Land Surface Deformation Research Articles

Sentinel-1 InSAR and GPS-Integrated Long-Term and Seasonal Subsidence Monitoring in Houston, Texas, USA

For approximately 100 years, the Houston region has been adversely impacted by land subsidence associated with excessive groundwater withdrawals. The rapidly growing population in the Houston region means the ongoing subsidence must be vigilantly monitored. Interferometric synthetic aperture radar (InSAR) has become a powerful tool for remotely mapping land-surface deformation over time and space. However, the humid weather and the heavy vegetation have significantly degraded the performance of InSAR techniques in the Houston region. This study introduced an approach integrating GPS and Sentinel-1 InSAR datasets for mapping long-term (2015–2019) and short-term (inter-annual, seasonal) subsidence within the greater Houston region. The root-mean-square (RMS) of the detrended InSAR-displacement time series is able to achieve a subcentimeter level, and the uncertainty (95% confidence interval) of the InSAR-derived subsidence rates is able to achieve a couple of millimeters per year for 5-year or longer datasets. The InSAR mapping results suggest the occurrence of moderate ongoing subsidence (~1 cm/year) in nothwestern Austin County, northern Waller County, western Liberty County, and the city of Mont Belvieu in Champers County. Subsidence in these areas was not recognized in previous GPS-based investigations. The InSAR mapping results also suggest that previous GPS-based investigations overestimated the ongoing subsidence in southwestern Montgomery County, but underestimated the ongoing subsidence in the northeastern portion of the county. We also compared the InSAR- and GPS-derived seasonal ground movements (subsidence and heave). The amplitudes of the seasonal signals from both datasets are comparable, below 4 mm within non-subsiding areas and over 6 mm in subsiding (>1 cm/year) areas. This study indicates that groundwater-level changes in the Evangeline aquifer are the primary reason for ongoing long-term and seasonal subsidence in the Houston region. The former is dominated by inelastic deformation, and the latter is dominated by elastic deformation. Both could cause infrastructure damage. This study demonstrated the potential of employing the GPS- and InSAR-integrated method (GInSAR) for near-real-time subsidence monitoring in the greater Houston region. The near-real-time monitoring would also provide timely information for understanding the dynamic of groundwater storage and improving both long-term and short-term groundwater resource management.

Land Subsidence Time Series Prediction Method Based on LSTM-AMSGD

Accurate prediction of geological subsidence is of great importance for geological hazard risk assessment. Various existing prediction models do not take into account the time correlation between geological subsidence, and the prediction effect lacks practical significance. In this paper, an LSTM-AMSGD-based land subsidence prediction method is proposed. Firstly, the high-precision time series inversion results of large-area land surface deformation are obtained by the small baseline interference technique with multiple principal image coherent targets. Secondly, a recurrent neural network (LSTM-AMSGD) is used as the network architecture. The final cumulative subsidence prediction error is within 0.3 mm, and the single-step prediction of more than 400,000 observation points can be completed in 126s. Therefore, the LSTM-AMSGD model in this paper is effective for the prediction of geological subsidence.

Numerical modeling of debris flows using basic equations in generalized curvilinear coordinate system and its application to debris flows in Kinryu River Basin in Saga City, Japan

Each year, structures installed in rivers and valleys (e.g., bank protections, bridges, and sabo dams) are damaged by debris flows; therefore, it is necessary to predict the flow characteristics of debris flows accurately to design river and valley structures that are robust against such debris flows. In recent years, several two-dimensional models have been developed to simulate debris flow. However, the basic equations in the numerical simulation models are in the Cartesian coordinate system, and the shape of each numerical analysis grid is square or rectangular. It is impossible to use numerical grids that match the horizontal shape of the river or valley structures, such as bank protections and sabo dams, when employing square or rectangular grids. This makes it difficult to calculate the fluid forces acting on river or valley structures. In this study, the basic equations of debris flow are provided in the generalized curvilinear coordinate system and a numerical simulation model of debris flow designed using an orthogonal curved grid along the horizontal shape of rivers and valleys is developed. Numerical simulations of a periodical meandering valley are conducted using the basic equations in the generalized curvilinear and Cartesian coordinate systems; the difference between the two results is discussed. Further, numerical simulations of the debris flow that occurred in the Kinryu River Basin in Saga City, Japan, in 2019 are performed using the basic equations in the generalized curvilinear and Cartesian coordinate systems, and the difference between the two simulation results is discussed. The numerical simulation results of debris flow in a periodical meandering channel suggest a slow propagation of debris flow when equations in the Cartesian coordinate system are used; this is attributed to the rough boundaries of debris flow when a square grid is used, which causes numerical energy dissipation that does not exist physically. The inundation areas and land surface deformation of debris flow in Kinryu River Basin were reproduced well by the developed numerical analysis model; the basic equations were written in the generalized curvilinear coordinate system. The development and decrescence of debris flows were reproduced using the developed model; the first debris flow in Kinryu River Basin was stopped in the upstream mild slope area, while the second flowed into the residential area. Reproducing the flow depth, velocity, and discharge could be improved by the model using basic equations in the generalized curvilinear coordinate system, as compared with those reproduced using basic equations in the Cartesian coordinate system. When the Cartesian coordinate system was used, the volume of the debris flow was evaluated to be small and the travel distance of the debris flow was evaluated to be short; thus, the debris flow does not arrive at the residential area and the risk of debris flows is underestimated.

