Continuous GPS Research Articles

3D Surface Velocity Field Inferred from SAR Interferometry: Cerro Prieto Step-Over, Mexico, Case Study

The Cerro Prieto basin, a tectonically active pull-apart basin, hosts significant geothermal resources currently being exploited in the Cerro Prieto Geothermal Field (CPGF). Consequently, natural tectonic processes and anthropogenic activities contribute to three-dimensional surface displacements in this pull-apart basin. Here, we obtained the Cerro Prieto Step-Over 3D surface velocity field (3DSVF) by accomplishing a weighted least square algorithm inversion from geometrically quasi-orthogonal airborne UAVSAR and RADARSAT-2, Sentinel 1A satellite Synthetic Aperture-Radar (SAR) imagery collected from 2012 to 2016. The 3DSVF results show a vertical rate of 150 mm/yr and 40 mm/yr for the horizontal rate, where for the first time, the north component displacement is achieved by using only the Interferometric SAR time series in the CPGF. Data integration and validation between the 3DSVF and ground-based measurements such as continuous GPS time series and precise leveling data were achieved. Correlating the findings with recent geothermal energy production revealed a subsidence rate slowdown that aligns with the CPGF’s annual vapor production.

Exploration of crustal deformation and tectonic interactions in Mexico based on continuous GPS data

Exploration of crustal deformation and tectonic interactions in Mexico based on continuous GPS data

Continuous GPS PPP-AR frequency transfer links

Abstract In this paper, we show that the SPARK software of the Natural Resources Canada (NRCan) with their DCR (Decoupled Clock Rapid) products can be used to generate the PPP-AR continuous batch clock solutions of multiple days, which we use to build frequency transfer links between two remotely located GPS receivers. The reliability and confidence in forming the long-term frequency transfer links have been improved compared to reference~\cite{jian2023gps}. We compare the SPARK PPP-AR links to an optical fiber and TWSTFT links for hundreds of days. The ∽500-day-long comparisons with TWSTFT show no frequency bias for continental and cross-continental links. Frequency transfer links formed using the SPARK solutions have uncertainty of 1×10-15/T, where T is in days, without reaching the noise floor, a critical requirement for comparing optical frequency standards and for the redefinition of the SI second. The short latency of the NRCan DCR products enables the quick availability of the PPP-AR links presented in this paper marking it particularly relevant for time sensitive applications.

Early postseismic slip of the 21 November 2022 Mw 5.6 Cianjur, Indonesia, earthquake based on GPS measurements

ABSTRACT Global Positioning System (GPS) data after the 21 November 2022 Mw 5.6 Cianjur earthquake are crucial for understanding the physical processes during the postseismic phase. New continuous GPS stations were installed and recorded data for periods ranging from five to twenty-five days after the mainshock. The daily time series data at GPS stations shows an evolving logarithmic decay over time, as expected due to frictional afterslip. We inverted the postseismic displacement data to solve the postseismic slip distribution, utilising Akaike’s Bayesian information criterion. A cumulative aseismic slip moment of 1.54 × 1016 N·m, equivalent to Mw 4.7, is modelled during the period from five to twenty-five days after the mainshock. This aseismic slip moment is equivalent to approximately 7% of the seismic moment during the mainshock. Our analysis on the newly identified active fault using GPS displacements highlights the imperative need to identify active faults prior to future earthquake occurrences, especially when conducting hazard mitigation in populated regions in Indonesia.

Slip Rate for the Rose Canyon Fault through San Diego, California, Based on Analysis of GPS Data: Evidence for a Potential Rose Canyon–San Miguel-Vallecitos Fault Connection?

