Search Results (465)

Leveraging multi-source remote sensing datasets and dynamic groundwater monitoring well observations, this study explores the multiscale spatiotemporal linkages of groundwater storage changes and land deformation in North China Plain (NCP) after the South-to-North Water Diversion Project (SNWDP). Firstly, we employed Gravity Recovery and Climate Experiment (GRACE) and interferometric synthetic aperture radar (InSAR) technology to estimate groundwater storage (GWS) and land deformation. Secondly and significantly, we proposed a novel GRACE statistical downscaling algorithm that integrates a weight allocation strategy and GWS estimation applied with InSAR technology. Finally, the downscaled results were employed to analyze spatial differences in land deformation across typical ground fissure areas. The results indicate that (1) between 2018 and 2021, groundwater storage in the NCP exhibited a declining trend, with an average reduction of −3.81 ± 0.53 km³/a and a maximum land deformation rate of −177 mm/a; (2) the downscaled groundwater storage anomalies (GWSA) showed high correlation with in situ measurements (R = 0.75, RMSE = 2.91 cm); and (3) in the Shunyi fissure area, groundwater storage on the northern side increased continuously, with a maximum growth rate of 28 mm/a, resulting in surface uplift exceeding 70 mm. Full article

Parametric optimization/inversion of Interferometric Synthetic Aperture Radar (InSAR) measurements enables the modeling of the volcanic deformation source by considering the approximation of the analytic formulations or by defining refined scenarios within a Finite Element (FE) framework. However, the geodetic data modeling can lead to ambiguous solutions when constraints are unavailable, turning out to be time-consuming. In this work, we use an integrated multiscale approach for retrieving the geometric parameters of volcanic deformation sources and then constraining a Monte Carlo optimization of FE parametric modeling. This approach allows for contemplating more physically complex scenarios and more robust statistical solutions, and significantly decreasing computing time. We propose the Campi Flegrei caldera (CFc) case study, considering the 2019–2022 uplift phenomenon observed using Sentinel-1 satellite images. The workflow firstly consists of applying the Multiridge and ScalFun methods, and Total Horizontal Derivative (THD) technique to determine the position and horizontal sizes of the deformation source. We then perform two independent cycles of parametric FE optimization by keeping (I) all the parameters unconstrained and (II) constraining the source geometric parameters. The results show that the innovative application of the integrated multiscale approach improves the performance of the FE parametric optimization in proposing a reliable interpretation of volcanic deformations, revealing that (II) yields statistically more reliable solutions than (I) in an extraordinary tenfold reduction in computing time. Finally, the retrieved solution at CFc is an oblate-like source at approximately 3 km b.s.l. embedded in a heterogeneous crust. Full article

Landslide InSAR monitoring is crucial for understanding the evolutionary mechanisms of geological disasters and enhancing risk prevention and control capabilities. However, for complex terrains and large-scale landslides, satellite-based SAR monitoring faces challenges such as a low observation frequency and limited spatial deformation interpretation capabilities. Additionally, two-dimensional monitoring struggles to comprehensively capture multi-directional movements. Taking the post-disaster monitoring of the landslide in Yunchuan, Sichuan Province, as an example, this study proposes a method for three-dimensional deformation dynamic monitoring by integrating dual-view MIMO ground-based synthetic aperture radar (GB-InSAR) data with high-resolution digital elevation model (DEM) data, successfully reconstructing the three-dimensional displacement fields in the east–west, north–south, and vertical directions. The results show that deformation in the landslide area evolved from slow accumulation to rapid failure, particularly concentrated in the middle and lower regions of the landslide. The average three-dimensional deformation of the main slip zone was approximately 60% greater than that of the original slope, with a maximum deformation of −100 mm. These deformation characteristics are highly consistent with the topographic structure and sliding direction. Field investigations further validated the radar data, with observed surface cracks and accumulation zones consistent with the high-deformation regions identified by the monitoring system. This system provides a solid foundation for geological disaster early warning systems, mechanism research, and risk prevention and control. Full article

