on bedrock both near and at the Koh Taphao Noi Island TG in Phuket, which together with older global positioning system (GPS) data provides a clear insight in the VLM of Phuket Island from 1994 onward. In addition, satellite altimetry (SALT) data has been analyzed since 1992. The VLM (GPS) position and relative (TG) and absolute (SALT) sea-level change time series were successfully combined in pairs to validate each independent result (e.g., SALT − GNSS = TG): prior to the 2004 earthquake, the relative sea-level rise in Phuket was 1.0 ± 0.7 mm/yr, lower by 2.4 ± 0.2 mm/yr than the absolute sea-level rise caused by VLM. After the earthquake, nonlinear post-seismic subsidence has caused the VLM to drop by 10 cm in the past 17 years, resulting, by the end of 2020, in a relative sea-level rise by up to 16 cm. During the same period, other TG stations in south Thailand recorded similar sea-level increases. Combination with SALT further suggests that, prior to 2005, uplift (5.3 ± 1.4 mm/yr) of the coastal region of Ranong (north of Phuket) resulted in a relative sea-level fall, but since then, post-seismic-induced negative VLM may have significantly increased coastal erosion along the entire Andaman Sea coastline.