Deformation Monitoring Techniques Research Articles

High-Precision Monitoring Method for Bridge Deformation Measurement and Error Analysis Based on Terrestrial Laser Scanning

In bridge structure monitoring and evaluation, deformation data serve as a crucial basis for assessing structural conditions. Different from discrete monitoring points, spatially continuous deformation modes provide a comprehensive understanding of deformation and potential information. Terrestrial laser scanning (TLS) is a three-dimensional deformation monitoring technique that has gained wide attention in recent years, demonstrating its potential in capturing structural deformation models. In this study, a TLS-based bridge deformation mode monitoring method is proposed, and a deformation mode calculation method combining sliding windows and surface fitting is developed, which is called the SWSF method for short. On the basis of the general characteristics of bridge structures, a deformation error model is established for the SWSF method, with a detailed quantitative analysis of each error component. The analysis results show that the deformation monitoring error of the SWSF method consists of four parts, which are related to the selection of the fitting function, the density of point clouds, the noise of point clouds, and the registration accuracy of point clouds. The error caused by point cloud noise is the main error component. Under the condition that the noise level of point clouds is determined, the calculation error of the SWSF method can be significantly reduced by increasing the number of points of point clouds in the sliding window. Then, deformation testing experiments were conducted under different measurement distances, proving that the proposed SWSF method can achieve a deformation monitoring accuracy of up to 0.1 mm. Finally, the proposed deformation mode monitoring method based on TLS and SWSF was tested on a railway bridge with a span of 65 m. The test results showed that in comparison with the commonly used total station method, the proposed method does not require any preset reflective markers, thereby improving the deformation monitoring accuracy from millimeter level to submillimeter level and transforming the discrete measurement point data form into spatially continuous deformation modes. Overall, this study introduces a new method for accurate deformation monitoring of bridges, demonstrating the significant potential for its application in health monitoring and damage diagnosis of bridge structures.

An Image Measurement Localization Technique for Deformation Monitoring of Engineering Constructions

An Image Measurement Localization Technique for Deformation Monitoring of Engineering Constructions

Multi-scale failure mechanisms of hydraulic engineering exposed to seasonally frozen salinization environment: Integrating SBAS-InSAR and mechanical experiments

Constructing hydraulic engineering ensures agricultural development and improves salinization environments. However, in seasonally frozen salinization regions, hydraulic engineering is prone to deformation failure. Leakage from canal raises the regional groundwater level, triggering secondary salinization environmental issues. Exploring the instability mechanisms is thus necessary for hydraulic engineering. Traditional deformation monitoring techniques and soil experiments are constrained by observation scale and timeliness. In this study, Sentinel-1B data from November 2017 to August 2019 were acquired. The small baseline subset (SBAS) InSAR approach was employed to interpret the seasonal deformation characteristics in both the vertical and slope directions of a damaged canal segment in Songyuan, Northeast China. The mechanical properties of saline-alkali soil under varying water contents were quantified by integrating unconfined compression experiment (UCE). In May, as the soil thawed downward, a frozen lenses with poor permeability formed at a depth of approximately 100 cm, causing the accumulation of meltwater and infiltrated precipitation between the frozen layer and the melting layer in the canal. The soil water content at a depth of 80 to 140 cm exceeded 22 %, reaching a threshold for rapid reduction in unconfined compression strength (UCS). Consequently, in spring, the low soil strength between the frozen layer and the melting layer resulted in interface sliding, with a displacement of −133.88 mm in the canal slope direction. Furthermore, the differential projection of freeze-thaw deformation in the slope direction caused continuous creep of the canal towards the free face, with a value of −23.27 mm, exacerbating the formation of the late spring landslide. Integrating InSAR and engineering geological analysis is beneficial for addressing deformation issues in hydraulic engineering. Ensuring the sustainable operation of hydraulic engineering holds important implications for mitigating the salinization process.

The Use of Shape Accel Array for Deformation Monitoring and Parameter Inversion of a 300 m Ultrahigh Rockfill Dam

The global construction of rockfill dams has now surpassed the 300 m height level. Despite great achievements in dam design and construction, monitoring techniques have lagged behind the development of high rockfill dams. Existing deformation monitoring techniques are ill-suited to the high earth and water pressures, and extended monitoring periods are required for ultrahigh rockfill dams. This study introduces, for the first time, the use of a shape accel array (SAA) to monitor internal displacement in a 300 m high earth core rockfill dam. The SAA employs a rope-like array of capacitive MEMS accelerometers for deformation measurement. Compared to conventional monitoring techniques, SAA is a data-intensive monitoring technique. Based on the intensive data obtained from SAA, we employed a parameter inversion method, utilizing multiobjective optimization algorithm, the nondominated sorting genetic algorithm-III (NSGA-III), to inverse the constitutive model parameters of the rockfill dam. The multiobjective parameter inversion method maximizes the use of multisource monitoring data for predicting rockfill dam deformation.

