Ground Deformation Monitoring Research Articles

Understanding spatially nonstationary effects of natural and human-induced factors on land subsidence based on multi-temporal InSAR and multi-source geospatial data: a case study in the Guangdong-Hong Kong-Macao Greater Bay Area

ABSTRACTLand subsidence, a common geological phenomenon in deltaic regions, poses significant risks to infrastructures, environments, and human lives. Monitoring and understanding land subsidence are crucial for establishing resilient, adaptive, and sustainable environments. In this study, a robust multi-temporal interferometric synthetic aperture radar (MTInSAR) method was employed to monitor land subsidence in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) using 541 Sentinel-1 SAR images. Spatial auto- and cross-correlation analysis were applied to select the most reasonable explanatory variables from nine candidates in each city of the GBA. City-level geographically weighted regression (GWR) models were then constructed to explore the spatially nonstationary effects of natural and human-induced factors. The findings revealed subsidence velocities ranging from 0 to 83.7 mm/yr in the GBA from 2015 to 2021, with the dominant factors affecting subsidence varying among regions. Natural and human-related factors accounted for 51.13% and 48.87%, respectively. Further analysis of representative subsidence areas highlights the importance of continuous monitoring of ground deformation using MTInSAR, region-specific land subsidence mitigation strategies, and regular maintenance of urban infrastructure. These insights are valuable for policymakers and urban planners in comprehending the complex processes underlying land subsidence and informing decision-making processes for sustainable and resilient urban development.

Underground Gas Storage Monitoring Using Free and Open Source InSAR Data: A Case Study from Yela (Spain)

Gas consumption is subject to large seasonal fluctuations between the summer season (period with lower request) and the winter season (time with increased consumer demand). Underground gas storage applications (UGS) help to ensure a steady and reliable supply of natural gas, even during periods of peak demand, smoothing price fluctuations and providing a means of balancing the supply and demand of natural gas on a daily, weekly, or seasonal basis. However, UGS activities can induce vertical ground displacement, which is usually strictly associated with the injection and withdrawal of gas into/from the reservoir. It is necessary to carefully monitor and manage the potential impact of UGS activities on the subsurface and surface to ensure the stability and safety of the local environment. The Interferometric Synthetic Aperture Radar (InSAR) technique can provide a wide range of high-precision information on seasonal surface deformation associated with UGS activities useful for increasing the amount of information on ground deformation monitoring. This study introduces a unique and replicable approach to investigating freely available ground movement data for a fractured aquifer reservoir located in the Madrid Basin (Guadalajara, Spain), which is currently employed for seasonal underground gas storage applications. Notably, this study gives a comprehensive comparison of InSAR results of UGS activity in a deep aquifer, leveraging data that are entirely open-source and easily accessible. The Yela UGS project exploits a carbonate reservoir (dolomite) managed, since 2012, by Enagás, the Spanish main Transmission System Operator (TSO). InSAR data from 2015 to 2021 provided a full and coherent ground deformation pattern of the area. Based on this data, a fully integrated volumetric variation model was developed, elucidating the effects of gas storage activity. A significant correlation between the periodic injection/withdrawal rates of natural gas and InSAR ground deformation over time was identified.

A distributed fibre optic monitoring method for ground subsidence induced by water pipeline leakage

After a water supply pipeline experiences leakage due to damage, the surrounding soil is prone to erosion, leading to the formation of underground voids. As the voids gradually expand, there is a high possibility of triggering ground subsidence accidents. Monitoring ground deformation is the simplest and most effective method for capturing the process of ground subsidence development. Among various methods of ground deformation monitoring, distributed optical fibre sensing has advantages such as real-time performance, distributed measurement, and ease of networking. This paper investigates the monitoring effectiveness of distributed optical fibre strain sensing technology on ground subsidence induced by underground voids under different conditions through indoor model experiments. To convert the measured strain of the optical fibre into ground subsidence, this paper proposes a strain–displacement conversion method based on the sequence-to-sequence (Seq2Seq) model. The method is validated using data from indoor model experiments. The research results indicate that distributed optical fibre sensing technology can effectively monitor the strain distribution of soil during the subsidence process. It can identify the development location of ground subsidence and reveal the deformation evolution patterns. The strain–displacement intelligent conversion model based on Seq2Seq can convert the strain monitored by the optical fibre during the ground subsidence process into ground subsidence. Compared to traditional methods, this conversion model exhibits higher accuracy.

