Persistent Scatterer Research Articles

Development of an Imagewise Stacking Method to Mitigate Atmospheric Effect With an Application to Lianyan Railway

Much attention has been paid to the subsidence monitoring of large-scale man-made linear features, which are usually characterized by long-distance, large-scale, and nonuniform distribution. The multitemporal interferometric synthetic aperture radar (InSAR) technique can provide ground deformation maps for a large area with high spatial resolution and millimeter precision at low costs. The technique overcomes the limitations of ground-based survey instruments. However, the variable atmospheric turbulent component in flat areas has impacts on InSAR detection capability, especially over low-amplitude quasi-stable deformation areas. We propose an imagewise stacking method, which can improve the InSAR time-series analysis by reducing residual noise while retaining the ground deformation signal. We integrate persistent scatterer and distributed scatterer in our processing strategy and conduct a tentative test on the roadbed subsidence monitoring of the Lianyan high-speed railway using 47 medium-resolution Sentinel-1 images. Comparing the InSAR displacement time series and the results with a continuous BeiDou navigation satellite system network, the standard deviation of 3.3 mm and the mean absolute error of 2.2 mm are obtained. The proposed method reduced the above two error measures by 66.3% and 65.6%, respectively, compared with the spatiotemporal filtering. Moreover, the analysis of the spatiotemporal characteristics of the railway deformations also tells that the railway under study is stable.

Ground Displacement Variation Around Power Line Corridors on the Loess Plateau Estimated by Persistent Scatterer Interferometry

As the world's largest producer and consumer of electricity, China has deployed a project to transport energy resources from West China to East China through extra-high-voltage transmission lines to reduce carbon emissions. In the Loess Plateau, the safety of transmission lines has been frequently threatened by natural hazards such as landslides and ground subsidence. However, it is prohibitively expensive to build a monitoring network covering all transmission lines to provide timely early warnings, particularly for sparsely inhabited areas. Based on the large-scale coverage of Sentinel-1 SLC images in IW TOPS mode, we utilized persistent scatterer interferometry to measure the ground target movements along transmission lines with millimeter accuracy. Three regions of interest were selected to reflect the different environmental conditions from the south to north of the Yan'an Region. The displacement variations were compared and evaluated at three spatial scales (region, route, local) from October 2018 to November 2019. On the regional scale, the deformation variation decreased from the south (-36 - 29 mm/yr) to the north (-19 - 20 mm/yr), which was significantly different as determined by the analysis of variance (ANOVA) and can be attributed to the impacts of water-induced subsidence and human activities. On the local scale, the results showed that the deformation rate was less than 10 mm/yr, which suggested a stable status for the experimental line sections. The displacement time series of transmission towers preliminarily revealed seasonal displacement variations, wherein winter and spring were relatively quiet periods. The application of advanced InSAR technologies has excellent prospects in smart grid implementation.

Persistent Scatterer Interferometry in mountainous areas: advantages of working in map geometry

Abstract We compare the processing of Persistent Scatterer Interferometry data in map geometry versus their processing in slant-range/azimuth radar coordinates. In mountainous areas, using the map geometry significantly reduces the geometric distortion of radar coordinates that places scatterers that are actually widely separated in altitude in very close proximity in terms of slant-range. Processing in slant-range coordinates over mountainous regions introduces distortion in the distances used for estimation and filtering of tropospheric phase and phase unwrapping. Spatial filtering, interpolation of missing values, and phase unwrapping have better performance in map geometry because the distances between points are closer to reality. Performing these steps in a map geometry results in a more robust and more reliable processing chain.

OCLeaS – A tomographic PSI Algorithm using Orthogonal Matching Pursuit and Complex Least Squares

This letter describes an algorithm using Compressive Sensing to analyse a stack of SAR images to monitor small urban areas. It uses the combination of the Orthogonal Matching Pursuit and Complex Least Squares, in order to estimate the residual height, thermal dilation coefficient and the displacement rate associated with one or multiple dominant persistent scatterers in a SAR resolution cell. It can be interpreted as a hybrid tomographic-PSI algorithm. The proposed method is tested with simulated data over single and double PS. Then it is applied to a stack of 79 SAR scenes over the Central Business District of the city of Perth in Australia. The results are compared to a conventional algorithm.