Ground deformation assessment of the Albertine graben using inSAR

Information on deformation of the land surface is vital for planning of infrastructure especially in areas such as the Albertine graben with substantial amounts of oil discoveries. Traditionally, global positioning systems, precise leveling and geotechnical techniques have been used for assessing and monitoring ground deformations. While these techniques provide accurate information, they are point based, expensive, time consuming and labour intensive over large area monitoring. This study explored an interferometric synthetic aperture radar (InSAR) approach for mapping deformation over Buliisa oil discovery area located in the Western arm of the East African rift valley. The method was implemented by measuring the phase differences of ALOS PALSAR data acquired between 2007 and 2011. Deformation estimates varied between -0.45m to +0.34m while the mean displacements varied from –0.10m to 0.089m. High ground deformation was detected in the Southern, North Eastern and North Western parts contributed by agricultural activity and drilling pad constructions. Generally, analysis of ALOS PALSAR data using InSAR approach provides a viable option for assessing land surface deformation in Buliisa oil exploration area.

Application and prospect of the integration of InSAR and BDS/GNSS for land surface deformation monitoring

Application and prospect of the integration of InSAR and BDS/GNSS for land surface deformation monitoring

A Probabilistic Framework for Land Deformation Prediction (Student Abstract)

The development of InSAR (satellite Interferometric Synthetic Aperture Radar) enables accurate monitoring of land surface deformations, and has led to advances of deformation forecast for preventing landslide, which is one of the severe geological disasters. Despite the unparalleled success, existing spatio-temporal models typically make predictions on static adjacency relationships, simplifying the conditional dependencies and neglecting the distributions of variables. To overcome those limitations, we propose a Distribution Aware Probabilistic Framework (DAPF), which learns manifold embeddings while maintaining the distribution of deformations. We obtain a dynamic adjacency matrix upon which we approximate the true posterior while emphasizing the spatio-temporal characteristics. Experimental results on real-world dataset validate the superior performance of our method.

Characterizing Spatiotemporal Patterns of Land Deformation in the Santa Ana Basin, Los Angeles, from InSAR Time Series and Independent Component Analysis

The excessive extraction and recharge of groundwater lead to long-time seasonal land subsidence in Los Angeles, USA, and especially in the Santa Ana basin. The rate of land subsidence in the Santa Ana basin has been rising, which could pose a danger to infrastructure and human lives. However, the most recent research on land surface deformation in the area was conducted using the traditional parameter estimation method, resulting in little understanding of the regional spatiotemporal characteristics. The parametric method consists of a least square linear inversion, using the pre-defined mathematical geometric or geophysical theoretical models to describe groundwater deformation, and it requires precise external environmental variables and accurate geophysical parameters, which are more difficult to implement. In this study, multitemporal InSAR-derived deformation time series are analyzed by using 69 descending C-band Sentinel-1A SAR scenes acquired from 2015 to 2018. A method based on independent component analysis (ICA) is applied to characterize the spatial pattern and temporal evolution of land subsidence in the Santa Ana basin. The results reveal two different spatial and temporal deformation patterns in the basin. First, a widespread seasonal deformation is identified by the first component, related to annual seasonal groundwater level changes, and the overall deformation shows a concentrated spatial pattern. The second component captures a long-term signal with a large-scale spatial pattern. For quantitative assessment, the obtained deformation time series are compared with the GNSS data, validating an accuracy of millimeters. We further calculate the cross-correlation coefficient and the elastic skeletal storage coefficient from the ICA-derived seasonal deformation and groundwater level, which reveals that the deformation responds quickly (i.e., a lag of 8 days) to the change in groundwater and the Santa Ana aquifer retains almost the same elasticity for at least 15 years. Quantifying the spatiotemporal characteristics of the deformation in the Santa Ana basin can provide a reference for the monitoring and managing of groundwater.