In mountainous canyon regions, BeiDou Navigation Satellite System (BDS)/Global Navigation Satellite System (GNSS) receivers are susceptible to multireflection and tropospheric factors, which frequently reduce the accuracy in monitoring vertical deformation monitoring under short-baseline methods. This limitation hinders the application of BDS/GNSS in high-precision monitoring scenarios in those cases. To address this issue, this study proposes a three-dimensional (3D) deformation measurement method that integrates BDS/GNSS positioning with dihedral corner reflectors (CRs). By incorporating high-precision horizontal positioning results obtained from BDS/GNSS into the radar line-of-sight (LOS) correction process and utilizing ascending and descending Synthetic Aperture Radar (SAR) data for joint monitoring, the method achieves millimeter-level- accuracy in measuring vertical deformation at corner reflector sites. At the same time, it enhances the 3D positioning accuracy of BDS/GNSS to the 1 mm level under short-baseline configurations. Based on monitoring stations deployed at the Jinsha River dam site, the proposed deformation fusion monitoring method was validated using high-resolution SAR imagery from Germany’s TerraSAR-X (TSX) satellite. Simulated horizontal and vertical displacements were introduced at the stations. The results demonstrate that BDS/GNSS achieves better than 1 mm horizontal monitoring accuracy and a vertical accuracy of around 5 mm. Interferometric SAR (InSAR) CRs achieve approximately 2 mm in horizontal accuracy and 1 mm in vertical accuracy. The integrated method yields a 3D deformation monitoring accuracy better than 1 mm. This paper’s results show high potential for achieving high-precision deformation observations by fusing BDS/GNSS and dihedral CRs, offering promising prospects for deformation monitoring in reservoir canyon regions. Full article

The Xiong’an New Area, a newly established national-level zone in China, faces the threat of land subsidence and ground fissure due to groundwater overexploitation and geothermal extraction, threatening urban safety. This study integrates time-series InSAR and GNSS monitoring to analyze spatiotemporal deformation patterns from 2017/05 to 2025/03. The key results show: (1) Three subsidence hotspots, namely northern Xiongxian (max. cumulative subsidence: 591 mm; 70 mm/yr), Luzhuang, and Liulizhuang, strongly correlate with geothermal wells and F4/F5 fault zones; (2) GNSS baseline analysis (e.g., XA01-XA02) reveals fissure-induced differential deformation (max. horizontal/vertical rates: 40.04 mm/yr and 19.8 mm/yr); and (3) InSAR–GNSS cross-validation confirms the high consistency of the results (Pearson’s correlation coefficient = 0.86). Subsidence in Xiongxian is driven by geothermal/industrial groundwater use, without any seasonal variations, while Anxin exhibits agricultural pumping-linked seasonal fluctuations. The use of rooftop GNSS stations reduces multipath effects and improves urban monitoring accuracy. The spatiotemporal heterogeneity stems from coupled resource exploitation and tectonic activity. We propose prioritizing rooftop GNSS deployments to enhance east–west deformation monitoring. This framework balances regional and local-scale precision, offering a replicable solution for geological risk assessments in emerging cities. Full article

Geological storage is an integral element of the green energy transition. Geological formations, such as aquifers, depleted reservoirs, and hard rock caverns, are used mainly for the storage of hydrocarbons, carbon dioxide and increasingly hydrogen. However, potential adverse effects such as ground movements, leakage, seismic activity, and environmental pollution are observed. Existing research focuses on monitoring subsurface elements of the storage, while on the surface it is limited to ground movement observations. The review was carried out based on 191 research contributions related to geological storage. It emphasizes the importance of monitoring underground gas storage (UGS) sites and their surroundings to ensure sustainable and safe operation. It details surface monitoring methods, distinguishing geodetic surveys and remote sensing techniques. Remote sensing, including active methods such as InSAR and LiDAR, and passive methods of multispectral and hyperspectral imaging, provide valuable spatiotemporal information on UGS sites on a large scale. The review covers modelling and prediction methods used to analyze the environmental impacts of UGS, with data-driven models employing geostatistical tools and machine learning algorithms. The limited number of contributions treating geological storage sites holistically opens perspectives for the development of complex approaches capable of monitoring and modelling its environmental impacts. Full article