An Adaptive Phase Optimization Algorithm for Distributed Scatterer Phase History Retrieval

The multitemporal interferometric synthetic aperture radar (InSAR) technique based on distributed scatterers (DSs) has been widely applied in high-precision deformation measurements, which compensates for the drawback that the persistent scatterer InSAR technique does not obtain sufficient monitoring points, especially in rural areas. Considering that DS pixels are susceptible to various decorrelation factors, it is necessary to retrieve the optimal phase series by phase optimization algorithms (POAs). However, conventional POAs rely on a sample covariance matrix or complex coherence matrix (CCM) derived by spatially averaging statistically homogeneous pixel neighborhoods, which may blur and destroy phase information, especially in dense fringe areas. To overcome this limitation, an adaptive POA is proposed in this article. The adaptive POA artificially constructs a superior CCM by the filtered interferometric phase, which is derived through spatial adaptive filtering approach fusion of principal phase component estimation and fast nonlocal means filtering, and an accurate coherence matrix determined via coherence estimation bias correction. Moreover, the modified eigen-decomposition-based maximum-likelihood-estimator of the interferometric phase (EMI) with coherence-power-weighting is proposed to further improve the estimation precision and computational efficiency. The estimated CCM is then processed with the modified coherence-power-weighted EMI algorithm, and the optimal phase history is retrieved. The experimental results validated against both simulated and Sentinel-1A data demonstrate the superior optimization performance and robustness of the adaptive POA over traditional POAs.

Comprehensive time-series analysis of bridge deformation using differential satellite radar interferometry based on Sentinel-1

We present a comprehensive methodological framework for structural deformation monitoring of critical infrastructure assets based on differential SAR interferometry. By employing persistent scatterer interferometry, deformation time series in line-of-sight are derived from freely available Sentinel-1 single look complex products. These raw time series are analysed and refined using an extensive post-processing chain to obtain daily rates for vertical and horizontal deformation components. The post-processing includes cleaning, smoothing and a temperature correction to account for different sensing times in ascending and descending orbits. Longitudinal clustering of time series is used to reveal spatial patterns in the single epoch deformation series. Seasonal trend decomposition of the aggregated time series is performed to separate deformation trends from seasonal deformations. The applicability of the framework is showcased at the example of an integral concrete bridge located in the port of Vienna. Results are validated against in situ deformation measurements. The presented framework constitutes a blueprint for the continuous monitoring of critical infrastructure assets using satellite interferometry, which may supplement conventional structural health monitoring.

Monitoring and Mapping of Shallow Landslides in a Tropical Environment Using Persistent Scatterer Interferometry: A Case Study from the Western Ghats, India

Persistent Scatterer Interferometry (PSI) techniques are now well established and accepted for monitoring ground displacements. The presence of shallow-seated landslides, ubiquitous phenomena in the tropics, offers an opportunity to monitor and map these hazards using PSI at the regional scale. Thus, the Western Ghats of India, experiencing a tropical climate and in a topographically complex region of the world, provides an ideal study site to test the efficacy of landslide detection with PSI. The biggest challenge in using the PSI technique in tropical regions is the additional noise in data due to vegetation. In this study, we filtered these noises by utilizing the 95-percentile of the highest coherence data, which also reduced the redundancy of the PSI points. The study examined 12 landslides that occurred within one of the three temporal categories grouped as Group 1, Group 2, and Group 3, categorized in relation to PSI monitoring periods, which was also further classified into east- and west-facing landslides. The Synthetic Aperture Radar (SAR) data is in descending mode, and, therefore, the east-facing landslides are characterized by positive deformation velocity values, whereas the west-facing landslides have negative deformation values. Further, the landslide-prone areas, delineated using the conventional factor of safety (FS), were refined and mapped using PSI velocity values. The combination of PSI with the conventional FS approach helped to identify exclusive zones prone to landslides. The main aim of such an attempt is to identify critical areas in the unstable category in the map prepared using FS and prioritizing the mitigation measures, and to develop a road map for any developmental activities. The approach also helps to increase confidence in the susceptibility mapping and reduce false alarms.