Land surface deformation monitoring in the Al-Ain arid region (UAE) using microgravity and SAR interferometry surveys

The integration of geophysical and satellite-based monitoring techniques can yield new insights in land surface deformation (LSD) studies. In this study, we integrated the microgravity monitoring geophysical technique with Interferometry Synthetic Aperture Radar (InSAR) to reveal the possible sources of LSD changes. A microgravity survey was conducted over Al-Ain city for 1 year at one-month intervals, with time-lapse microgravity changes calculated based on the results. Over the same area of interest and time interval, InSAR analysis was performed using Sentinel-1 (C-band) data. The time-lapse microgravity changes for the whole studied period ranged from −36 to 365 μGal. The InSAR processing showed periodic land surface deformation over the area of interest varying with the season of the year. The InSAR technique detected land surface subsidence at the northeast and western parts of the study area (−7 mm/year and −8 mm/year, respectively) and land surface uplift in the central and southern parts of the study area (2 mm/year). The recorded subsidence may relate to water extraction in these areas. The integration of the two techniques showed a negative correlation, with coefficients of −0.43 and −0.39 for land surface subsidence and uplift, respectively. Furthermore, groundwater level drawdown zones were identified in the west and center of the study area. Overall, LSD is mainly stimulated by water volume exploitation in the Al-Ain region.

Spatially characterizing land surface deformation and permafrost active layer thickness for Donnelly installation of Alaska using DInSAR and MODIS data

The degradation of permafrost in the Earth's cold regions due to climate warming and human activities is of increasing concern because of its impact on ecosystems and land management, thus, monitoring the degradation becomes critical. This study aimed to demonstrate a method in which Sentinel-1 DInSAR and MODIS data were combined to estimate and map seasonal and long-term land surface deformation (subsidence/uplifting) and permafrost active layer thickness (ALT) in Donnelly Training Area (DTA) in Alaska. The coherence (similarity) between the paired SAR images was analyzed for their applicability. A sensitivity analysis and accuracy assessment of the estimates were conducted to account for their quality. Results showed that the estimated seasonal subsidence mainly occurring in June and July was in the range of 0 to −0.43 m, while the estimated uplifting mainly happening from September to May of next year was as great as +0.34 m. Moreover, the estimated long-term (2015 to 2018) subsidence and uplifting were mostly distributed in the southern and northern parts of DTA, respectively. The spatially variable time delays led to the ALT estimates greater along the east river and in the west and south parts, and smaller in the north parts. At the significance level of 0.05, the coherence estimates of the paired images were significantly different from zero and compared with the referenced predictions from a widely used annual prediction model, the average residual of the ALT estimates did not significantly differ from zero at the significance level of 0.05. The spatial distributions of the uncertainties for the seasonal surface deformation estimates were similar to those of the input uncertainties from the estimates of model coefficients, the phase change, the modelling error, and the image pairs. Thus, the DInSAR image based method coupled with MODIS data offered the potential of mapping and monitoring the dynamics of permafrost environment for the cold regions such as DTA in which collecting field observations is difficult and costly. This study also enhanced understanding spatiotemporal variability of permafrost deformation in DTA and provided guidelines for developing a near real-time monitoring system of the permafrost environment.

Mapping land subsidence and aquifer system properties of the Willcox Basin, Arizona, from InSAR observations and independent component analysis