The precise characterization of surface rupture zones and associated co-seismic displacement fields from large earthquakes provides critical insights into seismic rupture mechanisms, earthquake dynamics, and hazard assessments. Stereo-photogrammetric digital elevation models (DEMs), produced from high-resolution satellite stereo imagery, offer reliable global datasets that are suitable for the detailed extraction and quantification of vertical co-seismic displacements. In this study, we utilized pre- and post-event WorldView-2 stereo images of the 2024 Ms7.1 Wushi earthquake in Xinjiang to generate DEMs with a spatial resolution of 0.5 m and corresponding terrain point clouds with an average density of approximately 4 points/m². Subsequently, we applied the Iterative Closest Point (ICP) algorithm to perform differencing analysis on these datasets. Special care was taken to reduce influences from terrain changes such as vegetation growth and anthropogenic structures. Ultimately, by maintaining sufficient spatial detail, we obtained a three-dimensional co-seismic displacement field with a resolution of 15 m within grid cells measuring 30 m near the fault trace. The results indicate a clear vertical displacement distribution pattern along the causative sinistral–thrust fault, exhibiting alternating uplift and subsidence zones that follow a characteristic “high-in-center and low-at-ends” profile, along with localized peak displacement clusters. Vertical displacements range from approximately 0.2 to 1.4 m, with a maximum displacement of ~1.46 m located in the piedmont region north of the Qialemati River, near the transition between alluvial fan deposits and bedrock. Horizontal displacement components in the east-west and north-south directions are negligible, consistent with focal mechanism solutions and surface rupture observations from field investigations. The successful extraction of this high-resolution vertical displacement field validates the efficacy of satellite-based high-resolution stereo-imaging methods for overcoming the limitations of GNSS and InSAR techniques in characterizing near-field surface displacements associated with earthquake ruptures. Moreover, this dataset provides robust constraints for investigating fault-slip mechanisms within near-surface geological contexts. Full article

Reservoir-induced landslides threaten infrastructures and downstream communities, making continuous deformation monitoring vital. Time-series InSAR, notably the SBAS algorithm, provides high-precision surface-displacement mapping but suffers from voids due to layover/shadow effects and temporal decorrelation. Existing deep-learning approaches often operate on fixed-size patches or ignore irregular spatio-temporal dependencies, limiting their ability to recover missing pixels. With this objective, a hybrid spatio-temporal Graph Attention (ST-GAT) framework was developed and trained on SBAS-InSAR values using 24 influential features. A unified spatio-temporal graph is constructed, where each node represents a pixel at a specific acquisition time. The nodes are connected via inverse distance spatial edges to their K-nearest neighbors, and they have bidirectional temporal edges to themselves in adjacent acquisitions. The two spatial GAT layers capture terrain-driven influences, while the two temporal GAT layers model annual deformation trends. A compact MLP with per-map bias converts the fused node embeddings into normalized LOS estimates. The SBAS-InSAR results reveal LOS deformation, with 48% of missing pixels and 20% located near the Dasu dam. ST D-GAT reconstructed fully continuous spatio-temporal displacement fields, filling voids at critical sites. The model was validated and achieved an overall R² (0.907), ρ (0.947), per-map R² ≥ 0.807 with RMSE ≤ 9.99, and a ROC-AUC of 0.91. It also outperformed the six compared baseline models (IDW, KNN, RF, XGBoost, MLP, simple-NN) in both RMSE and R². By combining observed LOS values with 24 covariates in the proposed model, it delivers physically consistent gap-filling and enables continuous, high-resolution landslide monitoring in radar-challenged mountainous terrain. Full article

With advancements in radar sensors, communications, and computer technologies, alongside an increasing number of ground observation tasks, Synthetic Aperture Radar (SAR) remote sensing is transitioning from being theory and technology-driven to being application-demand-driven. Since the late 1960s, Interferometric Synthetic Aperture Radar (InSAR) theories and techniques have continued to develop. They have been applied significantly in various fields, such as in the generation of global topography maps, monitoring of ground deformation, marine observations, and disaster reduction efforts. This article classifies InSAR into repeated-pass interference and single-pass interference. Repeated-pass interference mainly includes D-InSAR, PS-InSAR and SBAS-InSAR. Single-pass interference mainly includes CT-InSAR and AT-InSAR. Recently, China has made significant progress in the field of SAR satellite development, successfully launching several satellites equipped with interferometric measurement capabilities. These advancements have driven the evolution of spaceborne InSAR systems from single-frequency to multi-frequency, from low Earth orbit to higher orbits, and from single-platform to multi-platform configurations. These advancements have supported high precision and high-temporal-resolution land observation, and promoted the broader application of InSAR technology in disaster early warning, ecological monitoring, and infrastructure safety. Full article