ABSTRACT The Rose Canyon fault is the southern extension of the larger Newport–Inglewood–Rose Canyon fault system, which represents a major structural boundary in the Inner Continental Borderland (ICB) offshore of southern California. Ten to fifteen percent of total plate boundary motion in southern California is thought to be accommodated by the faults of the ICB, but the exact distribution of slip is uncertain. With an onshore segment, the Rose Canyon fault offers an opportunity to measure the slip rate using traditional geodetic methods. In this study, we use Global Positioning System (GPS) surface velocities from a combined campaign and continuous GPS network to constrain elastic models of the Rose Canyon fault. We then compare the observed surface velocities with proposed conceptual models of regional fault connections that facilitate the transfer of slip into the Rose Canyon fault to assess how well the observations are explained by the models. The results of elastic half-space models suggest that the Rose Canyon fault may be slipping toward the higher end of geologic estimates, with the preferred model indicating a slip rate of 2.4 ± 0.5 mm/yr. Although limited in terms of near-fault benchmarks, we find an improved model fit using an asymmetrical elastic half-space model and a higher slip rate, suggesting a potential rheological contrast across the Rose Canyon fault, similar to observations from the northern Newport–Inglewood fault segments. Observed GPS surface velocities, background seismicity, and gravity anomalies south of San Diego Bay point toward a more easterly trace for the Rose Canyon fault, suggesting a possible connection with the San Miguel–Vallecitos fault system. Such a connection could increase the potential rupture lengths of future earthquakes and have important consequences for regional seismic hazards.

Fault system dynamics of the Kashmir, NW Himalaya, India using continuous GPS observations and geomorphic evidences

We collected data from the continuous Global Positioning System (cGPS) sites across the Kashmir Valley, situated at latitude 34◦N, spanning from 2008 to 2021. Inter-site velocities define a region of approximately 15,000 km2 with broadly distributed strain accumulation at −7.22×10−8 nano strain/year (compression component) and the maximum shear strain γmax of 1.9051×10−7 nano strain/year. The estimated site velocity in the ITRF14 ranges between 30.5±1–42.85±3 mm/yr. It was observed that the average deformation rate of the GPS sites in the Kashmir region ranges between 2.86±1–15.47±3 mm/yr relative to the India fixed reference frame, suggesting a predominant N-S directed compressional tectonic regime. The focal mechanism solutions of the earthquakes in and around the Kashmir Valley suggest dominant thrust faulting followed by normal faulting. Analysis of the vertical component of the GPS time series shows that the northwest segment of the valley subsides at the rate of −1.71± 0.70 mm/yr, while the southeast segment uplifts at the rate of 5.4 ± 0.5 mm/yr. In addition to vertical component, we observed differential movement of the sites relative to IISC site on the northwest and southeast segments. The rate of baseline change of the GPS sites indicates 7.30 ± 0.75 mm/yr extension in SE-NW direction and −5.32 ± 0.75 mm/yr NE-SW compression across and along the Kashmir Valley. Geodetic observations reveal a transition that aligns with the Magam lineament/fault previously identified by Ganju and Khar (1984) using gravity and magnetic data. The observation was supported by the field investigations and remote sensing techniques, confirming the existence of Magam Fault. During the field investigations, various geomorphic expressions of fault were observed, including fault ruptures, fault scarps, offset ridges, deflected drainages/rivers, linear alignment of springs, linear drainage lines, triangular facets and offset Recent sedimentary deposits (Karewas) were observed. The field evidence suggests exposure of normal faults at Kondabal, Nasrullapora, Biru and Radbugh. These exposed extensional structures, trends in NE-SW direction and dip in NW direction with varying offset and dip amount. GPS observations supplemented by geomorphic evidences infer the presence of normal fault ̴ 80 Km extending from northeast to southwest.

High Spatial Resolution in Total Water Storage Variations Inferred From GPS: Case Study in the Great Lakes Watershed, US

AbstractAssessing spatiotemporal water storage variability in the Great Lakes Watershed (GLW) is critical given its transboundary status impacting both Canada and the United States. Here, we apply a novel inversion strategy to global positioning system (GPS) vertical movements to achieve high spatial resolution total water storage (TWS) variations in GLW through improved processing. The steps are composed of removing load changes driven by the lake water fluctuation by forward modeling, isolating the Great Lakes grids to solve the ill‐conditioned problem in inversion, and inverting the GPS residual series to estimate TWS variations on land (TWSGPS). The results show that the regional dense continuous GPS observation network can successfully resolve TWS on land at monthly timescales with 30–45 km spatial resolution. We also could effectively capture fine‐scale TWS features than GRACE/GFO mascon products. GRACE/GFO satellites largely underestimate seasonal and long‐term TWS spatial fluctuations, but their temporal patterns coincide with those from GPS. The average annual amplitude of TWSGPS on land reaches 82.0 mm, greatly exceeding estimates from GRACE/GFO (∼48.0 mm) and composite hydrological model outputs (∼62.0 mm). The seasonal groundwater fluctuations inferred from GPS have peak‐to‐peak amplitudes of ∼40 km3 with the maximum around September. This coincides with that from GRACE/GFO. However, the magnitudes and phases of groundwater storage from GPS vary markedly among the subbasins in GLW, and the different snow and soil moisture amounts measured in each subbasin cause discrepancies among these GPS estimates. This study shows the value of GPS data in spatially downscaling GRACE/GFO data and providing high‐resolution output at spatiotemporal scales with low latency.