Long-term excessive groundwater exploitation for agricultural, domestic and stock applications has resulted in substantial ground subsidence in Arizona, USA, and especially in the Willcox Groundwater Basin. The land subsidence rate of the Willcox Basin has not declined but has rather increased in recent years, posing a threat to infrastructure, aquifer systems, and ecological environments. In this study, we first investigate the spatiotemporal characteristics of land subsidence in the Willcox Groundwater Basin using an interferometric synthetic aperture radar (InSAR) time series analytical approach with L-band ALOS and C-band Sentinel-1 SAR data acquired from 2006 to 2020. The overall deformation patterns are characterized by two major zones of subsidence, with the mean subsidence rate increasing with time from 2006 to 2020. An approach based on independent component analysis (ICA) was adopted to separate the mixed InSAR time series signal into a set of independent signals. The application of ICA to the Willcox Basin not only revealed that two different spatiotemporal deformation features exist in the basin but also filtered the residual errors in InSAR observations to enhance the deformation time series. Integrating the InSAR deformation and groundwater level data, the response of the aquifer skeletal system to the change in hydraulic head was quantified, and the hydromechanical properties of the aquifer system were characterized. Historical spatiotemporal storage loss from 1990 to 2020 was also estimated using InSAR measurements, hydraulic head and estimated skeletal storativity. Understanding the characteristics of land surface deformation and quantifying the response of aquifer systems in the Willcox Basin and other groundwater basins elsewhere are important in managing groundwater exploitation to sustain the mechanical health and integrity of aquifer systems.

Estimation of Spouted Hot Mudflow Current Using Continuity Equation and DInSAR

Several techniques have been proposed to observe long-term land surface deformation using phase information of synthetic aperture radar (SAR), for example, interferometric SAR (InSAR), differential interferometric SAR (DInSAR), permanent scatterer interferometric SAR (PS-InSAR), and small baseline subset (SBAS) using images of JERS-1, ALOS-1/2, ENVISAT, ERS-1/2, RADARSAT-1/2, TerraSAR-X, SENTINEL-1A/B, and so on. These methods have also been employed to investigate land deformation and the impact caused by the hot mudflow accident at the study area of regency of Sidoarjo, East Java province, Indonesia, where this disaster happened on May 29, 2006, and has been flowing until now. But these methods only derived the land surface deformation and did not figure geological situation in the Earth, especially the current of geological material outflow. Therefore, this research proposed the continuity equation of the law of conservation of material to estimate the current of material outflow to investigate the impact of the land surface disaster in the study area. The information of vertical deformation or subsidence is derived by the consecutive DInSAR using multispaceborne SAR and substituted into the proposed equation to estimate the volume and current of hot mud outflow. The differential global positioning system (GPS) data collected since 2006 were employed to validate the analysis result of land surface deformation, and the root means square (rms) error is 0.46 m. The result obtained the current at the center of the study area at the beginning of the mudflow period was 6800 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /day and decreased from 2018 until now that matched well with the local reports. The proposed equation could also be applied for observation of land deformation, volcano, fault activity, underground water, and so on, using remote sensing technologies.

Application of an improved clustering approach on GPS height time series at CMONOC stations in Southwestern China

The hydrological, geological and meteorological conditions in southwestern China are relatively complex, so that the land surface deformation presents various features. Using 58 Crustal Movement Observation Network of China (CMONOC) stations across four provinces in Southwestern China, we adopt an improved clustering algorithm to classify 49 stations into 12 clusters with different similarity levels. Our results show that the average annual signals of GPS stations within each cluster have strong consistency, while obvious differences exist among the 12 clusters, indicating that clustering algorithm helps to describe surface deformation features more accurately in regions with complex conditions. We then combine other earth observation techniques, such as the Gravity Recovery and Climate Experiment (GRACE) satellite datasets and surface loading models (SLM), and observe that GPS, GRACE and SLM have strong correlation in their monthly displacement series at GPS stations. After excluding non-clustered stations according to our previous clustering results, the correlation coefficients of GPS/GRACE and GPS/SLM are enhanced. Also, the RMS reduction rates of GPS coordinate time series have been improved after deducting displacements obtained from GRACE and SLM, thus the clustering algorithm proves to be effective in improving the consistency of three techniques in joint detection of surface deformation. Moreover, the vertical displacements of four riverside GPS stations in the Three Gorges Reservoir (TGR) area show significant negative correlation with water level of TGR, hence we conclude that the Three Gorges Dam (TGD) may directly affect the consistency of GPS annual signals of its upstream and downstream GPS stations.Graphical

Land surface deformation in Nanchang, China 2018–2020 revealed by multi-temporal InSAR