With ongoing global warming, glacier lake outburst floods (GLOFs) and associated debris flows pose increasing threats to downstream communities and infrastructure. Glacial lakes differ in their triggering factors and breach mechanisms, necessitating event-specific analysis. This study investigates the GLOF risk of Jiongpuco Lake, located in the southeastern part of the Tibetan Plateau, using an integrated approach combining remote sensing, field surveys, and numerical modeling. Results show that the lake has expanded significantly—from 2.08 km² in 1990 to 5.43 km² in 2021—with the most rapid increase observed between 2015 and 2016. InSAR data and optical imagery indicate that surrounding moraine deposits remain generally stable. However, ice avalanches from the glacier terminus are identified as the primary trigger for lake outburst via wave-induced overtopping. Mechanical and geomorphological analyses suggest that the moraine dam is resistant to downcutting erosion, reinforcing overtopping as the dominant failure mode. To assess potential impacts, three numerical simulation scenarios were conducted based on different avalanche volumes. Under the extreme scenario involving a 5-million m³ ice avalanche, the modeled peak discharge at the dam site reaches approximately 19,000 m³/s. Despite the high flood magnitude, the broad and gently sloped downstream terrain facilitates rapid attenuation of flood peaks, resulting in limited impact on downstream settlements. These findings offer critical insights for GLOF hazard assessment, disaster preparedness, and risk mitigation under a changing climate. Full article

Using interferometric synthetic aperture radar (InSAR) to observe slow ground deformation can be challenging due to many sources of error, with tropospheric phase delay and unwrapping errors being the most significant. While analytical methods, weather models, and data exist to mitigate tropospheric error, most of these techniques are unsuitable for all InSAR applications (e.g., complex tropospheric mixing in the tropics) or are deficient in spatial or temporal resolution. Likewise, there are methods for removing the unwrapping error, but they cannot resolve the true phase when there is a high prevalence (>40%) of unwrapping error in a set of interferograms. Applying tropospheric delay removal techniques is unnecessary for C-band Sentinel-1 InSAR time series studies, and the effect of unwrapping error can be minimized if the full dataset is utilized. We demonstrate that using interferograms with long temporal baselines (800 days to 1600 days) but very short perpendicular baselines (<5 m) (LTSPB) can lower the velocity detection threshold to 2 mm y⁻¹ to 3 mm y⁻¹ for long-term coherent permanent scatterers. The LTSPB interferograms can measure slow deformation rates because the expected differential phases are larger than those of small baselines and potentially exceed the typical noise amplitude while also reducing the sensitivity of the time series estimation to the noise sources. The method takes advantage of the Sentinel-1 mission length (2016 to present), which, for most regions, can yield up to 300 interferograms that meet the LTSPB baseline criteria. We demonstrate that low velocity detection can be achieved by comparing the expected LTSPB differential phase measurements to synthetic tests and tropospheric delay from the Global Navigation Satellite System. We then characterize the slow (~3 mm/y) ground deformation of the Socorro Magma Body, New Mexico, and the Tampa Bay Area using LTSPB InSAR analysis. The method we describe has implications for simplifying the InSAR time series processing chain and enhancing the velocity detection threshold. Full article

The southwestern mountainous region of China (SMRC), characterized by complex geological environments, experiences frequent landslide disasters that pose significant threats to local residents. This study focuses on the Qijiang District of Chongqing, where we conduct a systematic evaluation of wavelength and observation geometry effects on InSAR-based landslide monitoring. Utilizing multi-sensor SAR imagery (Sentinel-1 C-band, ALOS-2 L-band, and LUTAN-1 L-band) acquired between 2018 and 2025, we integrate time-series InSAR analysis with geological records, high-resolution topographic data, and field investigation findings to assess representative landslide-susceptible zones in the Qijiang District. The results indicate the following: (1) L-band SAR data demonstrates superior monitoring precision compared to C-band SAR data in the SMRC; (2) the combined use of LUTAN-1 ascending/descending orbits significantly improved spatial accuracy and detection completeness in complex landscapes; (3) multi-source data fusion effectively mitigated limitations of single SAR systems, enhancing identification of small- to medium-scale landslides. This study provides critical technical support for multi-source landslide monitoring and early warning systems in Southwest China while demonstrating the applicability of China’s SAR satellites for geohazard applications. Full article

