Search Results (106)

Wildfires pose a significant threat to the natural and built environment and may alter the hydrologic cycle in burned areas increasing the risk of flooding, erosion, debris flows, and shallow landslides. In this paper, we investigate the feasibility of using differential interferometric synthetic aperture radar (DInSAR) to interpret changes in ground surface elevation following the 2017 Eagle Creek Wildfire in Oregon, USA. We show that DInSAR is capable of measuring ground surface displacements in burned areas not obscured by vegetation cover and that interferometric coherence can differentiate between areas that experienced different burn severities. The distribution of projected vertical displacement was analyzed, suggesting that different areas experience variable rates of change, with some showing little to no change for up to four years after the fire. Comparison of the projected vertical displacements with cumulative precipitation and soil moisture suggests that increases in precipitation and soil moisture are related to periods of increased vertical displacement. The findings of this study suggest that DInSAR may have value where in situ instrumentation is infeasible and may assist in prioritizing areas at high-risk of erosion or other changes over large geographical extents and measurement locations for deployment of instrumentation. Full article

On 22 July 2020, an Mw 6.4 earthquake occurred in Nima County in the Qiangtang Terrane of the central Tibetan Plateau. This event, caused by normal faulting, remains controversial in terms of its rupture process and causative fault due to the complex tectonics of the region. In this study, we analyzed the coseismic and postseismic deformation using differential interferometric synthetic aperture radar (D-InSAR). The coseismic slip distribution was independently estimated through InSAR inversion and teleseismic waveform analysis, while the afterslip distribution was inferred from postseismic deformation. Coulomb stress failure analysis was conducted to assess the potential seismic hazard. Our results showed a maximum line-of-sight (LOS) coseismic deformation of about 29 cm away from the satellite, with quasi-vertical subsidence peaking at 35 cm. Four distinct deformation zones were observed in the quasi-east–west direction. Coseismic deformation and slip models based on InSAR and teleseismic data indicate that the Nima earthquake ruptured the West Yibu Chaka fault. The seismogenic fault had a strike of 26°, an eastward dip of 43°, and a rake of −87.28°, with rupture patches at depths of 3–13 km and a maximum slip of 1.1 m. Postseismic deformation showed cumulative LOS displacement of up to 0.05 m. Afterslip was concentrated in the up-dip and down-dip areas of the coseismic rupture zone, reaching a maximum of 0.11 m. Afterslip was also observed along the East Yibu Caka fault. Coulomb stress modeling indicates an increased seismic risk between the Yibu Caka fault and the Jiangai Zangbu fault, highlighting the vulnerability of the region to future seismic activity. Full article

Dams are crucial for ensuring water and electricity supply, while also providing significant flood protection. Regular monitoring of dam deformations is of vital socio-economic and ecological significance. In Germany, dams must be constructed and operated according to generally accepted rules of engineering. The safety concept for dams based on these rules relies on structural safety, professional operation and maintenance, safety monitoring, and precautionary measures. Rather time-consuming in situ techniques have been employed for these measurements, which permit monitoring deformations with either high spatial or temporal resolution, but not both. As a means of measuring large-scale deformations in the millimeter range, the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique of Persistent Scatterer Interferometry (PSI) is already being applied in various fields. However, when considering the operational monitoring of dams using PSI, specific characteristics need to be considered. For example, the geographical location of the dam in space, as well as its shape, size, and land cover. All these factors can affect the visibility of the structure for the use with PSI and, in certain cases, limit the applicability of SAR data. The visibility of dams for PSI monitoring is often limited, particularly in cases where observation is typically not feasible due to factors such as geographical and structural characteristics. While corner reflectors can improve visibility, their large size often makes them unsuitable for dam infrastructure and may raise concerns with heritage protection for listed dams. Addressing these challenges, electronic corner reflectors (ECRs) offer an effective alternative due to their small and compact size. In this study, we analyzed the strategic placement of ECRs on dam structures. We developed a new CR Index, which identifies areas where PSI alone is insufficient due to unfavorable geometric or land use conditions. This index categorizes visibility potential into three classes, presented in a ‘traffic light’ map, and is instrumental in selecting optimal installation sites. We furthermore investigated the signal stability of ECRs over an extended observation period, considering the Amplitude Dispersion Index (ADI). It showed values between 0.1 and 0.4 for many dam structures, which is comparable to normal corner reflectors (CRs), confirming the reliability of these signals for PSI analysis. This work underscores the feasibility of using ECRs to enhance monitoring capabilities at dam infrastructure. Full article