With the influence of rapid urbanization, land subsidence in Nanchang has caused obvious surface cracks in urban roads. It is necessary to use effective deformation monitoring methods to grasp the current situation and causes of land subsidence in the urban area of Nanchang. Multi-temporal C-band Sentinel-1A images were processed by Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS InSAR) technique, and we obtained the land deformation in Nanchang urban area from 2018 to 2020. Deformation rate results show that most of the land in the study area was stable, and about 94% of the monitoring points had a deformation rate of −5 to 5 ​mm/year. However, small-scale subsidence occurred in the west, north, and south of the study area, with the maximum subsidence rate of −30 ​mm/year. Compared with the leveling data, InSAR-derived results reached the centimeter-level accuracy. Time-series deformation analysis reveals that the main factors causing land subsidence were urban constructions, including building construction, vehicle load, and Nanchang Metro operation. The most severe settlement in the study area was caused by vehicle load, which had significant spatial distribution characteristics. In addition, the acute subsidence that occurred in the construction and early operation stages of the metro gradually stabilized in less than two years.

Assessing the Accuracy of ALOS/PALSAR-2 and Sentinel-1 Radar Images in Estimating the Land Subsidence of Coastal Areas: A Case Study in Alexandria City, Egypt

Recently, the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique is widely used for quantifying the land surface deformation, which is very important to assess the potential impact on social and economic activities. Radar satellites operate in different wavelengths and each provides different levels of vertical displacement accuracy. In this study, the accuracies of Sentinel-1 (C-band) and ALOS/PALSAR-2 (L-band) were investigated in terms of estimating the land subsidence rate along the study area of Alexandria City, Egypt. A total of nine Sentinel-1 and 11 ALOS/PALSAR-2 scenes were used for such assessment. The small baseline subset (SBAS) processing scheme, which detects the land deformation with a high spatial and temporal coverage, was performed. The results show that the threshold coherence values of the generated interferograms from ALOS-2 data are highly concentrated between 0.2 and 0.3, while a higher threshold value of 0.4 shows no coherent pixels for about 80% of Alexandria’s urban area. However, the coherence values of Sentinel-1 interferograms ranged between 0.3 and 1, with most of the urban area in Alexandria showing coherent pixels at a 0.4 value. In addition, both data types produced different residual topography values of almost 0 m with a standard deviation of 13.5 m for Sentinel-1 and −20.5 m with a standard deviation of 33.24 m for ALOS-2 using the same digital elevation model (DEM) and wavelet number. Consequently, the final deformation was estimated using high coherent pixels with a threshold of 0.4 for Sentinel-1, which is comparable to a threshold of about 0.8 when using ALOS-2 data. The cumulative vertical displacement along the study area from 2017 to 2020 reached −60 mm with an average of −12.5 mm and mean displacement rate of −1.73 mm/year. Accordingly, the Alexandrian coastal plain and city center are found to be relatively stable, with land subsidence rates ranging from 0 to −5 mm/year. The maximum subsidence rate reached −20 mm/year and was found along the boundary of Mariout Lakes and former Abu Qir Lagoon. Finally, the affected buildings recorded during the field survey were plotted on the final land subsidence maps and show high consistency with the DInSAR results. For future developmental urban plans in Alexandria City, it is recommended to expand towards the western desert fringes instead of the south where the present-day ground lies on top of the former wetland areas.

Investigating GNSS multipath effects induced by co-located Radar Corner Reflectors

Abstract Radar Corner Reflectors (CR) are increasingly used as reference targets for land surface deformation measurements with the Interferometric Synthetic Aperture Radar (InSAR) technique. When co-located with ground-based Global Navigation Satellite Systems (GNSS) infrastructure, InSAR observations at CR can be used to integrate relative measurements of surface deformation into absolute reference frames defined by GNSS. However, CR are also a potential source of GNSS multipath effects and may therefore have a detrimental effect on the GNSS observations. In this study, we compare daily GNSS coordinate time series and 30-second signal-to-noise ratio (SNR) observations for periods before and after CR deployment at a GNSS site. We find that neither the site coordinates nor the SNR values are significantly affected by the CR deployment, with average changes being within 0.1 mm for site coordinates and within 1 % for SNR values. Furthermore, we generate empirical site models by spatially stacking GNSS observation residuals to visualise and compare the spatial pattern in the surroundings of GNSS sites. The resulting stacking maps indicate oscillating patterns at elevation angles above 60 degrees which can be attributed to the CR deployed at the analysed sites. The effect depends on the GNSS antenna used at a site with the magnitude of multipath patterns being around three times smaller for a high-quality choke ring antenna compared to a ground plane antenna without choke rings. In general, the CR-induced multipath is small compared to multipath effects at other GNSS sites located in a different environment (e. g. mounted on a building).