Monitoring Subsidence Deformation of Suzhou Subway Using InSAR Timeseries Analysis

Subway subsidence and the consequent geological hazards have become one of the major concerns especially in China's large cities. Large spatial-scale and temporally continuous measurements of surface deformation due to subway subsidence is the basis of the intelligent management for urban transit, as well as the guarantee for the early warning of geological disasters. In this paper, we used persistent scatterer interferometric synthetic aperture radar (PS InSAR) measurements to study and characterize the deformation process resulted from subway-induced subsidence in the construction and operation periods of Suzhou subway using 24-scene high-resolution TerraSAR data (from December 2009 to April 2015) and 19-scene low-resolution Sentinel-1A SAR data (from May 2017 to February 2020). Our results indicate spatially different subsidence rates at different segments along the Suzhou subway lines 1, 2, 3, 4, 5 and 6. TerraSAR data indicate the maximum subsidence rate of -13 mm/yr, while Sentinel-1A data demonstrate the maximum subsidence rate of -20 mm/yr. The decadal-scale subway subsidence deformation is generally characterized by its multistage dynamic processes. The significant subway subsidence is mainly distributed around interchange hubs at the intersection area of railway lines. The Peck function model is used to fit the subway subsidence displacement profiles, which reveals the normal distribution characteristics of the subway surface subsidence. Based on our timeseries analysis in different time periods, the logistic cycle function is used to invert the subway subsidence timing, which reveals four first-order stages during subway subsidence: slow acceleration period, fast acceleration period, decay period and steady-state period.

InSAR Multitemporal Data over Persistent Scatterers to Detect Floodwater in Urban Areas: A Case Study in Beletweyne, Somalia

A stack of Sentinel-1 InSAR data in an urban area where flood events recurrently occur, namely Beletweyne town in Somalia, has been analyzed. From this analysis, a novel method to deal with the problem of flood mapping in urban areas has been derived. The approach assumes the availability of a map of persistent scatterers (PSs) inside the urban settlement and is based on the analysis of the temporal trend of the InSAR coherence and the spatial average of the exponential of the InSAR phase in each PS. Both interferometric products are expected to have high and stable values in the PSs; therefore, anomalous decreases may indicate that floodwater is present in an urban area. The stack of Sentinel-1 data has been divided into two subsets. The first one has been used as a calibration set to identify the PSs and determine, for each PS, reference values of the coherence and the spatial average of the exponential of the interferometric phase under standard non-flooded conditions. The other subset has been used for validation purposes. Flood maps produced by UNOSAT, analyzing very-high-resolution optical images of the floods that occurred in Beletweyne in April–May 2018, October–November 2019, and April–May 2020, have been used as reference data. In particular, the map of the April–May 2018 flood has been used for training purposes together with the subset of Sentinel-1 calibration data, whilst the other two maps have been used to validate the products generated by applying the proposed method. The main product is a binary map of flooded PSs that complements the floodwater map of rural/suburban areas produced by applying a well-consolidated algorithm based on intensity data. In addition, a flood severity map that labels the different districts of Beletweyne, as not, partially, or totally flooded has been generated to consolidate the validation. The results have confirmed the effectiveness of the proposed method.

LAND SUBSIDENCE MONITORING ON THE UNDERGROUND MRT CONSTRUCTION AREA IN JAKARTA, INDONESIA

Space utilization for measurement of the changes of Earth’s surface is an alternative monitoring technique. Covering a large area with better spatial resolution, comparable accuracy and costly low compared with conventional measurement have made SAR technology more popular in monitoring the subsidence. Land subsidence is the vertical movement of the land surface mainly triggered by fluid extraction, load of construction, geological condition, natural compaction or tectonic activity. Previous researchers have found that Jakarta has experienced land subsidence for decades. On the other hand, rapid urban growth and severe congestion problem in Jakarta are also crucial issues. By providing the first MRT subway, it is expected to be solved the congestion problem. Persistent Scatterer Interferometry Synthetic Aperture Radar (PSInSAR) is one of method to identify the deformation with millimeter accuracy. It was perfectly useful for studied on the land subsidence in consequence of the first MRT subway project in Jakarta. The land displacement monitoring along MRT subway trajectory has been acquired by processing Sentinel 1 and ALOS PALSAR-2. This study was able to investigate the land subsidence by using SARPROZ. Finally, the results of this study indicated that land subsidence occurred in the construction area with the lowest land subsidence rate of -0.6 cm/year and the highest land subsidence rate was -7.3 cm/year.
 Keywords: PSInSAR; subway; land subsidence; MRT.

