GPS Time 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.

Analysis of the Spatial Distribution and Common Mode Error Correlation in a Small-Scale GNSS Network.

When analyzing GPS time series, common mode errors (CME) often obscure the actual crustal movement signals, leading to deviations in the velocity estimates of station coordinates. Therefore, mitigating the impact of CME on station positioning accuracy is crucial to ensuring the precision and reliability of GNSS time series. The current approach to separating CME mainly uses signal filtering methods to decompose the residuals of the observation network into multiple signals, from which the signals corresponding to CME are identified and separated. However, this method overlooks the spatial correlation of the stations. In this paper, we improved the Independent Component Analysis (ICA) method by introducing correlation coefficients as weighting factors, allowing for more accurate emphasis or attenuation of the contributions of the GNSS network's spatial distribution during the ICA process. The results show that the improved Weighted Independent Component Analysis (WICA) method can reduce the root mean square (RMS) of the coordinate time series by an average of 27.96%, 15.23%, and 28.33% in the E, N, and U components, respectively. Compared to the ICA method, considering the spatial distribution correlation of stations, the improved WICA method shows enhancements of 12.53%, 3.70%, and 8.97% in the E, N, and U directions, respectively. This demonstrates the effectiveness of the WICA method in separating CMEs and provides a new algorithmic approach for CME separation methods.

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.

Development of GPS time-based reference trajectories for quality assessment of multi-sensor systems

Abstract The development of multi-sensor systems (MSSs) goes hand in hand with assessing the quality of these complex systems. Therefore, reliable reference information of superior accuracy is essential for validation, serving as ground truth. When the assessment is based on 3D point cloud comparison, appropriate reference environments with suitable geometries are required. However, validation of an MSS can also be performed directly on its 3D position or even its 6D pose. This is particularly suitable for systems without sensors for environmental acquisition. When using kinematic measurement systems, the temporal relationship between the MSS and the reference trajectory must be considered, which can be challenging. Modern sensors of an MSS are often synchronized to GPS time. However, this global time information is not provided for high-accuracy tracking sensors such as robotic total stations (RTSs) or laser trackers (LTs). Instead, only a reference to an internal sensor time is implemented, which does not meet the highest quality requirements for reference trajectories. Depending on the motion speed, time offsets in the millisecond range can lead to significant trajectory inaccuracies. This paper presents investigations for GPS time synchronization of the polar measurement elements of both RTS and LT from Leica Geosystems. While the LT uses a precise trigger signal for the time link, the RTS requires the Measure & Stream application provided by the instrument manufacturer. The two different approaches are presented theoretically. Based on empirical long-term studies, their possibilities and limitations are critically discussed. For the high-frequency LT, reference trajectories with precise synchronization based on GPS time can be reliably realized. With an RTS, improved synchronization can be achieved by using Measure & Stream. Thus, 43 % lower tangential deviations from the reference could be achieved compared to the raw data. However, there are still inconstant time offsets of 63.9 ms on average. Depending on the speed of the target, this can lead to significant position deviations. Further investigations are required. In general, the developed approaches for the realization of GPS-synchronized reference trajectories can be used not only for the quality assessment of MSS, but also for monitoring or kinematic positioning applications.

Singular spectrum analysis for the time-variable seasonal signals from GPS in Yunnan Province

Studying the seasonal deformation in GPS time series is important to interpreting geophysical contributors and identifying unmodeled and mismodeled seasonal signals. Traditional seasonal signal extraction used the least squares method, which models seasonal deformation as a constant seasonal amplitude and phase. However, the seasonal variations are not constant from year to year, and the seasonal amplitude and phase are time-variable. In order to obtain the time-variable seasonal signal in the GPS station coordinate time series, singular spectrum analysis (SSA) is conducted in this study. We firstly applied the SSA on simulated seasonal signals with different frequencies 1.00 cycle per year (cpy), 1.04 cpy and with time-variable amplitude are superimposed. It was found that SSA can successfully obtain the seasonal variations with different frequencies and with time-variable amplitude superimposed. Then, SSA is carried out on the GPS observations in Yunnan Province. The results show that the time-variable amplitude seasonal signals are ubiquitous in Yunnan Province, and the time-variable amplitude change in 2019 in the region is extracted, which is further explained by the soil moisture mass loading and atmospheric pressure loading. After removing the two loading effects, the SSA obtained modulated seasonal signals which contain the obvious seasonal variations at frequency of 1.046 cpy, it is close with the GPS draconitic year, 1.040 cpy. Hence, the time-variable amplitude changes in 2019 and the seasonal GPS draconitic year in the region could be discriminated successfully by SSA in Yunnan Province.