Megalopolitan-scale ground deformation along metro lines in the Guangdong-Hong Kong-Macao Greater Bay Area, China, revealed by MT-InSAR

As one of the most densely populated and rapidly growing metropolitan areas worldwide, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China has been developing extensive metro networks to relieve the escalating traffic congestion inner cities and to shorten public transport time inter cities. Metro construction possibly triggers ground deformation, which may result in damage to the tunnel, pipeline, and ground structures. Fast and efficient monitoring ground deformation along metro lines is vital not only to the metro itself but also to these structures. This study provides a comprehensive investigation of ground deformation along 67 metro lines within the GBA, based on multi-temporal synthetic aperture radar interferometry (MT-InSAR) by using Sentinel-1 from March 2017 to February 2022. The results reveal that deformation velocity in this area ranges from –39.4 mm/year to 14.2 mm/year, which is mainly caused by the tunnel excavation, adjacent excavation and construction, and unfavorable geological conditions. Furthermore, risk levels have been evaluated based on the InSAR-derived results with the proposed median absolute deviation heatmap clustering method. The risky area accounts for 16.31% (∼205.24 km2) of the whole study area in the GBA, among which 13.76%, 2.16%, and 0.39% are classified as three risk levels, with mean deformation velocities of –2.2 mm/year, –3.4 mm/year, and –6.5 mm/year, respectively. This study presents a comprehensive megalopolitan-scale ground deformation monitoring, for the first time, along metro lines in six cities of the GBA, which provides important insights into future metro line constructing, operating and planning.

COSMO-SKYMED: A SATELLITE TOOL FOR MONITORING CULTURAL HERITAGE

Abstract. COSMO-SkyMed is the flagship Synthetic Aperture Radar (SAR) satellite constellation of the Italian Space Agency (ASI) that, among the many civilian applications for which it was originally conceived, is nowadays successfully exploited for cultural heritage applications. Current capabilities offered by both the First and Second Generations satellites are reviewed in light of the experience undertaken by ASI through data exploitation initiatives with scientific and commercial users, and more importantly in the framework of institutional projects and cooperation agreements such as those with the Colosseum Archaeological Park and the Italian Ministry of Culture (MiC). The interferometric nature of COSMO-SkyMed SAR acquisitions is the key feature exploited in structural and ground deformation monitoring of monuments and historical buildings, so as the constellation is currently the essential Earth Observation asset supporting MiC’s Extraordinary Plan of Monitoring and Conservation of Immovable Cultural Heritage. Further applications that could be enabled by COSMO-SkyMed data are explored through internal ASI research activity, such as the use of high resolution Digital Elevation Models (DEM) for topographic surveying of archaeological tells and condition assessment to estimate the impact due to natural and anthropogenic threats (e.g. looting, agriculture, destruction). Finally, current perspectives towards operational use and greater user uptake of COSMO-SkyMed for purposes of scientific downstream are opened by the new ASI programme Innovation for Downstream Preparation for Science (I4DP_SCIENCE).

Surface Subsidence of Nanchang, China 2015–2021 Retrieved via Multi-Temporal InSAR Based on Long- and Short-Time Baseline Net

Urban land subsidence threatens the safety of urban buildings and people’s lives. The time series interferometric synthetic aperture radar (InSAR) technology can provide us with large-area, high-resolution, and high-precision ground deformation monitoring. In this study, the time series InSAR technology and the strategy with long- and short-time baseline networking are used to obtain the surface deformation along the line of sight of Nanchang City based on the six-year (from December 2015 to December 2021) Sentinel-1 data. Longer datasets and better baseline strategies allow us to obtain more stable deformation results of Nanchang City than other researchers. The results of surface deformation show that the overall surface of Nanchang City is stable, but there are several obvious subsidence funnels. We carried out a field survey on four areas with significant surface subsidence. We considered that these subsidence areas may be related to soil compaction, building construction, and groundwater extraction. Based on the surface deformation results around the subway line, we analyzed the impact of subway construction on the surface along the line and identified the sections that need to be focused on by the managers to prevent the deformation area from affecting the surrounding buildings and subway line operation safety.