Non‐Linear Vertical Land Motion of Coastal Chile and the Antarctic Peninsula Inferred From Combining Satellite Altimetry, Tide Gauge and GPS Data

AbstractWe developed an enhanced Kalman‐based approach to quantify abrupt changes and significant non‐linearity in vertical land motion (VLM) along the coast of Chile and the Antarctic Peninsula using a combination of multi‐mission satellite altimetry (ALT), tide gauge (TG), and GPS data starting from the early 1990s. The data reveal the spatial variability of co‐seismic and post‐seismic subsidence at TGs along the Chilean subduction zone in response to the Mw8.8 Maule 2010, Mw8.1 Iquique 2014, and Mw8.3 Illapel 2015 earthquakes that are not retrievable from the interpolation of sparse GPS observations across space and time. In the Antarctic Peninsula, where continuous GPS data do not commence until ∼1998, the approach provides new insight into the ∼2002 change in VLM at the TGs of +5.3 ± 2.2 mm/yr (Palmer) and +3.5 ± 2.8 mm/yr (Vernadsky) due to the onset of ice‐mass loss following the Larsen‐B Ice Shelf breakup. We used these data to constrain viscoelastic Earth model parameters for the northern Antarctic Peninsula, obtaining a preferred lithosphere thickness of 115 km and upper mantle viscosity of 0.9 × 1018 Pa s. Our estimates of regionally‐correlated ALT systematic errors are small, typically between ∼±0.5–2.5 mm/yr over single‐mission time scales. These are consistent with competing orbit differences and the relative errors apparent in ALT crossovers. This study demonstrates that, with careful tuning, the ALT‐TG technique can provide improved temporal and spatial sampling of VLM, yielding new constraints on geodynamic models and assisting sea‐level change studies in otherwise data sparse regions and periods.

Declining magma supply to a poroelastic magma mush explains long-term deformation at Soufrière Hills Volcano

Volcano deformation studies traditionally consider melt-dominated magma reservoirs, often overlooking the significant role of poroelastic mush in modifying surface deformation. Here, we analyze the deformation of Soufrière Hills Volcano (SHV) with a focus on a mush-dominated, poroelastic magma reservoir, drawing on temporal deformation data from 14 continuous GPS stations during the ongoing intra-eruptive unrest period. We implemented a 3D Finite Element model and optimization to simulate the observed deformation. Our results reveal that the deformation is likely driven by ongoing, melt injection (Q = 1.1 m³ sec⁻¹) into a low permeability (k = 4.7 × 10⁻¹⁰ m²) reservoir with the injection to the base of the reservoir at 16.5 km depth below sea level. Our findings highlight temporal variations in the melt injection rate to fit the decreasing GPS-recorded deformation rates. An initial injection rate Qi = 1.9 m³ sec⁻¹ inferred at the start of our study period decreases to Qf = 0.3 m³ sec⁻¹ over a 12-year period (2010–2022). Exploratory forward modeling suggests that if current trends continue, the end of magma supply to our modelled reservoir could occur around June 2024 ± 2 years. However, this does not imply the end of associated volcanic hazards at SHV, as the poroelastic diffusion of melt will continue, causing redistribution of melt, surface deformation, and potentially initiating reservoir rupture. While our models offer new insights, inherent limitations in our simulations include interdependencies among our explored model parameters that would benefit from further refinement. Despite these limitations, the study offers crucial guidance on understanding and forecasting volcano deformation dynamics, particularly for volcanoes like SHV with crystal-rich magma reservoirs.