Monitoring the Vertical Land Motion of Tide Gauges and Its Impact on Relative Sea Level Changes in Korean Peninsula Using Sequential SBAS-InSAR Time-Series Analysis

The relative sea-level changes from tide gauges in the Korean peninsula provide essential information to understand the regional and global mean sea-level changes. Several corrections to raw tide gauge records are required to account for coastal vertical land motion (VLM), regional and local coastal variability. However, due to the lack of in-situ measurements such as leveling data and the Global Navigation Satellite System (GNSS), making precise assessments of VLM at the tide gauges is still challenging. This study aims to address the above limitation to assess the VLM in the Korean tide gauges using the time-series Interferometric Synthetic Aperture Radar (InSAR) technique. For 10 tide gauges selected in the Korean peninsula, we applied the Stanford Method for Persistent Scatterers (StaMPS)—Small Baseline Subset (SBAS) method to C-band Sentinel-1 A/B Synthetic Aperture Radar (SAR) data acquired during 2014/10–2020/05, with the novel sequential interferograms pair selection approach to increase the slowly decorrelating filtered phase (SDFP) pixels density near the tide gauges. Our findings show that overall the tide gauges in the Korean peninsula are stable, besides the largest VLM observed at Pohang tide gauge station (East Sea) of about −26.02 mm/year; also, higher rates of uplift (>1 mm/year) were observed along the coast of Yellow Sea (Incheon TG and Boryeong TG) and higher rates of subsidence (<−2 mm/year) were observed at Jeju TG and Seogwipo TG. Our approach estimates the rate of VLM at selected tide gauges with an unprecedented spatial and temporal resolution and is applicable when the in-situ and GNSS observations are not available.

Surface Subsidence in Urbanized Coastal Areas: PSI Methods Based on Sentinel-1 for Ho Chi Minh City

In Ho Chi Minh City (HCMC), Vietnam, though at present flooding is merely a recurring nuisance, there is increasing concern that a combination of impending climate change and rapid urbanization will significantly exacerbate the situation. Given the significant measures taken in HCMC to reduce groundwater extraction and sea-level rise (SLR) inundation since the most recent subsidence studies, we aim to update and contribute to the subsidence information of HCMC with continuous temporal coverage from 2017 to 2019. In this study, we use Persistent Scatterer Interferometry (PSI) with Copernicus Sentinel-1 data and open source tools to determine current subsidence rates within the urban center of HCMC. Additionally, the scalability of this method and use of freely accessible data allows for continuous updating and monitoring of this high-vulnerability region. The observed average subsidence rates were 3.3 mm per year with a maximum local subsidence of 5.3 cm per year. These results largely align with findings of previous studies and reflect similar spatial distributed subsidence patterns. Inundation risk awareness is enhanced by not only continued improved subsidence analysis, but also incorporating latest advancements in Digital Elevation Model (DEM) accuracy. This study compares local differences between traditionally used AW3D30 DEM with the CoastalDEM. Our findings indicate that although we identify lower than previously accepted elevations in the urban core, that stabilization of subsidence is observed in this same region.

Land Subsidence Measurement in Reclaimed Coastal Land: Noksan Using C-Band Sentinel-1 Radar Interferometry

Nur, A.-S.; Achmad, A.-R., and Lee, C.-W., 2020. Land subsidence measurement in reclaimed coastal land: Noksan using C-Band Sentinel-1 radar interferometry. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Geospatial Research of Coastal Environments. Journal of Coastal Research, Special Issue No. 102, pp. 218-223. Coconut Creek (Florida), ISSN 0749-0208.It has been 27 years since the beginning of the Noksan national industrial complex construction at downstream of the Nakdong River in Busan. The complex was built by landfilling a coastal area over one of Korea's deepest soft ground areas. Land subsidence occurred since the start of construction due to primary consolidation and secondary consolidation after the creation finished. Since secondary consolidation directly affects the structure over Noksan, it is crucial to monitor the subsidence rate. This study found that land subsidence happened in four areas of Noksan National Industrial Complex from 2017 to 2020 by applying Stamford Methods for Persistent Scatterer (StaMPS) time-series method using C-band Sentinel-1 SAR datasets from descending and ascending track. The results show land subsidence with a maximum velocity of 20.98 mm/year from descending track datasets and 20.92 mm/year from ascending track datasets. The highest rate area of land subsidence occurred in the south part of Noksan. Mean vertical deformation maps between descending and ascending track have been compared and show a good relationship with 0.93 of coefficient correlation. These approach methods in this study that using StaMPS could be used to monitor slow rate of land subsidence in reclaimed coastal land.