VALIDATING THE EUROPEAN GROUND MOTION SERVICE: AN ASSESSMENT OF MEASUREMENT POINT DENSITY

Abstract. The European Ground Motion Service (EGMS) is an operational data service that uses interferometric analysis of Sentinel-1 radar images to provide high-resolution monitoring of ground deformation. The service is the first continental ground motion public dataset that is open and available for various applications and studies. This paper presents the validation workflow of the EGMS product in terms of spatial coverage and density of measurement points. The study employs open land cover data to evaluate the density per class and proposes statistical parameters associated with the data processing and timeseries estimation to ensure consistency across different selected sites.The validation process involves twelve selected sites across Europe, representing the four processing entities, covering both rural and urban areas. The paper highlights the importance of ensuring completeness and consistency of the EGMS product for its effective use, along with pointwise quality measures critical in assessing the quality of the EGMS point timeseries results. Additionally, the paper discusses the challenges faced during the pre-processing of the data from EGMS and presents a custom algorithm designed to eliminate biases in the data. As an open and freely available dataset, the EGMS will provide valuable resources for further research and applications, enabling better understanding and management of geohazards, environmental monitoring, and urban planning.

Dam Deformation Monitoring using Cloud-Based P-SBAS Algorithm: The Kramis Dam Case (Algeria)

This paper presents the application of the Parallel Small Baseline Subset (P-SBAS) algorithm, provided by the Geohazards Exploitation Platform for the precise monitoring of an earth dam's ground deformation using C-band Sentinel-1 data. The test site object of this study was the Kramis dam, located in the Mostaganem State, Western Algeria. Among the multiple advanced DInSAR techniques, SBAS is very adequate for long-term displacement monitoring in areas with changing terrain and vegetation. Ten corner reflectors were installed as a backscattered radar signal amplification tool to reduce the effect of temporal decorrelation and delineate the dam area. Four Sentinel-1 A and B satellite tracks were available (T30, T37, T103, and T110) to measure displacements, in the Line of Site (LoS) direction, for two years since the installation of the CRs in July 2019. The results showed a subsiding area on the left bank of the dam dike, with a velocity of 4mm/yr, and an uplifting rate of 3-4mm/yr in the upper part of the dike. The entire 3-dimensional vector of displacement of the dam vicinity was estimated using the least-squares method, proving a better understanding of the dam's temporal deformation, particularly for dams with a high exposure factor and associated risk.

The Influence of Horizon Xiv’s Exploitation on the Stability of Surface at Slănic Prahova Mine

Abstract The exploitation of the XIV horizon, in two slices, across the entire mining perimeter of the Slănic Prahova Salt Mine until the end of 2059 will result in the amplification of surface subsidence, already affected by the mining operations of Victoria, Cantacuzino, and Old Mines. Systematic annual monitoring of ground deformation has been conducted since 2004 through geometric leveling along selected representative alignments, which were utilized to forecast the temporal evolution of surface subsidence and the impact of mining the XIV horizon. Furthermore, 3D numerical modeling was employed to estimate the subsidence and ground displacements.

Observation of spatial and temporal patterns of seasonal ground deformation in central Yakutia using time series InSAR data in the freezing season

The seasonal freeze/thaw variations of the active layer cause seasonal ground deformation, such as thaw subsidence in summer and frost heave in winter due to the cyclic phase changes of soil water. The Synthetic Aperture Radar (SAR) remote sensing, especially interferometric SAR (InSAR) techniques, has been proven to be a very useful tool for observing surface displacements of permafrost environments. Most previous studies on seasonal InSAR displacement have been concentrated in several study sites in the Arctic tundra regions. The objective of this study is to extend the InSAR analysis of seasonal ground deformations to boreal forest regions, where monitoring ground deformation is particularly important in terms of better understanding active layer dynamics under various ecological and geological conditions. In this study, we presented a strategy to analyze the time series SAR data in the freezing season to estimate the differential phase for seasonal ground deformation while overcoming the problem of coherence losses due to the rapid growth of vegetation during the short growing season. We applied the SBAS-based InSAR processing method to Sentinel-1 SAR in the central Yakutian lowlands, where boreal forests and thermokarst landforms are widely distributed, and retrieved frost-related displacement signals successfully. In addition to the magnitude of ground deformation in the freezing season, we further examined the temporal deformation pattern related to the progression of the freezing front in the soil during active freezing. Based on the Stefan solution, we proposed a piecewise linear model for the time series deformation. The proposed model divides the time series displacement according to the progression of freezing into three linear segments, and the slope parameter of each linear model can be interpreted as indicating the hydrological characteristics of the upper, middle, and lower parts of the soil. The results for the Yakutian lowlands illustrated the potential of SAR remote sensing to observe and quantify spatial details of the thermal and hydrological properties inside the active layer soil even in highly vegetated subarctic boreal forest areas.