DEFORMATION INTERACTION OF STRONG EARTHQUAKES OF 2010–2016 IN THE ZONE OF INFLUENCE OF THE HIKURANGA SUPERPLUME (NEW ZEALAND) ACCORDING TO GPS OBSERVATIONS

Between 2010 and 2016, a series of 11 strong M>6 earthquakes occurred in New Zealand. In the area covering the epicentral zones of these seismic events, the spatiotemporal characteristics of movements and deformations of the Earth’s crust were obtained based on the processing of continuous satellite GPS observations at 64 points of the geodetic network. Using these data, we have studied the evolution of horizontal movements and deformations in order to reveal the possible relationship between the observed deformational and seismic processes. Analysis has been made on the total shear deformation, since the main tectonic structures of the region are faults with a shear mechanism of displacement of their sides. The presence of a giant mantle superplume in the area was the reason for the study of the behavior of horizontal dilatation deformation, and horizontal and vertical crustal motions. Based on the obtained digital deformation models, there were created kinematic visualizations, which are synoptic animations providing direct observations of the seismic deformation process and their heuristic analysis. The study revealed that a series of the strongest earthquakes may be interconnected by a long-term single deformation process, which is caused by the occurrence of an anomalous total shear deformation. The general maximum of shear deformation, dilatation deformation, and horizontal and vertical displacements are concentrated in the center of mantle superplume activity. Prior to strong seismic events, there occur zones of deficit (minimum) displacements of the Earth’s crust in the area of future epicenters, which is of research interest in terms of predicting their locations.

Machine learning assisted crustal velocity proxy: A case study over the Tibetan Plateau and its surroundings

So far only a few individuals have attempted to use Machine Learning approaches to anticipate GPS site velocity for crustal deformation research. Generally, a dense network of Continuously Operating Reference Station (CORS) is employed to monitor crustal deformation continuously. Campaign-mode GPS surveys are often used to densify the existing CORS network. Even sometimes, it is very challenging to establish a station in the location of our interest due to logistical problems and regional geographical considerations. However, this process is expensive, and crustal movement studies are eventually hampered by data missing issues owing to logistical restrictions. Thus, to obtain velocity vectors at the desired locations, we implemented machine learning (ML) techniques, such as support vector machines, decision trees and Gaussian processing regression, to accomplish the crustal movement precisely. We inspected data from 1271 permanent continuous and campaign-mode GPS stations, located on the Tibetan plateau and its environs. This study demonstrates the effectiveness of these ML techniques in forecasting velocity vectors (easting velocity (VE) and northing velocity (VN)) and enhancing plate movement characterisation. The correlation coefficient between (CR > 0.98 at training and CR > 0.96 at test phase) predicted and actual velocity vectors are satisfactory, making these ML predictive models considerably reliable for estimating geodetic velocity vectors. This ML algorithm demonstrates a remarkable achievement in the field of geodetic study in a cost-effective manner.

Показатель пожарной опасности для лесной среды с использованием метеорологических и GPS-данных на территории Забайкальского национального парка

The main indicators of potential fire hazards are temperature, relative humidity, precipitation, and wind speed readings. Prompt detection of fire risk should be an integral part of forest protection systems. For this purpose, it is essential to use automatic instruments based on comprehensive meteorological observations. In recent years, most forest fires in the Republic of Buryatia have started due to natural rather than anthropogenic causes. To assess the risk of forest fire based on current weather conditions, the Nesterov index is used. Continuous GPS measurements, combined with highprecision geodetic techniques, allow us to regularly obtain data on tropospheric signal delays, which provide information about the total water vapor content in the atmosphere (IWV). The possibility of using the IWV values obtained to assess the fire risk of forest areas is demonstrated, taking into account data from the Ust-Barguzin weather station located on the territory of the Trans-Baikal National Park. Creating an online resource based on Nesterov's complex indicator using GPS measurements and meteorological data would allow for real-time monitoring of fire risk in forests.