Land Subsidence Measurement of Jakarta Coastal Area Using Time Series Interferometry with Sentinel-1 SAR Data

Hakim, W.L.; Achmad, A.R.; Eom, J., and Lee, C.-W., 2020. Land subsidence measurement in Jakarta coastal area using time series interferometry with Sentinel-1 SAR data. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Geospatial Research of Coastal Environments. Journal of Coastal Research, Special Issue No. 102, pp. 75-81. Coconut Creek (Florida), ISSN 0749-0208.Jakarta coastal area is a part of North Jakarta which has a boundary to the Java Sea. Coastal flood from the Java Sea was not a new case in North Jakarta, the situations occurred due to sea-level rise. The conditions of coastal flood in Jakarta can be worsening by land subsidence in Jakarta coastal area. The land subsidence in Jakarta coastal area was occurred in many years and detected by geodetic measurement methods such as GPS and leveling surveys. The study about land subsidence in Jakarta coastal area needed to be updated because it could affect the urban development. This study presents the mean vertical deformation map using Stanford Methods for Persistent Scatterer (StaMPS) for time-series analysis on the Sentinel-1 data archives in the period of March 2017 through April 2020 in both ascending and descending track. The comparison of mean vertical deformation map between two tracks shows a good correlation in terms of displacement patterns with slightly different in 4 individual chosen points that show a high deformation at rates between 30 mm/year and 40 mm/year. The area chosen in this study known as a reclaimed area and the subsidence occurred due to young alluvium consolidation that not supported the maximum compression from a lot of buildings. These approach methods in this study that using StaMPS could be used to monitor land subsidence from all-terrain.

Railway Infrastructure Classification and Instability Identification Using Sentinel-1 SAR and Laser Scanning Data.

Satellite radar interferometry (InSAR) techniques have been successfully applied for structural health monitoring of line-infrastructure such as railway. Limited by meter-level spatial resolution of Sentinel-1 satellite radar (SAR) imagery and meter-level geolocation precision, it is still challenging to (1) categorize radar scatterers (e.g., persistent scatterers (PS)) and associate radar scatterers with actual objects along railways, and (2) identify unstable railway segments using InSAR Line of Sight (LOS) deformation time series from a single viewing geometry. In response to this, (1) we assess and improve the 3-D geolocation quality of Sentinel-1 derived PS using a 2-step method for PS 3-D geolocation improvement aided by laser scanning data; after geolocation improvement, we step-wisely classify railway infrastructure into rails, embankments and surroundings; (2) we recognize unstable rail segments by utilizing the (localized) differential settlement of rails in the normal direction (near vertical) which is yielded from the LOS deformation decomposition. We tested and evaluated the methods using 170 Sentinel-1a/b ascending data acquired between January 2017 and December 2019, over the Betuwe freight train track, in the Netherlands. The results show that 98% PS were associated with real objects with a significance level of 25%, the PS settlement measurements were generally in line with the in-situ track survey Rail Infrastructure aLignment Acquisition (RILA) measurements, and the standard deviations of the PS settlement measurements varied slightly with an average value of 6.16 mm.

Sentinel-1 Data for Underground Processes Recognition in Bucharest City, Romania

Urban areas are strongly influenced by the different processes affecting the underground and implicitly the terrestrial surface. Land subsidence can be one of the effects of the urban processes. The identification of the vulnerable areas of the city, prone to subsidence, can be of great help for a sustainable urban planning. Using Sentinel-1 data, by the PSI (persistent scatterer interferometry) technique, a vertical displacements map of Bucharest city has been prepared. It covers the time interval 2014–2018. Based on this map, several subsidence areas have been identified. One of them, holding a thick layer of debris from urban constructions, was analyzed in detail, on the basis of an accurate local geological model and by correlating the local displacements with the urban groundwater system hydraulic heads. The properties of the anthropogenic layer have been characterized by complementary geotechnical and hydrogeological studies. A dynamic instability pattern, highlighted by PSI results, has been put into evidence when related to this type of anthropogenic layer. This thick anthropogenic layer and its connections to the urban aquifer system have to be further analyzed, when the procedures of urban planning and design invoke constructive operations modifying the aquifer dynamics.