Research on regionalised digital image slope monitoring methods.

The digital image correlation method is a high precision and non-contact ground deformation monitoring method, which is widely used in surface deformation monitoring. However, according to its principle, different surface characteristics have great influence on the monitoring results. In this paper, a regional digital image slope monitoring method is established to meet the monitoring requirements of different areas of the same slope. Firstly, the features of different regions in the image are identified according to the optical region detection, and then the deformation calculation method is matched according to the features of different regions. Finally, according to the binocular vision principle, the three-dimensional displacement of the slope is obtained. Taking a highway slope in Qinhuangdao as an example, we realised all-weather and full-field deformation monitoring of slope, and verified the applicability and feasibility of regional digital image slope monitoring method. The applicability of digital image correlation method in slope monitoring is improved.

EZ-InSAR: An easy-to-use open-source toolbox for mapping ground surface deformation using satellite interferometric synthetic aperture radar

Satellite Interferometric Synthetic Aperture Radar (InSAR) is a space-borne geodetic technique that can map ground displacement at millimetre accuracy. Via the new era for InSAR applications provided by the Copernicus Sentinel-1 SAR satellites, several open-source software packages exist for processing SAR data. These packages enable one to obtain high-quality ground deformation maps, but still require a deep understanding of InSAR theory and the related computational tools, especially when dealing with a large stack of images. Here we present an open-source toolbox, EZ-InSAR (easy-to-use InSAR), for a user-friendly implementation of InSAR displacement time series analysis with multi-temporal SAR images. EZ-InSAR integrates the three most popular and renowned open-source tools (i.e., ISCE, StaMPS, and MintPy), to generate interferograms and displacement time series by using these state-of-art algorithms within a seamless Graphical User Interface. EZ-InSAR reduces the user’s workload by automatically downloading the Sentinel-1 SAR imagery and the digital elevation model data for the user’s area of interest, and by streamlining preparation of input data stacks for the time series InSAR analysis. We illustrate the EZ-InSAR processing capabilities by mapping recent ground deformation at Campi Flegrei (> 100 mm·yr−1) and Long Valley (~ 10 mm·yr−1) calderas with both Persistent Scatterer InSAR and Small-Baseline Subset approaches. We also validate the test results by comparing the InSAR displacements with Global Navigation Satellite System measurements at those volcanoes. Our tests indicate that the EZ-InSAR toolbox provided here can serve as a valuable contribution to the community for ground deformation monitoring and geohazard evaluation, as well as for disseminating bespoke InSAR observations for all.

Wavelet-like denoising of GNSS data through machine learning. Application to the time series of the Campi Flegrei volcanic area (Southern Italy)

The great potential of the Global Navigation Satellite System (GNSS) in monitoring ground deformation is widely recognized. As with other geophysical data, GNSS time series can be significantly noisy, hiding elusive ground deformation signals. Several denoising techniques have been proposed to improve the signal-to-noise ratio over the years. One of the most effective denoising techniques has been proved to be multi-resolution decomposition through the discrete wavelet transform. However, wavelet analysis requires long data sets to be effective, as well as long computation times, that hinder its use as a real or near real-time monitoring tool. We propose training by a Convolutional Neural Network (CNN) to perform the equivalent of wavelet analysis to overcome these limitations. Once trained, the CNN model provides answers within seconds, making it feasible as a real-time data analysis tool. Our Machine Learning algorithm is tested on daily GNSS time series collected in the Campi Flegrei caldera (Southern Italy), which is a highly volcanic risk area. Without significant gaps, the retrieved RMSE and R2 values vary in the ranges 0.65–0.98 and 0.06–0.52 cm, respectively. These results are encouraging, as they hint at the possibility of applying this methodology in more effective real-time monitoring solutions for active volcanoes.