Reservoir-Induced Land Deformation: Case Study from the Grand Ethiopian Renaissance Dam

The Nile River stretches from south to north throughout the Nile River Basin (NRB) in Northeast Africa. Ethiopia, where the Blue Nile originates, has begun the construction of the Grand Ethiopian Renaissance Dam (GERD), which will be used to generate electricity. However, the impact of the GERD on land deformation caused by significant water relocation has not been rigorously considered in the scientific research. In this study, we develop a novel approach for predicting large-scale land deformation induced by the construction of the GERD reservoir. We also investigate the limitations of using the Gravity Recovery and Climate Experiment Follow On (GRACE-FO) mission to detect GERD-induced land deformation. We simulated three land deformation scenarios related to filling the expected reservoir volume, 70 km3, using 5-, 10-, and 15-year filling scenarios. The results indicated: (i) trends in downward vertical displacement estimated at −17.79 ± 0.02, −8.90 ± 0.09, and −5.94 ± 0.05 mm/year, for the 5-, 10-, and 15-year filling scenarios, respectively; (ii) the western (eastern) parts of the GERD reservoir are estimated to move toward the reservoir’s center by +0.98 ± 0.01 (−0.98 ± 0.01), +0.48 ± 0.00 (−0.48 ± 0.00), and +0.33 ± 0.00 (−0.33 ± 0.00) mm/year, under the 5-, 10- and 15-year filling strategies, respectively; (iii) the northern part of the GERD reservoir is moving southward by +1.28 ± 0.02, +0.64 ± 0.01, and +0.43 ± 0.00 mm/year, while the southern part is moving northward by −3.75 ± 0.04, −1.87 ± 0.02, and −1.25 ± 0.01 mm/year, during the three examined scenarios, respectively; and (iv) the GRACE-FO mission can only detect 15% of the large-scale land deformation produced by the GERD reservoir. Methods and results demonstrated in this study provide insights into possible impacts of reservoir impoundment on land surface deformation, which can be adopted into the GERD project or similar future dam construction plans.

Monitoring of land surface subsidence using persistent scatterer interferometry techniques and ground truth data in arid and semi-arid regions, the case of Remah, UAE

The United Arab Emirates (UAE) is located in an arid desert climate with very limited water resources and scarce rainfall. Along with the fast development of the country, the water demand for agriculture, industrial, and domestic purposes increased and led to diminishing groundwater resources. In this study, we explore the land surface deformations due to groundwater overexploitation in the agricultural area of Remah by analyzing Sentinel-1 data between 2015 and 2019 with the novel Parallelized-Persistent Scatterer Interferometry (P-PSI) technique. The detected land surface deformations have been correlated to the recorded groundwater levels at nearby water wells. This study detected land surface deformations in a form of an extensive subsidence bowl (with 28.5 km in diameter) with a maximum subsidence rate of 40 mm/year and a standard deviation within the bowl of less than 2 mm/year. The detected subsidence was associated with a 12 m drop in the water table level within the study area. The Persistent Scatterers with the highest deformations rate were spatially correlated with the depression cone of the groundwater level. These findings provide useful insights in understanding the groundwater regime of the area and have an important role in assessing regional hazards and driving mitigation measures towards managing uncontrolled groundwater overexploitation for sustainable management of groundwater resources.

Assessment of groundwater depletion–induced land subsidence and characterisation of damaging cracks on houses: a case study in Mohali-Chandigarh area, India