Geodetic constraints on slip rate on the Karakoram fault and its role in the Himalayan arc deformation

The evolution of the >1000 km long Karakoram fault along the southwestern margin of the Tibetan plateau and its role in Himalayan arc deformation is debated extensively. We report new results of continuous GPS measurements along a >300 km length of the Karakoram fault and suggest that the fault in the Nubra valley (K2 segment of the northern Karakoram fault) is inactive while that in the Bangong Chaxikang region (the southern Karakoram fault), slips at a rate of 1.6–3.2 mm/year. The low slip rate on the southern segment and no slip on the northern segment of the Karakoram fault support the model in which the Karakoram fault is considered a transient feature (and not a lithospheric scale fault) in the Himalayan arc deformation, that acted as transfer structure linking thrusts in the Pamir and western Tibet. Once the Longmu Co Gozha Co fault system (a part of the Altyn Tagh fault) developed in the late Pliocene and impinged on the Karakoram fault, the northern segment of the Karakoram fault became inactive. Further, our modelling of GPS measurements indicates a locking depth of ∼12–15 km for the southern Karakoram fault. Although, because of low fault slip and uncertainty in the measurements it is not well constrained, the lack of historical and instrumental earthquakes of large magnitude implies that the southern part of the Karakoram fault has been accumulating deformation for several centuries, probably confirms that the southern Karakoram fault has been accumulating strain for several centuries.

Current deformation in eastern part of Java derived from GPS observation 2017-2022

The eastern part of Java Island is a prone area with high seismic potential. Geologically, the seismicity in this area is dominated by the subduction zone in southern Java, reverse faults structure in the north extending along east to west part of Java Islands, and normal faults in Pasuruan and Probolinggo. Several studies have indicated the potential of earthquakes associated with these sources. The geodetic technique is employed to monitor the deformation activity in the eastern part of Java to understand the characteristics. We utilized the continuous GPS stations operated by Geospatial Agency of Indonesia (BIG) and processed them using the GAMIT/GLOBK software. The processing incorporates the IGS stations surrounding Indonesia. We also used precise orbit and 2nd-order ionospheric correction. The processing produces the velocity in the ITRF2014 reference frame, which generally indicates the south-eastward velocity up to 29 mm/year, mainly influenced by block rotation. Velocity referenced to the Sunda block shows a distinguished pattern between southern Java and northern Java. The velocity pattern in the southern part of Java tends to move northwest with a velocity variation of 3-6 mm/year, while several north stations show a velocity pattern to the south with a variation of 2-4 mm/yr. The strain analysis shows different patterns between eastern and western regions and different characteristics of southern and northern regions. Mainly the deformation is dominated by the compression due to the subduction in the south. Meanwhile, near to the central Java the deformation patterns significantly change due to the appearance of the east-west extension. The result indicates the different distinguished characteristics of the deformation source in the eastern part of Java. This result will have implications for seismic hazard analysis as a contribution to disaster risk reduction in the future.

Slip Partitioning Across Subparallel Strands of the North Anatolian Fault in the Marmara Region

Summary Marmara Region hosts a substantial part of the inhabitants in Turkey, more than 30% of the total population in the cities of Istanbul, Bursa, and Kocaeli. This region has experienced several large earthquakes in the past and is still under threat of destructive earthquakes in the future. There, subparallel strands of the North Anatolian Fault (NAF) expand into the region, distributing the earthquake hazards across the whole region. Thus, it is a key issue to investigate how the tectonic process is distributed between these subparallel strands to discriminate their individual earthquake hazards. In this context, we used GPS slip rates to quantify the slip partitioning of the subparallel strands of the fault system. In addition to available slip rates compiled by Bulut et al. (2019) and Kreemer et al. (2014), we analyzed 71 GPS sites (51 continuous and 20 campaign-based) to intensify the GPS network in the region. GPS observations reveal 81.7%, 7.7%, and 10.7% slip ratios for northern, middle, and southern strands. Time series analysis for four continuous GPS stations in the western Marmara Region also confirms these ratios.