Ground Deformation Monitoring over Xinjiang Coal Fire Area by an Adaptive ERA5-Corrected Stacking-InSAR Method

Underground coal fire is a global geological disaster that causes the loss of resources as well as environmental pollution. Xinjiang, China, is one of the regions suffering from serious underground coal fires. The accurate monitoring of underground coal fires is critical for management and extinguishment, and many remote sensing-based approaches have been developed for monitoring over large areas. Among them, the multi-temporal interferometric synthetic aperture radar (MT-InSAR) techniques have been recently employed for underground coal fires-related ground deformation monitoring. However, MT-InSAR involves a relatively high computational cost, especially when the monitoring area is large. We propose to use a more cost-efficient Stacking-InSAR technique to monitor ground deformation over underground coal fire areas in this study. Considering the effects of atmosphere on Stacking-InSAR, an ERA5 data-based estimation model is employed to mitigate the atmospheric phase of interferograms before stacking. Thus, an adaptive ERA5-Corrected Stacking-InSAR method is proposed in this study, and it is tested over the Fukang coal fire area in Xinjiang, China. Based on original and corrected interferograms, four groups of ground deformation results were obtained, and the possible coal fire areas were identified. In this paper, the ERA5 atmospheric delay products based on the estimation model along the LOS direction (D-LOS) effectively mitigate the atmospheric phase. The accuracy of ground deformation monitoring over a coal fire area has been improved by the proposed method choosing interferograms adaptively for stacking. The proposed Adaptive ERA5-Corrected Stacking-InSAR method can be used for efficient ground deformation monitoring over large coal fire areas.

Investigating characteristics of the long-term settlement of railway embankments in warm permafrost areas

Introduction: The embankment in the permafrost zone of the Qinghai–Tibet Railway (QTR) faces the problem of permafrost degradation, especially in the warm and ice-rich permafrost areas. The settlement deformation of the embankment is more serious in these areas.Methods: This study systematically investigates the settlement deformation characteristics during 16 operational years of three types of typical roadbed structures. The traditional embankment (TE), U-shaped crushed-rock embankment (UCRE), and crushed-rock revetment embankment (CRRE) are the roadbed structures. The long-term monitoring ground temperature and deformation data of the embankment section along the QTR in warm permafrost areas from 2005 to 2020 are utilized in analysis.Results and Discussion: This study focuses on the influence law of the roadbed structure form, shady–sunny slope effect, and temperature field change on the settlement of the roadbed. The results indicated that the two types of the crushed-rock embankment (CRE) of the long-term cumulative settlement are less than 50% of the cumulative settlement of the TE, and the impact on controlling the settlement is significant. The annual settlements of the three types of embankment structures are related to the artificial permafrost table (APT) and influenced by cyclical climate change at the regional scale. The annual growth rate of the settlement at the left and right shoulders of the UCRE as a result of the effect of the shady–sunny slope does not vary considerably as the number of operational years increases. The impact of the shady–sunny slope on the CRRE for the various settlements before 2008 was negligible. After 2008, the thermal disturbance to the embankment temperature field induced by the preconstruction and the effect of shady–sunny slopes decreased gradually as the number of operational years increased. In some years of operation, a thawed interlayer in the TE and CRRE greatly affected the embankment settlement acceleration. The settlement growth rate of the TE is related to the decline of the artificial permafrost table (APT). During the operational years, there was no thawed interlayer in the UCRE. The development of the settlement rate is unaffected by the temperature field for either the left or right embankment shoulder.

Ground deformation monitoring of the eruption offshore Mayotte

Ground deformation monitoring of the eruption offshore Mayotte

An Efficient Polarimetric Persistent Scatterer Interferometry Algorithm for Dual-Pol Sentinel-1 Data