Integrated Sensing and Communication (ISAC) is an important trend for future commutation networks. The Communication Base Station (CBS) can be used as a Ground-Based Synthetic Aperture Radar (GB-SAR). By using Synthetic Aperture Radar (SAR) images obtained at a different time, GB-SAR will have the ability to detect millimeter-level ground deformations with Interferometric SAR (InSAR) processing through a phase difference operation. In this paper, we investigated the observation and performance for millimeter-level ground deformation detection based on the CBS with Differential InSAR (D-InSAR) for the first time. Building on the characteristics of short temporal sampling intervals, an in-depth investigation was conducted into the process of detecting deformations using the CBS. A practical experimental scenario was established, and the high coherence between adjacent images resulting from short temporal sampling intervals was leveraged to enhance the phase Signal-to-Noise Ratios (SNRs) through time series Differential Interferometric Phase sample averaging. On this basis, the first experimental result is given, which indicates that CBS can accurately capture millimeter-level deformations with a maximum error of 0.3437 mm. The experimental results confirm the feasibility and accuracy of employing CBSs as GB-SAR systems for monitoring ground deformations. Full article

China’s first L-band fully polarimetric Synthetic Aperture Radar (SAR) constellation, LuTan-1 (LT-1), was designed for terrain mapping and geohazard monitoring. This study evaluates LT-1’s capability in identifying landslides in the southern hilly regions of China, focusing on Longshan County, Hunan Province. Using both ascending and descending orbit data from LT-1, we conducted landslide identification experiments. First, deformation was obtained using Differential Interferometric SAR (D-InSAR) technology, and the deformation rates were derived through the Stacking technique. A landslide identification method that integrates C-index, slope, and ascending/descending orbit deformation information was then applied. The identified landslides were validated against existing geohazard points and medium-to-high-risk slope and gully unit data. The experimental results indicate that LT-1-ascending orbit data identified 88 landslide areas, with 39.8% corresponding to geohazard points and 65.9% within known slope units. Descending orbit data identified 90 landslide areas, with 37.8% matching geohazard points and 61.1% within known slope units. The identification results demonstrated good consistency with existing data. Comparative analysis with Sentinel-1 data revealed that LT-1’s combined ascending and descending orbit data outperformed Sentinel-1’s single ascending orbit data. LT-1’s L-band characteristics, comprehensive ascending and descending orbit coverage, and high-precision deformation detection make it highly promising for landslide identification in the southern hilly regions. This study underscores LT-1’s robust technical support for early landslide identification, highlighting its potential to enhance geohazard monitoring and mitigate risks in challenging terrains. Full article

On 7 January 2025, at Beijing time, an M_w7.1 earthquake occurred in Dingri County, Shigatse, Tibet. To accurately determine the fault that caused this earthquake and understand the source mechanism, this study utilized Differential Interferometric Synthetic Aperture Radar (DInSAR) technology to process Sentinel-A data, obtaining the line-of-sight (LOS) co-seismic deformation field for this earthquake. This deformation field was used as constraint data to invert the geometric parameters and slip distribution of the fault. The co-seismic deformation field indicates that the main characteristics of the earthquake-affected area are vertical deformation and east-west extension, with maximum deformation amounts of 1.6 m and 1.0 m for the ascending and descending tracks, respectively. A Bayesian method based on sequential Monte Carlo sampling was employed to invert the position and geometric parameters of the fault, and on this basis, the slip distribution was inverted using the steepest descent method. The inversion results show that the fault has a strike of 189.2°, a dip angle of 40.6°, and is classified as a westward-dipping normal fault, with a rupture length of 20 km, a maximum slip of approximately 4.6 m, and an average slip angle of about −82.81°. This indicates that the earthquake predominantly involved normal faulting with a small amount of left–lateral strike–slip, corresponding to a moment magnitude of M_w7.1, suggesting that the fault responsible for the earthquake was the northern segment of the DMCF (Deng Me Cuo Fault). The slip distribution results obtained from the finite fault model inversion show that this earthquake led to a significant increase in Coulomb stress at both ends of the fault and in the northeastern–southwestern region, with stress loading far exceeding the earthquake triggering threshold of 0.03 MPa. Through analysis, we believe that this Dingri earthquake occurred at the intersection of a “Y”-shaped structural feature where stress concentration is likely, which may be a primary reason for the frequent occurrence of moderate to strong earthquakes in this area. Full article