The MS 6.9, 1980 Irpinia Earthquake from the Basement to the Surface: A Review of Tectonic Geomorphology and Geophysical Constraints, and New Data on Postseismic Deformation

The MS 6.9, 1980 Irpinia earthquake occurred in the southern Apennines, a fold and thrust belt that has been undergoing post-orogenic extension since ca. 400 kyr. The strongly anisotropic structure of fold and thrust belts like the Apennines, including late-orogenic low-angle normal faults and inherited Mesozoic extensional features besides gently dipping thrusts, result in a complex, overall layered architecture of the orogenic edifice. Effective decoupling between deep and shallow structural levels of this mountain belt is related to the strong rheological contrast produced by a fluid-saturated, shale-dominated mélange zone interposed between buried autochthonous carbonates—continuous with those exposed in the foreland to the east—and the allochthonous units. The presence of fluid reservoirs below the mélange zone is shown by a high VP/VS ratio—which is a proxy for densely fractured fluid-saturated crustal volumes—recorded by seismic tomography within the buried autochthonous carbonates and the top part of the underlying basement. These crustal volumes, in which background seismicity is remarkably concentrated, are fed by fluids migrating along the major active faults. High pore fluid pressures, decreasing the yield stress, are recorded by low stress-drop values associated with the earthquakes. On the other hand, the mountain belt is characterized by substantial gas flow to the surface, recorded as both distributed soil gas emissions and vigorous gas vents. The accumulation of CO2-brine within a reservoir located at hypocentral depths beneath the Irpinia region is not only interpreted to control a multiyear cyclic behavior of microseismicity, but could also play a role in ground motions detected by space-based geodetic measurements in the postseismic period. The analysis carried out in this study of persistent scatterer interferometry synthetic aperture radar (PS-InSAR) data, covering a timespan ranging from 12 to 30 years after the 1980 mainshock, points out that ground deformation has affected the Irpinia earthquake epicentral area in the last decades. These ground motions could be a result of postseismic afterslip, which is well known to occur over years or even decades after a large mainshock such as the 23 November 1980, MS 6.9 earthquake due to cycles of CO2-brine accumulation at depth and its subsequent release by Mw ≥ 3.5 earthquakes, or most likely by a combination of both. Postseismic afterslip controls geomorphology, topography, and surface deformation in seismically active areas such as that of the present study, characterized by ~M 7 earthquakes. Yet, this process has been largely overlooked in the case of the 1980 Irpinia earthquake, and one of the main aims of this study is to fill such the substantial gap of knowledge for the epicentral area of some of the most destructive earthquakes that have ever occurred in Italy.

Surface Motion Prediction and Mapping for Road Infrastructures Management by PS-InSAR Measurements and Machine Learning Algorithms

This paper introduces a methodology for predicting and mapping surface motion beneath road pavement structures caused by environmental factors. Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) measurements, geospatial analyses, and Machine Learning Algorithms (MLAs) are employed for achieving the purpose. Two single learners, i.e., Regression Tree (RT) and Support Vector Machine (SVM), and two ensemble learners, i.e., Boosted Regression Trees (BRT) and Random Forest (RF) are utilized for estimating the surface motion ratio in terms of mm/year over the Province of Pistoia (Tuscany Region, central Italy, 964 km2), in which strong subsidence phenomena have occurred. The interferometric process of 210 Sentinel-1 images from 2014 to 2019 allows exploiting the average displacements of 52,257 Persistent Scatterers as output targets to predict. A set of 29 environmental-related factors are preprocessed by SAGA-GIS, version 2.3.2, and ESRI ArcGIS, version 10.5, and employed as input features. Once the dataset has been prepared, three wrapper feature selection approaches (backward, forward, and bi-directional) are used for recognizing the set of most relevant features to be used in the modeling. A random splitting of the dataset in 70% and 30% is implemented to identify the training and test set. Through a Bayesian Optimization Algorithm (BOA) and a 10-Fold Cross-Validation (CV), the algorithms are trained and validated. Therefore, the Predictive Performance of MLAs is evaluated and compared by plotting the Taylor Diagram. Outcomes show that SVM and BRT are the most suitable algorithms; in the test phase, BRT has the highest Correlation Coefficient (0.96) and the lowest Root Mean Square Error (0.44 mm/year), while the SVM has the lowest difference between the standard deviation of its predictions (2.05 mm/year) and that of the reference samples (2.09 mm/year). Finally, algorithms are used for mapping surface motion over the study area. We propose three case studies on critical stretches of two-lane rural roads for evaluating the reliability of the procedure. Road authorities could consider the proposed methodology for their monitoring, management, and planning activities.