The present study identified groundwater depletion–induced land subsidence by spaceborne differential interferometric SAR (DInSAR) technique and assessed the damaging impacts of land subsidence by characterising the cracks on houses in Mohali-Chandigarh area of India. First, we identified groundwater depletion hot spots using pre-monsoon and post-monsoon groundwater-level (GWL) data of Central Ground Water Board (CGWB), India, for the period of 2005–2018. Both conventional and advanced DInSAR techniques were used to identify temporally consistent subsiding areas and measure precise rates of subsidence in and around groundwater depletion hot spots. We studied the damaging impacts of land surface deformation by characterising the damaging cracks on houses in affected areas. Groundwater depletion and resulting aquifer-system compaction increase effective stress on confining clay layer which leads to stress build-up at the soil-structure interface and causes damaging cracks on houses. A variety of damaging cracks on houses were observed at the affected areas such as Sohana, Landran, Kharar and Kurali localities. We attempted to characterise the damaging cracks on the basis of shape, size, orientation, surface morphology and texture of the cracks; sense of ground movement; and nature of stress build-up at the interface. We identified tensional cracks, compressional cracks and shear cracks with diverse orientations and separation widths. Finally, a comparative assessment of groundwater depletion, land subsidence and damaging impacts on houses has been made. Using DInSAR technique, we identified land subsidence in and around the groundwater depletion areas in Sohana and Landran (both in Mohali City area), Kharar and Kurali (in Mohali district outside Mohali City area) and Sectors 27–28 in Chandigarh with radar line-of-sight subsidence rates of ~6–7.5 cm/year, ~5.5–6.5 cm/year, and ~ 4 cm/year respectively. We observed that the houses in and around Landran appears to be worst affected followed by Kharar, Sohana and Kurali. From this study, it appears that the type of construction of the houses, e.g. prevalence of masonry and reinforced masonry structures, is primarily responsible for the worst damaging impacts of the houses in Landran and Kurali areas besides the magnitude of land subsidence.

Recent land deformation detected by Sentinel-1A InSAR data (2016–2020) over Hanoi, Vietnam, and the relationship with groundwater level change

ABSTRACT Interferometric synthetic aperture radar (InSAR), one of the most commonly used remote sensing methods for observing and monitoring land subsidence, has been applied in Hanoi, Vietnam in several studies with results showing deformation up to 2014. However, freely accessible Sentinel-1 InSAR data have not been investigated thoroughly to date. Here, we investigate the most recent land surface deformation in Hanoi for the period 20162020 using Sentinel-1A SAR data. The analysis is conducted on 114 SAR scenes with both the Persistent Scatterer InSAR (PSInSAR) and Small BAseline Subset (SBAS) methods. The GPS-based deformation time series are used to verify InSAR results and borehole groundwater level measurements are employed to evaluate the relationship between groundwater depletion and surface subsidence. The results show that observed deformation from SBAS and PSInSAR is consistent in both spatial patterns and statistics, in which two high-rate subsiding bowls were detected in Dan Phuong/Hoai Duc and Ha Dong/Thanh Tri districts with the mean subsiding rates of ∼5 mm per year. GPS and InSAR deformation generally agree well except for the comparison at the JNAV station after 2017, which can be attributable to the local deformation detected by GPS and the average movement of a 100-m radius area captured by InSAR. An agreement in the drawdown trend between borehole groundwater and InSAR-derived deformation was found at four wells located within or in proximity to the two bowls. The declining rates of groundwater level at about 0.31 m per year were found at the two wells Q57a and Q58a located within the Dan Phuong/Hoai Duc bowl, corresponding to the surface subsidence rates found at 6–8 mm per year. The Q68a well was found to experience groundwater level declining at the highest rate of ∼0.9 m per year corresponding to the subsidence rate of ∼7 mm per year found by InSAR.

Investigating Ground Subsidence and the Causes over the Whole Jiangsu Province, China Using Sentinel-1 SAR Data

Interferometric synthetic aperture radar (InSAR) mapping of localized ground surface deformation has become an important tool to manage subsidence-related geohazards. However, monitoring land surface deformation using InSAR at high spatial resolution over a large region is still a formidable task. In this paper, we report a research on investigating ground subsidence and the causes over the entire 107, 200 km2 province of Jiangsu, China, using time-series InSAR. The Sentinel-1 Interferometric Wide-swath (IW) images of 6 frames are used to map ground subsidence over the whole province for the period 2016–2018. We present processing methodology in detail, with emphasis on the three-level co-registration scheme of S-1 data, retrieval of mean subsidence velocity (MSV) and subsidence time series, and mosaicking of multiple frames of results. The MSV and subsidence time series are generated for 9,276,214 selected coherent pixels (CPs) over the Jiangsu territory. Using 688 leveling measurements in evaluation, the derived MSV map of Jiangsu province shows an accuracy of 3.9 mm/year. Moreover, subsidence causes of the province are analyzed based on InSAR-derived subsidence characteristics, historical optical images, and field-work findings. Main factors accounting for the observed subsidence include: underground mining, groundwater withdrawal, soil consolidations of marine reclamation, and land-use transition from agricultural (paddy) to industrial land. This research demonstrates not only the capability of S-1 data in mapping ground deformation over wide areas in coastal and heavily vegetated region of China, but also the potential of inferring valuable knowledge from InSAR-derived results.