The Himalayan belt, formed due to the Cenozoic convergence between the Eurasian and Indian craton, acts as a storehouse of large amounts of strain, resulting in large earthquakes from the Western to the Eastern Himalayas. Glaciers also occur over a major portion of the high-altitude Himalayan region. The impact of earthquakes can be easily studied in the plains and plateaus with the help of well-distributed seismogram networks and these regions’ accessibility is helpful for field- and lab-based studies. However, earthquakes triggered close to high-altitude Himalayan glaciers are tough to investigate for the impact over glaciers and glacial deposits. In this study, we attempt to understand the impact of earthquakes on and around Himalayan glaciers in terms of vertical displacement and coherence change using space-borne synthetic aperture radar (SAR). Eight earthquake events of various magnitudes and hypocenter depths occurring in the vicinity of Himalayan glacial bodies were studied using C-band Sentinel1-A/B SAR data. Differential interferometric SAR (DInSAR) analysis is applied to capture deformation of the glacial surface potentially related to earthquake occurrence. Glacial displacement varies from −38.9 mm to −5.4 mm for the 2020 Tibet earthquake (M_w 5.7) and the 2021 Nepal earthquake (M_w 4.1). However, small glacial and ground patches processed separately for vertical displacements reveal that the glacial mass shows much greater seismic displacement than the ground surface. This indicates the possibility of the presence of potential site-specific seismicity amplification properties within glacial bodies. A reduction in co-seismic coherence around the glaciers is observed in some cases, indicative of possible changes in the glacial moraine deposits and/or vegetation cover. The effect of two different seismic events (the 2020 and 2021 Nepal earthquakes) with different hypocenter depths but with the same magnitude at almost equal distances from the glaciers is assessed; a shallow earthquake is observed to result in a larger impact on glacial bodies in terms of vertical displacement. Earthquakes may induce glacial hazards such as glacial surging, ice avalanches, and the failure of moraine-/ice-dammed glacial lakes. This research may be able to play a possible role in identifying areas at risk and provide valuable insights for the planning and implementation of measures for disaster risk reduction. Full article

Monitoring and analyzing reservoir landslides are essential for predicting and mitigating geohazards, which are crucial for maintaining sustainability and supporting socio-economic development in reservoir areas. High spatiotemporal resolution is vital for effective reservoir landslide monitoring and analysis. For this purpose, we improved the resolution of the differential interferometric synthetic aperture radar (DInSAR) technique by fusing two-path deformation results from an overlapping Sentinel-1 area. First, we summarized the mathematical ratio relationship between deformation from the two paths. Second, time-series linear interpolation and time-reference difference removal were applied to the two separate deformation results of time-series DInSAR. Third, a ratio algorithm was adopted to fuse the deformation of the two paths into one integrated time-series result. The standard deviations of the deformation before and after fusion were similar, confirming the accuracy of the fusion results and feasibility of the method. From the integrated deformation, we analyzed the hydraulic impact, mechanisms, and physical processes associated with four reservoir landslides in the Three Gorges Reservoir area of China, accounting for rainfall and water-level data. The comprehensive analysis presented herein provides new insights on the hydraulic mechanisms of reservoir landslides and verifies the efficacy of this new integrated method for landslide investigation and monitoring. Full article

The conventional Structural Health Monitoring (SHM) framework focuses on individual structures. However, preliminary studies are required at a large territorial scale to effectively identify the most vulnerable elements. This becomes particularly challenging in urban settings, where numerous buildings of varied shapes, ages, and structural conditions are closely spaced from one another. A twofold task is therefore required: the automated identification and differentiation of various structures, coupled with a ranking system based on perceived structural risk, here assumed to be linked to their deformation patterns. It integrates displacement measurements acquired through the Differential Synthetic Aperture Radar Interferometry (DInSAR) technique, specifically employing the full-resolution Small Baseline Subset (SBAS) approach coupled with Hierarchical Clustering. The effectiveness of this method is successfully demonstrated and validated in two selected areas of Rome, Italy, serving as case studies. The results of this vast-area scale monitoring can be used to select the constructions that need a more in-depth assessment. Full article