Intra- and interannual variation in the foraging behavior of common Murres (Uria aalge) in the Central California current

Seabirds modify their behavior during the breeding season as they transition from incubation (self-feeding) to chick-rearing (self-feeding + chick provisioning) periods, which affects parental foraging patterns and distribution. However, it is less clear how much flexibility parents have to modulate their behavior when environmental conditions are unusually poor. Using GPS loggers and time depth recorders, we examined the foraging flexibility of common murres (Uria aalge) at Southeast Farallon Island as adjustments were made between breeding phases and across consecutive years (2019 and 2020) with contrasting oceanographic conditions (i.e. prominent marine heatwave in 2019). Foraging trips were longer during the incubation period (2019: 31.7 ± 20.1 h; 2020: 23.5 ± 7.2 h) compared to the chick provisioning period (2019: 12.2 ± 9.9 h; 2020: 7.5 ± 8.3 h). Moreover, parents generally ventured farther from the colony during incubation (2019: 34.7 ± 17.6 km; 2020: 30.1 ± 11.5 km) than when foraging to provision chicks (2019: 22.6 ± 17.1 km; 2020: 14.1 ± 15.0 km) in each year. Nevertheless, overall foraging ranges had a high degree of overlap (> 60%) within breeding phases and across years, suggesting that murres at this colony are constrained by the habitats primarily based on foraging range. Murres dove deeper during incubation compared to chick-rearing in 2020 (36.0 ± 24.4 vs 19.5 ± 15.2 m), but there were no other differences within or across years in diving behavior, suggesting that diving effort was less affected by breeding stage. Interannual differences in foraging behavior only occurred during chick-feeding trips and were likely driven by the prey species present. For example, rockfish were more common in chick diets in 2020, when ocean temperatures were cooler compared to 2019. Despite similarities in trip parameters between years, breeding productivity was much lower in 2019 compared to both long-term averages and the 2020 season, suggesting a potential constraint on murre behavioral flexibility when oceanographic variation occurs. These results emphasize the importance of examining behavior on multiple time scales to gain a better understanding of how predators respond to changes in their environment.

High Elevation Radiation Array (HERA) detectors for airborne thunderstorm investigations

A high-energy atmospheric physics phenomenon, referred to as a terrestrial gamma ray flash (TGF), is associated with lightning and produces large bursts of energetic photon radiation. TGFs will be investigated using a suite of gamma-ray instruments designed and constructed to fly on ten United States Air Force (USAF) WC-130J Hurricane Hunter aircraft as part of an aircrew ionization study led by the Air Force Institute of Technology (AFIT) and the United States Air Force School of Aerospace Medicine (USAFSAM), in cooperation with the 53rd Weather Reconnaissance Squadron (WRS). Each instrument consists of one NaI and one plastic detector, a GPS timing device, and an instrument computer that performs data acquisition. High Elevation Radiation Array (HERA) detectors will be employed to maximize the chances of observing TGFs near their source and to gain a better understanding of their origin, mechanism, ubiquity, and to assess potential hazards posed to military and commercial aircrew and passengers. The HERA program, deployed on 10 separate Air Force aircraft over a multi-year campaign, will result in thousands of observational flight hours and be the largest concerted effort to date to observe TGFs in situ through aircraft observations. In this paper, we give an overview of the scientific goals of this campaign and how the HERA instruments have been designed to meet those goals. We include a detailed description of the HERA instrument, along with mass model and signal processing simulations.

A method for locating lightning strikes in distribution lines with multiple branches

A lightning strike fault location (FT) method for multi-terminal overhead lines based on 0-mode 1-mode wave velocity difference is proposed to address the shortcomings of current multi-terminal overhead line positioning methods that are difficult to identify due to multi-terminal GPS time synchronization and reflected traveling waves. Based on the wave velocity difference between 0-mode and 1-mode, single-end ranging is performed, and an FT judgment vector is formed based on the ratio of the ranging results of each monitoring terminal to the inherent length of the line. By analyzing the element features in the FT judgment vector, an FT criterion is proposed, and the FT results of the appropriate monitoring terminal are selected as the final FT. After PSCAD/EMTDC simulation verification, this method is suitable for complex multi-branch overhead lines, and can accurately locate the FT without being affected by time synchronization.

