Search Results (130)

The use of satellite Differential Synthetic Aperture Radar Interferometry (DInSAR) has transformed the analysis of landslide dynamics by enabling detailed spatiotemporal monitoring of slow and subtle ground deformations. DInSAR enables comprehensive geomorphological characterization and identification of triggering factors. Retrospective applications of DInSAR provide valuable insights into past events and support causal analysis linked to rainfall episodes or piezometric fluctuations. Moreover, integration with numerical modeling enhances predictive capabilities and facilitates the calibration of geotechnical parameters. DInSAR is also instrumental in assessing infrastructure impacts and in the generation of susceptibility, hazard, vulnerability, and risk maps, which are key for land-use planning and risk management. Nevertheless, this technique has inherent limitations that must be carefully considered when interpreting results. Future developments, driven by the integration of artificial intelligence and enhanced computing capacities, are transforming the landscape of InSAR applications in landslide studies. These advancements, combined with upcoming satellite missions, are expected to significantly improve measurement accuracy, temporal resolution, and overall operational potential, paving the way for more robust quasi-early warning systems for landslide prevention. In this work, an overview of the current applications, future trends, and challenges of DInSAR in landslide studies is presented, with particular emphasis on the practical dimension of landslide studies and on the exploitation of DInSAR outcomes to support risk management and mitigation strategies. Full article

Accurately characterizing the kinematics of slow-moving urban landslides remains a major scientific and operational challenge, because no single monitoring technique can simultaneously provide spatially continuous deformation patterns and reliable three-dimensional displacement measurements. This study investigates the spatial and temporal evolution of a slow-moving landslide affecting the University of Azuay campus in Cuenca (Ecuador), where ongoing ground deformation has caused structural damage to several buildings. An integrated monitoring strategy combining GNSS measurements, Sentinel-1 multi-temporal DInSAR analysis, and geophysical investigations (ERT and seismic profiling) was adopted to characterize landslide kinematics and constrain subsurface conditions. GNSS observations revealed that the north–south displacement component was dominant, with cumulative displacements exceeding 20 cm during the monitoring period (from July 2021 to June 2024), while east–west displacements were on the order of 10 cm. MT-DInSAR analysis delineated the spatial extent of the unstable area and identified mean deformation rates of up to approximately −1.5 cm/year in the central sector of the landslide. The combined interpretation of geodetic and geophysical data indicates that slope instability is controlled by saturated fine-grained layers and mechanical contrasts, with the basal sliding zone associated with weak levels of the Mangan Formation. Overall, the results demonstrate the value of a multi-sensor, component-wise monitoring strategy for improving the reliability of deformation estimates and for supporting landslide risk assessment and land-use planning in complex urban environments. Full article

High-intensity mining activities in coal mining areas have produced large-gradient surface deformation, posing severe challenges to deformation monitoring using Interferometric Synthetic Aperture Radar (InSAR) techniques based on C-band Synthetic Aperture Radar (SAR) data. This study systematically evaluated the applicability of L-band LuTan-1 SAR (L-SAR) data versus C-band Sentinel-1A data for monitoring mining-induced surface deformation, using the Guqiao Coal Mine in Huainan as the study area. Based on 10 ascending-track and 13 descending-track L-SAR images and 42 Sentinel-1A images, deformation retrievals were performed using Differential InSAR (DInSAR) and the Small Baseline Subset (SBAS) InSAR approach, respectively, and the results were validated against independent levelling measurements. Results indicate that the mean coherence of descending- and ascending-track L-SAR interferometric pairs are 0.42 and 0.45, respectively, substantially higher than Sentinel-1A’s 0.25. In the DInSAR analysis along profile A–A′, the maximum line-of-sight (LOS) displacement obtained from descending- and ascending-track L-SAR are −0.40 m and −0.43 m, respectively, compared with −0.25 m from Sentinel-1A. In the SBAS-InSAR time-series analysis, descending- and ascending-track L-SAR yield 209,418 and 228,388 coherent points, respectively, clearly revealing the temporal evolution of surface deformation; their maximum LOS deformation rates are approximately −1.54 m·yr⁻¹ and −2.0 m·yr⁻¹, respectively. By contrast, Sentinel-1A selects only 81,669 coherent points, with severe loss of coherence in the subsidence center and a maximum LOS deformation rate of about −0.48 m·yr⁻¹. Accuracy validation shows that the Root Mean Square Error (RMSE) of vertical displacements obtained from DInSAR monitoring results based on descending and ascending L-SAR data is 16.1 mm, satisfying the requirement of centimeter-level accuracy for mining area surface subsidence monitoring. The study demonstrates the pronounced advantages of L-SAR for monitoring large-gradient, nonlinear deformation in mining environments. L-band data outperform C-band Sentinel-1A across coherence preservation, deformation sensitivity, and monitoring accuracy, providing a scientific basis for the broader application of domestic L-band SAR satellites in disaster risk assessment and long-term time-series monitoring of mining-induced subsidence. Full article