On 23 January 2024, an M_w 7.01 earthquake struck the Wushi County, Xinjiang Uygur Autonomous Region, China. The occurrence of this earthquake provides an opportunity to gain a deeper understanding of the rupture behavior and tectonic activity of the fault system in the Tianshan seismic belt. The coseismic deformation field of the Wushi earthquake was derived from Sentinel-1A ascending and descending track data using Differential Interferometric Synthetic Aperture Radar (D-InSAR) technology. The findings reveal a maximum line-of-sight (LOS) displacement of 81.1 cm in the uplift direction and 16 cm in subsidence. Source parameters were determined using an elastic half-space dislocation model. The slip distribution on the fault plane for the M_w 7.01 Wushi earthquake was further refined through a coseismic slip model, and Coulomb stress changes on nearby faults were calculated to evaluate seismic hazards in surrounding areas. Results indicate that the coseismic rupture in the M_w 7.01 Wushi earthquake sequence was mainly characterized by left-lateral strike-slip motion. The peak fault slip was 3.2 m, with a strike of 228.34° and a dip of 61.80°, concentrated primarily at depths between 5 and 25 km. The focal depth is 13 km. This is consistent with findings reported by organizations like the United States Geological Survey (USGS). The fault rupture extended to the surface, consistent with field investigations by the Xinjiang Uygur Autonomous Region Earthquake Bureau. Coulomb stress results suggest that several fault zones, including the Kuokesale, Dashixia, Piqiang North, Karaitike, southeastern sections of the Wensu, northwestern sections of the Tuoergan, and the Maidan-Sayram Fault Zone, are within regions of stress loading. These areas show an increased risk of future seismic activity and warrant close monitoring. Full article

The LuTan-1 (LT-1) satellite, launched in 2022, is China’s first L-band full-polarimetric Synthetic Aperture Radar (SAR) constellation, boasting interferometry capabilities. However, given its limited use in subsidence monitoring to date, a comprehensive evaluation of LT-1’s interferometric quality and capabilities is necessary. In this study, we utilized the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique to analyze mining-induced subsidence results near Shenmu City (China) with LT-1 data, revealing nine subsidence areas with a maximum subsidence of −19.6 mm within 32 days. Furthermore, a comparative analysis between LT-1 and Sentinel-1 data was conducted focusing on the aspects of subsidence results, interferometric phase, scattering intensity, and interferometric coherence. Notably, LT-1 detected some subsidence areas larger than those identified by Sentinel-1, attributed to LT-1’s high resolution, which significantly enhances the detectability of deformation gradients. Additionally, the coherence of LT-1 data exceeded that of Sentinel-1 due to LT-1’s L-band long wavelength compared to Sentinel-1’s C-band. This higher coherence facilitated more accurate capturing of differential interferometric phases, particularly in areas with large-gradient subsidence. Moreover, the quality of LT-1’s monitoring results surpassed that of Sentinel-1 in root mean square error (RMSE), standard deviation (SD), and signal-to-noise ratio (SNR). In conclusion, these findings provide valuable insights for future subsidence-monitoring tasks utilizing LT-1 data. Ultimately, the systematic differences between LT-1 and Sentinel-1 satellites confirm that LT-1 is well-suited for detailed and accurate subsidence monitoring in complex environments. Full article

Coal mining-induced ground subsidence is a severe hazard that can damage property, infrastructure, and the environment in the vicinity when the deformation is not negligible. The boundary of a mining-induced subsidence-affected zone refers to the area beyond which the ground subsidence is less concerned. Accurately measuring mining-induced ground deformation is essential for delineating the irregular boundary of the impacted area. This study employs multitemporal interferometric synthetic aperture radar (MT-InSAR) techniques, including differential InSAR (DInSAR), InSAR stacking, and interferometric point target analysis (IPTA), to analyze coal mine subsidence and delineate the boundaries of the mining-impacted zones. DInSAR accurately reconstructs, locates, and detects the trend in mining-induced subsidence and correlates well with documented mining operations. The InSAR stacking method maps the spatial variation of the ground’s average line-of-sight (LOS) velocity over the mining area, delineating the boundary of the impacted zone. IPTA analysis combining multilook and single-pixel phases achieves millimeter-level surface measurement above tunnel alignments and measures unevenly distributed deformation fields. This study considers an average of 4 cm per year of surface deformation in the LOS direction as the subsidence threshold value for delineating the boundary of the mining-induced subsidence-affected (MISA) zone during the active coal mining stage. Interestingly, there are twin transportation tunnels near the mining area. The twin tunnels completed before the coal mining activities started were functioning well, but damage was observed after the mining began. Our study reveals the tunnels are located within the InSAR-derived MISA zone, although the tunnels approach the MISA boundary. As direct signs of subsidence, ground fissures have been identified near the tunnels via field investigations and UAV photogrammetry. Furthermore, the derived distribution of ground fissures validates and verifies InSAR measurements. The integrated approach of MT-InSAR, UVA photogrammetry, and field investigation developed in this study can be applied to delineate the irregular boundary of the MISA zone and study the accumulating effects of mining-induced subsidence on the performance of infrastructure in areas proximate to coal mining activities. Full article