GPS displacement dataset for the study of elastic surface mass variations

Abstract. Quantification of uncertainty in surface mass change signals derived from Global Positioning System (GPS) measurements poses challenges, especially when dealing with large datasets with continental or global coverage. We present a new GPS station displacement dataset that reflects surface mass load signals and their uncertainties. We assess the structure and quantify the uncertainty of vertical land displacement derived from 3045 GPS stations distributed across the continental US. Monthly means of daily positions are available for 15 years. We list the required corrections to isolate surface mass signals in GPS estimates and screen the data using GRACE(-FO) as external validation. Evaluation of GPS time series is a critical step, which identifies (a) corrections that were missed, (b) sites that contain non-elastic signals (e.g., close to aquifers), and (c) sites affected by background modeling errors (e.g., errors in the glacial isostatic model). Finally, we quantify uncertainty of GPS vertical displacement estimates through stochastic modeling and quantification of spatially correlated errors. Our aim is to assign weights to GPS estimates of vertical displacements, which will be used in a joint solution with GRACE(-FO). We prescribe white, colored, and spatially correlated noise. To quantify spatially correlated noise, we build on the common mode imaging approach by adding a geophysical constraint (i.e., surface hydrology) to derive an error estimate for the surface mass signal. We study the uncertainty of the GPS displacement time series and find an average noise level between 2 and 3 mm when white noise, flicker noise, and the root mean square (rms) of residuals about a seasonality and trend fit are used to describe uncertainty. Prescribing random walk noise increases the error level such that half of the stations have noise > 4 mm, which is systematic with the noise level derived through modeling of spatially correlated noise. The new dataset is available at https://doi.org/10.5281/zenodo.8184285 (Peidou et al., 2023) and is suitable for use in a future joint solution with GRACE(-FO)-like observations.

Estimating Bridge Natural Frequencies Based on Modal Analysis of Vehicle-Bridge Synchronized Vibration Data.

This paper presents a method for accurately estimating the natural frequencies of bridges by simultaneously measuring the acceleration vibration data of vehicles and bridges and applying modal analysis theory. Vibration sensors synchronized with GPS timing were installed on both vehicles and bridges, achieving stable and high-precision time synchronization. This enabled the computation of the bridge's Frequency Response Functions (FRFs) for each mode, leading to a refined estimation of natural frequencies. The validity of the theory was confirmed through numerical simulations and experimental tests. The simulations confirmed its effectiveness, and similar trends were observed in actual bridge measurements. Consequently, this method significantly enhances the feasibility of bridge health monitoring systems. The proposed method is suitable for road bridges with spans ranging from short- to medium-span length, where the vehicle is capable of exciting the bridge.

Mechanism and implications of the post-seismic deformation following the 2021 Mw 7.4 Maduo (Tibet) earthquake

SUMMARY A major earthquake shook the Chinese county of Maduo, located in the Songpan-Ganzi terrane on the Tibetan Plateau, on 21 May 2021. Here, we investigate the post-seismic deformation process of this event, with the aim to understand the fault geometry, friction behaviour and regional rheology. To keep the self-consistency between co- and post-seismic deformation models, we first constrain the fault geometry and coseismic slip model of this event, which are directly used in modelling the post-seismic deformation. The coseimsic slip model reveals that the majority of coseismic slip is confined at the middle (3–15 km) of the brittle layer, leading to significant shallow slip deficit. Secondly, we obtain the post-seismic deformation in the first 450 d following the 2021 Maduo earthquake using the GPS and InSAR displacement time-series data. Thirdly, a combined model incorporating afterslip and viscoelastic relaxation is built to explain the observed post-seismic deformation. Our results suggest that the viscoelastic relaxation effect should be considered in the observation period, in order to avoid the unphysical deep afterslip in the ductile lower crustal layer. Combined analysis on viscosities inferred from this study and previous studies suggests a weak lower crust with steady-state viscosity of 1018–1019 Pa s beneath the Songpan-Ganzi terrane, which may give rise to the distributed shear deformation and the development of subparallel secondary faults within the terrane. Besides, the inferred afterslip on uppermost patches of the middle fault segment suggests a rate-strengthening frictional behaviour that may be related to the coseismic slip deficit and rupture arrest of the Maduo earthquake.