This study proposes a feature-level fusion method that integrates Differential Interferometric Synthetic Aperture Radar (D-InSAR) and Unmanned Aerial Vehicle photogrammetry (UAV-P) for monitoring mining-induced subsidence basin (MSB). The method begins by extracting key subsidence characteristics based on the patterns of coal-mining-related surface displacement; the centimeter-level subsidence boundary is determined from D-InSAR data, while the meter-scale deformation at the subsidence center is derived from UAV-P. These extracted features are then used to invert the parameters of the probability integral method (PIM). The subsidence basin predicted by the inverted parameters serves as a criterion to select the superior dataset between the D-InSAR and UAV-derived results. Finally, the selected subsidence data are fused to generate a composite subsidence map. The proposed method was applied to the 2S201 panel in the Wangjiata Coal Mine using eight Sentinel-1A images and two UAV surveys. The fusion results were evaluated for their regional and overall accuracy against 30 ground control points measured by total station and GPS. The results demonstrate that the fusion method not only accurately extracts large-scale deformations in the mining area, with a maximum subsidence of 2.5 m and a root mean square error (RMSE) of 0.277 m in the subsidence center area, but also precisely identifies the subsidence boundary region with an accuracy of 0.039 m. The fused subsidence basin exhibits an overall accuracy of 0.182 m, which represents a significant improvement of 83.6% and 27.8% over the results obtained using D-InSAR and UAV alone, respectively. This method effectively reconstructs the complete morphology of the mining-induced subsidence basin, confirming its feasibility for practical applications. Full article

Within the field of the structural monitoring of bridges, numerous technologies and methodologies have been developed. Among these, methods based on synthetic aperture radar (SAR) which utilise satellite data from missions such as Sentinel-1 (European Space Agency-ESA) and COSMO-SkyMed (Agenzia Spaziale Italiana—ASI) to capture displacements, temperature-related changes, and other geophysical measurements have gained increasing attention. However, SAR has yet to establish its value and potential fully; its broader adoption hinges on consistently demonstrating its robustness through recurrent applications, well-defined use cases, and effective strategies to address its inherent limitations. This study presents a systematic literature review (SLR) conducted in accordance with key stages of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 framework. An initial corpus of 1218 peer-reviewed articles was screened, and a final set of 25 studies was selected for in-depth analysis based on citation impact, keyword recurrence, and thematic relevance from the last five years. The review critically examines SAR-based techniques—including Differential Interferometric SAR (DInSAR), multi-temporal InSAR (MT-InSAR), and Persistent Scatterer Interferometry (PSI), as well as approaches to integrating SAR data with ground-based measurements and complementary digital models. Emphasis is placed on real-world case studies and persistent technical challenges, such as atmospheric artefacts, Line-of-Sight (LOS) geometry constraints, phase noise, ambiguities in displacement interpretation, and the translation of radar-derived deformations into actionable structural insights. The findings underscore SAR’s significant contribution to the structural health monitoring (SHM) of bridges, consistently delivering millimetre-level displacement accuracy and enabling engineering-relevant interpretations. While standalone SAR-based techniques offer wide-area monitoring capabilities, their full potential is realised only when integrated with complementary procedures such as thermal modelling, multi-sensor validation, and structural knowledge. Finally, this document highlights the persistent technical constraints of InSAR in bridge monitoring—including measurement ambiguities, SAR image acquisition limitations, and a lack of standardised, automated workflows—that continue to impede operational adoption but also point toward opportunities for methodological improvement. Full article