Country-scale assessment of urban areas, population, and households exposed to land subsidence using Sentinel-1 InSAR, and GPS time series

The increased need for water resources in urban sprawls and intense droughts has forced more aggressive groundwater extraction resulting in numerous urban areas undergoing land subsidence. In most cases, only some large metropolitan areas have been well-characterized for subsidence. However, there is no existing country-wide assessment of urban areas, population, and households exposed to this process. This research showcases a methodology to systematically evaluate urban localities with land subsidence higher than − 2.8 cm/year throughout Mexico. We used Interferometric Synthetic Aperture Radar (InSAR) tools with a dataset of 4611 scenes from European Space Agency’s Sentinel-1 A/B SAR sensors acquired from descending orbits from September 2018 through October 2019. This dataset was processed at a supercomputer using InSAR Scientific Computing Environment and the Miami InSAR Time Series software in Python software. The quality and calibration of the resulting velocity maps are assessed through a large-scale comparison with observations from 100 continuous GPS sites throughout Mexico. Our results show that an urban area of 3797 km2, 6.9 million households, and 17% of the total population in Mexico is exposed to subsidence velocities of faster than − 2.8 cm/year, in more than 853 urban localities within 29 land subsidence regions. We also confirm previous global potential estimations of subsidence occurrence in low relief areas over unconsolidated deposits and where groundwater aquifers are under stress. The presented research demonstrates the capabilities for surveying urban areas exposed to land subsidence at a country-scale level by combining Sentinel-1 velocities with spatial national census data.

Cross-Comparison Individual Patient Level Analysis of Three Gene Expression Signatures in Localized Prostate in over 50,000 Men

Risk stratification guides the management of localized prostate cancer. Multiple commercial gene expression biomarkers have been developed to improve estimates of prognosis, however the 22-gene Decipher genomic classifier (22-GC) is the only test with level 1 evidence supporting its use per NCCN guidelines. It is unknown whether other commercial signatures, Oncotype (GPS) or Prolaris (CCP), are sufficiently correlated to negate the differences in evidence supporting these commercial tests. Herein, we aim to perform a cross-comparison of these signatures in a large cohort of patients diagnosed with localized prostate cancer. Patients diagnosed with localized prostate cancer who underwent whole transcriptome gene expression microarray analysis on their primary tumor biopsy specimen were included. The 22-GC score was calculated by Veracyte using a commercially locked model. Individual genes in each of the GPS and CCP gene signatures were identified, and the gene weights in each signature were retrained for prediction of metastasis in a multi-institutional cohort of 1,574 men with long-term outcome data. This was performed to improve correlation performance of GPS and CCP given only the 22-GC was trained for prediction of metastasis. For each of the three signatures, both continuous and categorical scores were calculated. Linear regression and spearman correlations were calculated both on univariable and multivariable analyses adjusting for age, grade group, PSA, and T-stage. A total of 50,881 patients were included (15,379 (30.2%) NCCN low-risk, 14,773 (29.0%) favorable intermediate-risk, 15,544 (30.5%) unfavorable intermediate-risk, and 5,185 (10.2%) high/very high-risk) with a median age of 68 years, and a median PSA of 6.2 ng/mL. On linear regression, the GPS model had poor goodness-of-fit to the 22-GC with an R2 of 0.36, as did the CCP model to the 22-GC with an R2 of 0.32. For CCP, the linear sum of the 31-genes was also tested but had inferior performance (R2 0.28) compared to the reoptimized CCP model. Results were similar on multivariable analysis adjusting for age, PSA, clinical stage and grade group. Spearman correlation between the continuous GPS model scores and the 22-GC was moderate at 0.59, as was the correlation between CCP model and the 22-GC of 0.54. CCP is a measure of proliferation, but in 22-GC high-risk patients, the majority (64.1%) of patients had low-average proliferation and only 35.9% had high proliferation, potentially explaining the lack of strong correlation. There is minimal to moderate correlation between the 22-GC and GPS or CCP gene expression signatures tested. Therefore, these tests should not be viewed as interchangeable, and utilization should be based on the level of evidence supporting each gene expression biomarker.