AIS R-Mode Trilateration for GPS Positioning and Timing Insurance

AIS R-Mode Trilateration for GPS Positioning and Timing Insurance

Reconstruction of the Motion of Traffic Accident Vehicle in the Vehicle‐Mounted Video Based on Direct Linear Transform

Based on the principle of direct linear transformation (DLT) in close‐range photogrammetry, a method was proposed for reconstructing the motion states of the host vehicle and other vehicles based on vehicle‐mounted videos. To verify the effectiveness and accuracy of the method, validation experiments were designed. Under two typical operating states, steering and straight driving, the motion states of the host vehicle and other vehicles (including trajectory, distance, speed, and acceleration) were reconstructed from the vehicle‐mounted video. In the experiments, high‐precision inertial navigation was installed on the other vehicle to record real‐time motion data of the vehicle. Finally, in order to compare and analyze the reconstructed video results with the vehicle’s actual motion data, the recorded motion data were matched and synchronized to the same time axis as the vehicle‐mounted videos through a GPS timing device. The experimental result shows that the reconstructed trajectory results based on this method can generally reflect the vehicle’s actual trajectory, with an average deviation of less than 7.4%; the reconstructed distance results have an average deviation of less than 9.3%; the reconstructed speed results have an average deviation of less than 7.3%; the reconstructed acceleration results can reflect the vehicle’s acceleration or deceleration states. The results of this study provide an effective solution for obtaining important parameters of vehicles in accident reconstruction research, such as the trajectory, speed, distance, and acceleration or deceleration, and it has significant practical value for applications.

TOWARDS AUTONOMOUS HIGH-DEFINITION MAP CONSTRUCTION

Abstract. This paper presents a GPS constrained SLAM solution, which adds reliable GPS observations as key frames to the state-of-the-art SLAM algorithm Lightweight and Ground-Optimized Lidar Odometry and Mapping (LeGO-LOAM). As the GPS has a much higher frequency than that of lidar, we first assign each lidar frame with GPS time, then every 5 seconds, a reliable GPS observation is inserted as a key frame to the pose graph, then optimizes the pose estimation and updates the old key frames. We test our method with two platforms in real driving scene, and compare its performance with LeGO-LOAM, where LeGO-LOAM cannot acquire realtime efficiency. The difference of lidar odometry of our solution with compare to RTK-GPS is less than 0.4m, with the globally referenced map can be used for relocalization.

GPS data analysis and geodetic velocity field investigation in Greece, 2001–2016

In this study, an updated crustal velocity field for the Greece area was estimated using a time series analysis that covers a duration of 16 years (2001–2016) from 227 Global Navigation Satellite System (GNSS) permanent stations. The GPS processing was carried out using GNSS Analysis software at MIT (GAMIT) and the velocity field expressed with respect to Eurasian plate. For the time series analysis, we applied a robust Median Interannual Difference Adjusted for Skewness trend estimator to mitigate the effects of discontinuities due to geophysical phenomena on the estimation of geodetic velocities and their uncertainties. The main earthquake events that occurred in the GPS time series analysis in the study area are analyzed, providing the co-seismic displacements in the permanent GNSS stations. We also compare our geodetic velocities with five previous publications, where we found consistency at the mm/year level, leading to reliable results for the geodynamic behavior of the Greek area, providing a dense velocity field.

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.

Postseismic Deformation in the Northern Antarctic Peninsula Following the 2003 and 2013 Scotia Sea Earthquakes

AbstractLarge earthquakes in the vicinity of Antarctica have the potential to cause postseismic viscoelastic deformation affecting measurements of displacement that are used to constrain models of glacial isostatic adjustment (GIA). In November 2013, a Mw 7.7 strike‐slip earthquake occurred in the Scotia Sea, 650 km from the Antarctic Peninsula. GPS time series from the northern Peninsula show a change in rate after this event, indicating a far‐field postseismic deformation signal is present. In this study, we use a finite element model with a suite of 1D and 3D Earth structures to investigate the extent of postseismic deformation in the Antarctic Peninsula. Model output is compared with GPS time series to place constraints on the Earth structure in this region. The preferred Earth structure has a thin lithosphere combined with a Burgers rheology with steady‐state viscosity of 4 × 1018 Pa s and transient viscosity one order of magnitude lower. Our study shows that including 3D Earth structure does not improve the fit. Using the best fitting Earth structure, we run a forward model of the nearby 2003 Mw 7.6 strike‐slip earthquake and combine the predictions for both earthquakes. We show that postseismic deformation is widespread across the northern Peninsula with rates of horizontal deformation up to 1.65 mm/yr for the period 2015–2020, a signal that persists for decades. These results suggest that much of Antarctica may be deforming due to recent postseismic deformation and this signal needs to be accounted for when using GPS observations to constrain geophysical models.