In recent years, differential synthetic aperture radar interferometry (DInSAR) has been widely used to monitor ground deformation induced by mineral resource exploitation. Compared with conventional DInSAR, InSAR time series (TS-InSAR) techniques offer significantly improved monitoring accuracy. However, their results still remain strongly influenced by atmospheric delays. To address this and discuss the applicability of tropospheric delay correction methods over mining areas, this study applied multiple correction strategies to distributed scatterer InSAR (DS-InSAR), including the Linear, ERA5, GACOS, spatio-temporal filtering method, and their adaptive weighted fusion approach. Meanwhile, an improved Common Scene Stacking (CSS) InSAR tropospheric delay correction method has been proposed. These methods’ performance have been evaluated by the quantitative comparisons of the corrected interferometric phases and by in situ measurements. The results indicated that the adaptive fusion method outperformed any individual model included, where spatio-temporal filtering should be applied with caution, as it may undermine part of the deformation signal. The effectiveness of ERA5 and GACOS is limited due to their resolution mismatch with that of the SAR images. On the other hand, the improved CSS method achieved the best results over the study area, with an average reduction of 32.22% in the RMSE of the interferometric phase, resulting in an RMSE below 8 mm on average and as low as 5 mm over certain areas. Thus, over local mining areas with large-magnitude and ground deformation, the improved CSS outperforms all the other compared methods, where it can effectively mitigate atmospheric delays while preserving the deformation signals. Full article

Subsidence over abandoned goaves is a primary trigger for secondary geological hazards such as surface collapse, landslides, and cracking. This threatens safe mining operations, impairs regional economic progress, and endangers local inhabitants and their assets. At present, goaf areas are mainly treated through grouting. However, owing to the deficiencies of traditional deformation monitoring methods (e.g., leveling and GPS), including their slow speed, high cost, and limited data accuracy influenced by the number of monitoring points, the surface deformation features of goaf zones treated with grouting cannot be obtained in a timely fashion. Therefore, this study proposes a method to analyze the spatio-temporal patterns of surface deformation in grout-filled goaves based on the fusion of Multi-temporal InSAR technologies, leveraging the complementary advantages of D-InSAR, PS-InSAR, and SBAS-InSAR techniques. An investigation was conducted in a coal mine located in Shandong Province, China, utilizing an integrated suite of C-band satellite data. This dataset included 39 scenes from the RadarSAT-2 and 40 scenes from the Sentinel missions, acquired between September 2019 and September 2022. Key results reveal a significant reduction in surface deformation rates following grouting operations: pre-grouting deformation reached up to −98 mm/a (subsidence) and +134 mm/a (uplift), which decreased to −11.2 mm/a and +18.7 mm/a during grouting, and further stabilized to −10.0 mm/a and +16.0 mm/a post-grouting. Time-series analysis of cumulative deformation and typical coherent points confirmed that grouting effectively mitigated residual subsidence and induced localized uplift due to soil compaction and fracture expansion. The comparison with the leveling measurement data shows that the accuracy of this method meets the requirements, confirming the method’s efficacy in capturing the actual ground dynamics during grouting. It provides a scientific basis for the safe expansion of mining cities and the safe reuse of land resources. Full article