Efficient Large-Scale GPS Trajectory Compression on Spark: A Pipeline-Based Approach

Every day, hundreds of thousands of vehicles, including buses, taxis, and ride-hailing cars, continuously generate GPS positioning records. Simultaneously, the traffic big data platform of urban transportation systems has already collected a large amount of GPS trajectory datasets. These incremental and historical GPS datasets require more and more storage space, placing unprecedented cost pressure on the big data platform. Therefore, it is imperative to efficiently compress these large-scale GPS trajectory datasets, saving storage cost and subsequent computing cost. However, a set of classical trajectory compression algorithms can only be executed in a single-threaded manner and are limited to running in a single-node environment. Therefore, these trajectory compression algorithms are insufficient to compress this incremental data, which often amounts to hundreds of gigabytes, within an acceptable time frame. This paper utilizes Spark, a popular big data processing engine, to parallelize a set of classical trajectory compression algorithms. These algorithms consist of the DP (Douglas–Peucker), the TD-TR (Top-Down Time-Ratio), the SW (Sliding Window), SQUISH (Spatial Quality Simplification Heuristic), and the V-DP (Velocity-Aware Douglas–Peucker). We systematically evaluate these parallelized algorithms on a very large GPS trajectory dataset, which contains 117.5 GB of data produced by 20,000 taxis. The experimental results show that: (1) It takes only 438 s to compress this dataset in a Spark cluster with 14 nodes; (2) These parallelized algorithms can save an average of 26% on storage cost, and up to 40%. In addition, we design and implement a pipeline-based solution that automatically performs preprocessing and compression for continuous GPS trajectories on the Spark platform.

Co-seismic deformation for the 2015 MW7.8 Gorkha earthquake (Nepal) using near-field GPS data

Seasonal variations and common mode errors affect the precision of the Global Positioning System (GPS) time series. In this paper, we explore to improve the precision of coordinate time series, thereby providing a better detection of weak or transient deformation signals, particularly co-seismic signals. Based on 97 GPS stations, including the campaign and continuous GPS stations in Nepal and southern Tibet, we first consider seasonal variations and common errors, then obtain co-seismic deformation of the 2015 Gorkha earthquake in Nepal and southern Tibet. Our co-seismic rupture model is characterized by a shallow ramp and a deeper detachment fault, in agreement with the relocated aftershock sequence. Our results indicate that the earthquake rupture is mainly distributed in the upper-crustal fault, and the maximum slip is up to 8.0 m at ∼15.0 km depth located in the approximate-80 km east of the epicenter. The average slip is more than 5 m, and the total modelled magnitude is MW7.84, consistent with the observed seismic moment. Our rupture model for the 2015 Gorkha earthquake suggests that the rupture zone is not only in the upper crustal Main Himalayan Thrust (MHT), but also spreads to the northern segment of the MHT.

Evidence of Strain Accumulation and Coupling Variation in the Himachal Region of NW Himalaya From Short Term Geodetic Measurements

AbstractHimachal region of Northwest Himalaya exhibits the widest structural re‐entrant in Kangra region and significant strain partitioning along the frontal and hinterland out‐of‐sequence faults. We report results of continuous GPS measurements from 10 new sites in the region and analyze them along with the previously published results to constrain the ongoing arc‐normal and arc‐parallel convergence rates at 16.5 ± 1.1 and 4–5 mm/yr respectively. Thus, the ongoing convergence is oblique by 15°–20°. The Main Himalayan Thrust (MHT) is strongly coupled up to ∼100 km from the Main Frontal Thrust but displays significant variation in coupling in the transition zone across the Kangra re‐entrant and the adjoining western salient. Joint analysis of the coupling variation, the geologically inferred MHT geometry variations and the local topographic anomaly pattern strongly suggest the possibility of a potentially active, strain accumulating segment of MBT along the southern margin of Dhauladhar ranges in Western Himachal region, which is also proposed to be influencing the long‐term topographic growth in the region. Although a general agreement is observed between the long‐term shortening rates along the active faults and the estimated geodetic convergence in this region, the ensuing discussion highlights their complex relationship in terms of temporal and spatial variability in the fault activity and elastic‐inelastic deformation. We use the fault orientation and the estimated convergence rate to geometrically constrain a mean dextral slip‐rate of 4.4–5.7 mm/yr along a recently discovered Khetpurali‐Taksal fault, which is proposed to partition the majority of ongoing arc‐parallel deformation along it.