The precursory phase of large earthquakes.

The existence of an observable precursory phase of slip on the fault before large earthquakes has been debated for decades. Although observations preceding several large earthquakes have been proposed as possible indicators of precursory slip, these observations do not directly precede earthquakes, are not seen before most events, and are also commonly observed without being followed by earthquakes. We conducted a global search for short-term precursory slip in GPS data. We summed the displacements measured by 3026 high-rate GPS time series-projected onto the directions expected from precursory slip at the hypocenter-during 48 hours before 90 (moment magnitude ≥7) earthquakes. Our approach reveals a ≈2-hour-long exponential acceleration of slip before the ruptures, suggesting that large earthquakes start with a precursory phase of slip, which improvements in measurement precision and density could more effectively detect and possibly monitor.

Wireless and Low-Power System for Synchronous and Real-Time Structural-Damage Assessment

The rise of Internet of Things (IoT) systems and the evolution of Low-Power Wide-Area Networks have directly contributed to the emergence of a new generation of Structural Health Monitoring (SHM) systems based on the Non-Destructive Test approach. Consequently, this article presents the design and development of a synchronous, low-cost, real-time, wireless, and low-power consumption SHM system for pre-existing buildings and infrastructures, which has been validated on a structure built in the High Middle Ages forming part of the historical heritage of the city of Seville (Spain). The system proposes a modular and scalable design with the capacity for synchronous monitoring of the accelerations of a structure thanks to the deployment of several reduced-size nodes that acquire and transmit the accelerations of the structures through a Secure Sockets Layer (SSL) NB-IoT connection. This aspect and Firmware Over The Air (FOTA) capability enables the permanent deployment of sensor nodes, thereby not only obviating the use of costly traditional devices but also granting access to the structures to be monitored for each test and maintenance task and hence supporting the tasks related to the preventive conservation of heritage. The experimental tests carried out demonstrate the low impact of GPS time synchronization and FOTA on the autonomy of the system. The precision of the system is also validated by comparing the results with a precision system in a real field test. Furthermore, continuous monitoring is guaranteed through the graphical interface developed as a composition of microservices, which enables management of the deployed networks.

A Technology for Seismogenic Process Monitoring and Systematic Earthquake Forecasting

Earthquakes are a severe natural phenomenon that require continuous monitoring, analysis, and forecasting to mitigate their risks. Seismological data have long been used for this purpose, but geodynamic data from remote sensing of surface displacements have become available in recent decades. In this paper, we present a novel information technology for monitoring, analyzing seismogenic fields, and predicting earthquakes using Earth remote sensing data presented as a time series of surface displacement points for systematic regional earthquake prediction. We demonstrate, for the first time, the successful application of this technology and discuss the method of the minimum area of alarm, which was developed for machine learning and systematic earthquake prediction, as well as the architecture and tools of the GIS platform. Our technology is implemented as a network platform consisting of two GISs. The first GIS automatically loads earthquake catalog data and GPS time series, calculates spatiotemporal fields, performs systematic earthquake prediction in multiple seismically active regions, and provides intuitive mapping tools to analyze seismic processes. The second GIS is designed for scientific research of spatiotemporal processes, including those related to earthquake forecasting. We demonstrate the effectiveness of platform analysis tools that are intuitive and accessible to a wide range of users in solving problems of systematic earthquake prediction. Additionally, we provide examples of scientific research on earthquake prediction using the second GIS, including the effectiveness of using GPS data for forecasting earthquakes in California, estimating the density fields of earthquake epicenters using the adaptive weighted smoothing (AWS) method for predicting earthquakes in Kamchatka, and studying earthquake forecasts in the island part of the territory of Japan using the earthquake catalog and GPS. Our examples demonstrate that the method of the minimum area of alarm used for machine learning is effective for forecasting both catalog and remote sensing data.