In the semi-desert aeolian sand areas of Northern China, surface deformation monitoring with SAR is challenged by loss of coherence due to mobile dunes, seasonal vegetation changes, and large-gradient, nonlinear subsidence from underground mining. This study utilizes PALSAR-2 (L-band, 3 m resolution) and Sentinel-1 (C-band, 30 m resolution) data, applying InSAR and Offset tracking methods combined with differential, Stacking, and SBAS techniques to analyze deformation monitoring effectiveness and propose an efficient dynamic monitoring strategy for the Shendong Coalfield. The main conclusions can be summarized as follows: (1) PALSAR-2 data, which has advantages in wavelength and resolution (L-band, multi-look spatial resolution of 3 m), exhibits better interference effects and deformation details compared to Sentinel-1 data (C-band, multi-look spatial resolution of 30 m). The highly sensitive differential-InSAR (D-InSAR) can promptly detect new deformations, while Stacking-InSAR can accurately delineate the range of rock strata movement. SBAS-InSAR can reflect the dynamic growth process of the deformation range as a whole, and SBAS-Offset is suitable for observing the absolute values and morphology of the surface moving basin. The combined application of Stacking-InSAR and Stacking-Offset methods can accurately acquire the three-dimensional deformation field of mining-induced strata movement. (2) The spatiotemporal process of surface deformation caused by coal mining-induced strata movement revealed by InSAR exhibits good correspondence with both the underground mining progress and the development of ground fissures identified in UAV images. (3) The maximum displacement along the line of sight (LOS) measured in the mining area is approximately 2 to 3 m, which is close to the 2.14 m observed on site and aligns with previous studies. The calculated advance influence angle of the No. 22308 working face in the study area is about 38.3°. The influence angle on the solid coal side is 49°, while that on the goaf side approaches 90°. These findings further deepen the understanding of rock movement and surface displacement parameters in this region. The dynamic monitoring strategy proposed in this study is cost-effective and operational, enhancing the observational effectiveness of InSAR technology for surface deformation due to coal mining in this area, and it enriches the understanding of surface strata movement patterns and parameters in this region. Full article

An effective understanding of sediment deposition and erosion in river basins, particularly floodplains, is critical for modeling geomorphic evolution, managing flood risks, and maintaining ecological integrity. However, most related studies have been limited to hydraulic or hydrodynamic modeling approaches. Therefore, this study integrated Sentinel-1 differential interferometric synthetic aperture radar (DInSAR) coherence, Sentinel-2 normalized difference vegetation index, and soil surface moisture index data with one-dimensional hydraulic modeling to assess flood-induced sediment deposition and erosion in the Gamcheon River basin under non-flood, short flood, and long flood scenarios. The DInSAR deformation analysis revealed a clear pattern of upstream erosion and downstream deposition during flood events, indicating a total depositional uplift of 0.33 m during the long flood scenario but dominant erosion with a total measured surface lowering of −2.03 m during the non-flood scenario. These results were highly consistent with the predictions from the hydraulic model and supported by the hysteresis curves for in situ suspended sediment concentration. The findings of this study demonstrate the effectiveness of the proposed integrated approach for quantifying floodplain sediment dynamics, offering particular application value in data-scarce or inaccessible floodplains. Furthermore, the proposed approach provides practical insights into sediment management, flood risk assessment, and ecosystem restoration efforts. Full article