Radar Remote Sensing to Supplement Pipeline Surveillance Programs through Measurements of Surface Deformations and Identification of Geohazard Risks

This research focused on the quantitative assessment of the surface deformation velocities and rates and their natural and man-made controlling factors as the potential risks along the seismically active 70 km section of buried oil and gas pipeline in Azerbaijan using Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) and Small Baseline Subset (SBAS) remote sensing analysis. Both techniques showed that the continuous subsidence was prevailing in the kilometer range of 13–70 of pipelines crossing two seismic faults. The ground uplift deformations were observed in the pipeline kilometer range of 0–13. Although both PS-InSAR and SBAS measurements were highly consistent in deformation patterns and trends along pipelines, they showed differences in the spatial distribution of ground deformation classes and noisiness of produced results. High dispersion of PS-InSAR measurements caused low regression coefficients with SBAS for the entire pipeline kilometer range of 0–70. SBAS showed better performance than PS-InSAR along buried petroleum and gas pipelines in the following aspects: the complete coverage of the measured points, significantly lower dispersion of the results, continuous and realistic measurements and higher accuracy of ground deformation rates against the GPS historical measurements. As a primary factor of ground deformations, the influence of tectonic movements was observed in the wide scale analysis along 70 km long and 10 km wide section of petroleum and gas pipelines; however, the largest subsidence rates were observed in the areas of agricultural activities which accelerate the deformation rates caused by the tectonic processes. The diverse spatial distribution and variation of ground movement processes along pipelines demonstrated that general geological and geotechnical understanding of the study area is not sufficient to find and mitigate all the critical sites of subsidence and uplifts for the pipeline operators. This means that both techniques outlined in this paper provide a significant improvement for ground deformation monitoring or can significantly contribute to the assessment of geohazards and preventative countermeasures along petroleum and gas pipelines.

Monitoring of Ground Movement and Groundwater Changes in London Using InSAR and GRACE

Groundwater-induced land movement can cause damage to property and resources, thus its monitoring is very important for the safety and economics of a city. London is a heavily built-up urban area and relies largely on its groundwater resource and thus poses the threat of land subsidence. Interferometric Synthetic Aperture Radar (InSAR) can facilitate monitoring of land movement and Gravity Recovery and Climate Experiment (GRACE) gravity anomalies can facilitate groundwater monitoring. For London, no previous study has investigated groundwater variations and related land movement using InSAR and GRACE together. In this paper, we used ENVISAT ASAR C-band SAR images to obtain land movement using Persistent Scatterer InSAR (PSInSAR) technique and GRACE gravity anomalies to obtain groundwater variations between December 2002 and December 2010 for central London. Both experiments showed long-term, decreasing, complex, non-linear patterns in the spatial and temporal domain. The land movement values varied from −6 to +6 mm/year, and their reliability was validated with observed Global Navigation Satellite System (GNSS) data, by conducting a two-sample t-test. The average groundwater loss estimated from GRACE was found to be 9.003 MCM/year. The ground movement was compared to observed groundwater values obtained from various boreholes around central London. It was observed that when large volumes of groundwater is extracted then it leads to land subsidence, and when groundwater is recharged then surface uplift is witnessed. The results demonstrate that InSAR and GRACE complement each other and can be an excellent source of monitoring groundwater for hydrologists.