Monitoring three-dimensional (3D) deformation in underground mining areas is crucial for the prevention and control of mining-induced disasters. Differential interferometric synthetic aperture radar (D-InSAR) is limited to detecting one-dimensional (1D) deformation along the line of sight (LOS). This paper proposes a new method for extracting 3D mining-induced deformation based on the differentiability of D-InSAR LOS deformation fields. The method approximates the D-InSAR LOS deformation field in underground mining areas as a differentiable function and constructs a 3D deformation extraction model utilizing directional derivatives of this function. The least squares method is used for estimating and evaluating the 3D deformation. Simulation and real data experiments have been used to verify the feasibility of the method in extracting mining-induced 3D deformation. The simulation results show relative root mean square errors (RRMSES) of 1.24%, 6.05%, 0.97%, and 11.47% for vertical and horizontal displacements along the east–west and south–north directions, respectively. The real data experiments using Sentinel-1 images show that the root mean square errors (RMSES) of the up–down, south–north, and east–west directions are 14.06 mm, 7.37 mm, and 11.56 mm, respectively. Experimental results show that the method can provide a certain basis for 3D surface deformation monitoring of mining subsidence. Full article

Advanced statistics can enable the detailed characterization of ground deformation time series, which is a fundamental step for thoroughly understanding the phenomena of land subsidence and their main drivers. This study presents a novel methodological approach based on pre-existing open-access statistical tools to exploit satellite differential interferometric synthetic aperture radar (DInSAR) data to investigate land subsidence processes, using European Ground Motion Service (EGMS) Sentinel-1 DInSAR 2018−2022 datasets. The workflow involves the implementation of Persistent Scatterers (PS) time series classification through the PS-Time tool, deformation signal decomposition via independent component analysis (ICA), and drivers’ investigation through spatio-temporal correlation with geospatial and monitoring data. Subsidence time series at the three demonstration sites of Bologna, Ravenna and Carpi (Po Plain, Italy) were classified into linear and nonlinear (quadratic, discontinuous, uncorrelated) categories, and the mixed deformation signal of each PS was decomposed into independent components, allowing the identification of new spatial clusters with linear, accelerating/decelerating, and seasonal trends. The relationship between the different independent components and DInSAR-derived displacement velocity, acceleration, and seasonality was also analyzed via regression analysis. Correlation with geological and groundwater monitoring data supported the investigation of the relationship between the observed deformation and subsidence drivers, such as aquifer resource exploitation, local geological setting, and gas extraction/reinjection. Full article

Orbit error is one of the primary error sources of interferometric synthetic aperture radar (InSAR) and differential InSAR (D-InSAR) measurements, arising from inaccurate orbit determination of SAR platforms. Typically, orbit error in the interferogram can be estimated using polynomial models. However, correcting for orbit errors with significant time-varying characteristics presents two main challenges: (1) the complexity and variability of the azimuth time-varying orbit errors make it difficult to accurately model them using a set of polynomial coefficients; (2) existing patch-based polynomial models rely on empirical segmentation and overlook the time-varying characteristics, resulting in residual orbital error phase. To overcome these problems, this study proposes an automated block adjustment framework for estimating time-varying orbit errors, incorporating the following innovations: (1) the differential interferogram is divided into several blocks along the azimuth direction to model orbit error separately; (2) automated segmentation is achieved by extracting morphological features (i.e., peaks and troughs) from the azimuthal profile; (3) a block adjustment method combining control points and connection points is proposed to determine the model coefficients of each block for the orbital error phase estimation. The feasibility of the proposed method was verified by repeat-pass L-band spaceborne and P-band airborne InSAR data, and finally, the InSAR digital elevation model (DEM) was generated for performance evaluation. Compared with the high-precision light detection and ranging (LiDAR) elevation, the root mean square error (RMSE) of InSAR DEM was reduced from 18.27 m to 7.04 m in the spaceborne dataset and from 7.83~14.97 m to 3.36~6.02 m in the airborne dataset. Then, further analysis demonstrated that the proposed method outperforms existing algorithms under single-baseline and single-polarization conditions. Moreover, the proposed method is applicable to both spaceborne and airborne InSAR data, demonstrating strong versatility and potential for broader applications. Full article