With time-series PolSAR images, polarimetric persistent scatterer interferometry (PolPSI) algorithms can obtain optimized interferograms with overall better phase quality than any single-pol channel for ground deformation monitoring. Moreover, the open access of Sentinel-1 PolSAR data makes it possible for applications of PolPSI over large regions worldwide. However, the optimum scattering mechanism usually has to be searched in a high dimension solution space by PolPSI techniques from each pixel. This is with very high or even unacceptable computational costs if satisfactory results are expected. To this end, an efficient and effective PolPSI algorithm named as TP-ESM is proposed with Sentinel-1 data in this study, which optimizes pixels' interferograms by a weighted sum of their corresponding VV and VH channel interferograms. The effectiveness of TP-ESM is tested together with two other PolPSI techniques (i.e., TP-MSM and ESPO) over Beijing with 46 Sentinel-1 PolSAR images. The results show that TP-ESM can obtain similar optimized interferometric phases with ESPO over high quality pixels, and the ground deformation monitoring pixel density improvement achieved by TP-ESM and ESPO w.r.t. conventional PSI approach (with VV data) is 35% and 43%, respectively. On the other hand, the TP-MSM approach is found not applicable to Sentinel-1 data. Considering the negligible computational cost of TP-ESM w.r.t. ESPO, it presents a quite good performance on both interferograms' optimizations and ground deformation monitoring. Moreover, the proposed TP-ESM outperforms ESPO on DS pxiels' optimization, and it is anticipated to have promising performances on other PolSAR images acquired by other sensors.

Geotechnical Investigation and Monitoring of Underground Excavation of Tunnel-2 in Srisailam Left Bank Canal Tunnel Project (AMRP), Nalgonda District, Telangana, India

Construction stage geotechnical investigation for tunnels within rocks includes detailed engineering geological mapping of excavated strata and its subsequent rock mass classification for the purpose of selection and installation of suitable supports. Monitoring of ground deformations during excavation of rock tunnels serves as the principal means of verifying the design of tunnel supports and stability of the excavation. Geology of the area comprises of Archean gneissic complex with basic intrusives overlain unconformably by the Srisailam Quartzites. The contact of basic intrusives with granite reaches was expected to be fractured and sheared and identified as adverse geological conditions and may warrant instrumental monitoring. In this work, the underground excavation of Srisailam Left Bank Canal (SLBC) Tunnel2, excavated in the Archean gneisses and granites was mapped by face mapping and 3D geological logging on 1:250 scale during construction stage, for the entire length of 7121Mresulting in identification of Chainages 2776M, 3200M and 4170M for field monitoring. Field instrumentation comprising of MPBX/SPBX, Load cells were installed at the adverse locations. The ground deformations were found to have attained stability with the installation of primary supports comprising shotcrete 50MM thick and pattern rock bolts 4M long full grouted for Rock Mass Class III (Fair Rock), shotcrete 100MM thick and pattern rock bolts)/ Steel Ribs with back fill concrete for Rock Mass Class IV and V(Poor Rock and Very Poor Rock). Keywords: Geological Investigation, Rock Mass Classification, Excavation Monitoring, Ground Deformation, Tunnels, Nalgonda District

Time Series InSAR Ionospheric Delay Estimation, Correction, and Ground Deformation Monitoring With Reformulating Range Split-Spectrum Interferometry

Time Series InSAR Ionospheric Delay Estimation, Correction, and Ground Deformation Monitoring With Reformulating Range Split-Spectrum Interferometry

Multiple-input multiple-output radar, ground-based MIMO SAR for ground deformation monitoring

ABSTRACT This study focuses on investigating the capabilities of a Multiple-input multiple-output RADAR. A Radar interferometer, based on an electronically scanned array in MIMO configuration (MIMO‐SAR), has been assessed for operational use in monitoring phenomena of geological interest, such as landslides unstable slopes. The system applies the very well‐known and proven Ground-Based Interferometric technique. It guarantees a very short refreshing time compared to traditional systems based on the mechanical movement of the radar transceiver on a rail or the mechanical steering of a real antenna. The system can monitor several phenomena having deformation rates too high to be correctly retrieved by traditional systems currently in use. Implementing a prototype termed MELISSA allowed the testing technique’s performances in two real case studies: a landslide and an unstable volcanic flank. The experimental results were compared with LISA, a well-known Ground-Based Interferometric Synthetic Aperture Radar (GBInSAR) interferometer. MELISSA allows for obtaining an excellent accuracy, better than 0.01 mm. The range and angular resolution are on the same order of magnitude as those obtained through LISA. However, the refreshing rate obtained from MELISSA, 0.01 s, guarantees a strong coherence even in challenging environmental scenarios as a flank of an active volcano.