Land subsidence significantly threatens vulnerable coastal environments. This study aims to explore how Semarang’s government, local communities, and researchers address land subsidence and its role in exacerbating flood risk, against the backdrop of ongoing efforts within flood risk governance. Employing an integrated mixed-methods approach, the research combined quantitative geospatial analysis (InSAR and land cover change detection) with qualitative socio-political and governance analysis (interviews, FGDs, field observations). Findings show high subsidence rates in Semarang. Line of sight displacement measurements revealed a continuous downward trend from late 2014 to mid-2023, with rates varying from −8.8 to −10.1 cm/year in Karangroto and Sembungharjo. Built-up areas concurrently expanded from 21,512 hectares in 2017 to 23,755 hectares in 2023, largely displacing cropland and tree cover. Groundwater extraction was identified as the dominant driver, alongside urbanization and geological factors. A critical disconnect emerged: community views focused on flooding, often overlooking subsidence’s fundamental role as an exacerbating factor. The study concluded that multi-level collaboration, improved risk communication, and sustainable land management are critical for enhancing urban coastal resilience against dual threats of subsidence and flooding. These insights offer guidance for similar rapidly developing coastal cities. Full article

On 18 December 2023, a M_w 6.2 earthquake occurred in close proximity to Jishishan County, located on the northeastern edge of the Qinghai–Tibet Plateau. The event struck the structural intersection of the Haiyuan fault, Lajishan fault, and West Qinling fault, providing empirical evidence for investigating the crustal compression mechanisms associated with the northeastward expansion of the Qinghai–Tibet Plateau. In this study, we successfully acquired a high-resolution coseismic deformation field of the earthquake by employing interferometric synthetic aperture radar (InSAR) technology. This was accomplished through the analysis of image data obtained from both the ascending and descending orbits of the Sentinel-1A satellite, as well as from the ascending orbit of the ALOS-2 satellite. Our findings indicate that the coseismic deformation is predominantly localized around the Lajishan fault zone, without leading to the development of a surface rupture zone. The maximum deformations recorded from the Sentinel-1A ascending and descending datasets are 7.5 cm and 7.7 cm, respectively, while the maximum deformation observed from the ALOS-2 ascending data reaches 10 cm. Geodetic inversion confirms that the seismogenic structure is a northeast-dipping thrust fault. The geometric parameters indicate a strike of 313° and a dip angle of 50°. The slip distribution model reveals that the rupture depth predominantly ranges between 5.7 and 15 km, with a maximum displacement of 0.47 m occurring at a depth of 9.6 km. By integrating the coseismic slip distribution and aftershock relocation, this study comprehensively elucidates the stress coupling mechanism between the mainshock and its subsequent aftershock sequence. Quantitative analysis indicates that aftershocks are primarily located within the stress enhancement zone, with an increase in stress ranging from 0.12 to 0.30 bar. It is crucial to highlight that the structural units, including the western segment of the northern margin fault of West Qinling, the eastern segment of the Daotanghe fault, the eastern segment of the Linxia fault, and both the northern and southern segment of Lajishan fault, exhibit characteristics indicative of continuous stress loading. This observation suggests a potential risk for fractures in these areas. Full article

The remote sensing of seismic waves in challenging and hazardous environments, such as active volcanic regions, remains a critical yet unresolved challenge. Conventional methods, including laser Doppler interferometry, InSAR, and stereo vision, are often hindered by atmospheric turbulence or necessitate access to observation sites, significantly limiting their applicability. To overcome these constraints, this study introduces a Moiré-based apparatus augmented with active convolved illumination (ACI). The system leverages the displacement-magnifying properties of Moiré patterns to achieve high precision in detecting subtle ground movements. Additionally, ACI effectively mitigates atmospheric fluctuations, reducing the distortion and alteration of measurement signals caused by these fluctuations. We validated the performance of this integrated solution through over 1900 simulations under diverse turbulence intensities. The results illustrate the synergistic capabilities of the Moiré apparatus and ACI in preserving the fidelity of Moiré fringes, enabling reliable displacement measurements even under conditions where passive methods fail. This study establishes a cost-effective, scalable, and non-invasive framework for remote seismic monitoring, offering transformative potential across geophysics, volcanology, structural analysis, metrology, and other domains requiring precise displacement measurements under extreme conditions. Full article