The area encompassing the Campi Flegrei and Vesuvio volcanoes, situated approximately 25 km apart and bisected by the city of Naples, Italy, is recognised as one of the most hazardous regions globally. In recent decades, the Campi Flegrei caldera has undergone significant changes in its monitored geophysical, geochemical and geodetical signals. The most recent, ongoing unrest began in 2005, resulting in an uplift of over 150 centimetres in the area of maximum uplift. Previous analyses of deformation data from ERS/ENVISAT (available up to 2010) and Sentinel-1 (available since 2015) Synthetic Aperture Radar (SAR) imagery, as well as global navigation satellite system data, have suggested that the shape of the deformation field at Campi Flegrei has remained constant and that the area around Vesuvio experienced a slight subsidence in the early 2000s, concurrently with a change in the sign of the ground deformation (from subsidence to uplift) at Campi Flegrei. This study presents and provides the ground displacement time series obtained from RADARSAT-2 images of the entire volcanic area from 2010 to 2015, thus filling the temporal gap between the ERS/ENVISAT and Sentinel-1 missions. The time series were generated using a bespoke procedure, based on the Sentinel Application Platform and the GMTSAR software. The validity of the displacement time series has been confirmed through comparison with continuous Global Positioning System data from the Neapolitan Volcanoes Continuous GPS network. Analysis of RADARSAT-2 ground displacements indicates that velocities in the vicinity of Vesuvio were no greater than a few millimetres per year, and no discernible deformation pattern is evident. Consequently, given the uncertainty in Differential Interferometry Synthetic Aperture Radar (DInSAR) measurements, there is no evidence to suggest deformation activity close to Vesuvio between 2010 and 2015. In contrast to Vesuvio, significant deformation is evident in the Campi Flegrei area. The shape of the ground displacement field remained constant between 2010 and 2015, within the uncertainty of DInSAR measurements. The mean upward velocity reaches a maximum of approximately 5 cm y⁻¹, while the mean eastward velocity reaches 2.4 cm y⁻¹. 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

Snow water equivalent (SWE) can be estimated using Differential SAR Interferometry (DInSAR), which captures changes in snow depth and density between two SAR acquisitions. However, challenges arise due to SAR signal penetration into the snowpack and the intrinsic limitations of DInSAR measurements. This study addresses these issues and explores the use of multi-band SAR data to derive SWE maps in alpine regions characterized by steep terrain, small spatial extent, and a potentially heterogeneous snowpack. We first conducted a performance analysis to assess SWE estimation precision and the maximum unambiguous SWE variation, considering incidence angle, wavelength, and coherence. Based on these results, we selected C-band Sentinel-1 and L-band SAOCOM data acquired over alpine areas and applied tailored DInSAR processing. Atmospheric artifacts were corrected using zenith total delay maps from the GACOS service. Additionally, sensitivity maps were generated for each interferometric pair to identify pixels suitable for reliable SWE estimation. A comparative analysis of the C- and L-band results revealed several critical issues, including significant atmospheric artifacts, phase decorrelation, and phase unwrapping errors, which impact SWE retrieval accuracy. A comparison between our Sentinel-1-based SWE estimations and independent measurements over an instrumented site shows results fairly in line with previous works exploiting C-band data, with an RSME in the order of a few tens of mm. Full article

Monitoring the structural health of bridges in road infrastructure is crucial for ensuring public safety and efficient maintenance. This paper presents a multi-level semi-automatic methodology for bridge monitoring, using Multi-Temporal Differential SAR Interferometry (MT-DInSAR) data. The proposed approach requires a dataset of satellite-derived MT-DInSAR measurements for the Area of Interest. The methodology involves creating a georeferenced database of bridges which allows the filtering of measurement points (generally named Persistent Scatterers—PSs) using spatial queries. Since existing datasets often provide only point geometries for bridge locations, additional data sources such as OpenStreetMaps-derived repositories have been utilized to obtain linear representations of bridges. These linear features are segmented into 20 m sections, which are then converted into polygonal geometries by applying a uniform buffer. Spatial joining between the bridge polygons and PS datasets allows the extraction of key statistics, such as mean displacement velocity, PS density and coherence levels. Based on predefined velocity thresholds, warning flags are triggered, indicating the need for further in-depth analysis. Finally, an upscaling step is performed to provide a practical tool for infrastructure managers, visually categorizing bridges based on the presence of flagged pixels. The proposed approach facilitates large-scale bridge monitoring, supporting the early detection of potential structural issues. Full article

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

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