Interannual Variation of Landfast Ice Using Ascending and Descending Sentinel-1 Images from 2019 to 2021: A Case Study of Cambridge Bay

Landfast ice has undergone a dramatic decline in recent decades, imposing potential effects on ice travel for coastal populations, habitats for marine biota, and ice use for industries. The mapping of landfast ice deformation and the investigation of corresponding causes of changes are urgent tasks that can provide substantial data to support the maintenance of the stability of the Arctic ecosystem and the development of human activities on ice. This work aims to investigate the time-series deformation characteristics of landfast ice at multi-year scales and the corresponding influence factors. For the landfast ice deformation monitoring technique, we first combined the small baseline subset approach with ascending and descending Sentinel-1 images to obtain the line-of-sight deformations for two flight directions, and then we derived the 2D deformation fields comprising the vertical and horizontal directions for the corresponding periods by introducing a transform model. The vertical deformation results were mostly within the interval [−65, 23] cm, while the horizontal displacement was largely within the range of [−26, 78] cm. Moreover, the magnitude of deformation observed in 2019 was evidently greater than those in 2020 and 2021. In accordance with the available data, we speculate that the westerly wind and eastward-flowing ocean currents are the dominant reasons for the variation in the horizontal direction in Cambridge Bay, while the factors causing spatial differences in the vertical direction are the sea-level tilt and ice growth. For the interannual variation, the leading cause is the difference in sea-level tilt. These results can assist in predicting the future deformation of landfast ice and provide a reference for on-ice activities.

Time series phase unwrapping algorithm using LP-norm optimization compressive sensing

Time series phase unwrapping is an essential step in the time series interferometric synthetic aperture radar technique for deformation monitoring. However, traditional unwrapping algorithms are prone to unwrapping errors in the case of intense noise and steep deformation gradients, which directly affect the accuracy of the deformation information interpretation. To address this problem, a time series phase unwrapping algorithm using LP-norm optimization compressive sensing is proposed in this paper. This algorithm first transforms the minimizing L0-norm describing compressive sensing technique into a nonconvex problem with weaker constraints, that is, minimizing the LP-norm. Then, an optimized compressed sensing model was proposed by combining the constraint criterion of the phase triplet closure in the temporal domain and the solution strategy of the iterative reweighted least squares method. Improved temporal dimensional phase unwrapping and unwrapping error correction algorithms were developed based on this optimized model. Finally, the proposed algorithm was perfected by combining the above improved methods and the pseudo-three-dimensional phase unwrapping framework. Simulated and Sentinel-1A real datasets verify that the proposed algorithm has better noise robustness, unwrapping stability, and efficiency than traditional algorithms, particularly in the case of a steep deformation gradient and intense noise. The temporal coherence estimated by the proposed algorithm for the real dataset is generally greater than 0.99, which is far superior to traditional algorithms. Furthermore, the proposed algorithm facilitates high-precision interpretation of deformation information. The cross-validation results show that the deformation results obtained by traditional algorithms are underestimated by at least 73 mm/a and 68 mm at the maximum subsidence than the DSInSAR. However, the deformation result obtained by the proposed algorithm is highly consistent with that of the DSInSAR.

High precision deformation monitoring with integrated GNSS and ground range observations in harsh environment

Global Navigation Satellite System (GNSS) has become one of the most essential deformation monitoring techniques for large structs due to its high precision, automatability, and continuity. Normally, excellent observation circumstances are required to achieve an accuracy of millimeter level. However, the monitoring stations are sometimes located in harsh environments, which results in accuracy degradation of GNSS positioning caused by signal blockage and corruption. In this study, GPS, BDS and ground ranging observations (GNSS + ROBS) are combined to achieve an accuracy of mm level in harsh environment, where the ROBS could be obtained from a ranging technology. Experiments were carried out at a concrete faced rockfill dam in central China. The results show that GNSS + ROBS can achieve positioning precision of 0.5 mm, 0.6 mm, and 1.2 mm in the east (E), north (N), and up (U) directions, respectively. In comparison with GNSS-only positioning, the positioning accuracy of GNSS + ROBS is improved by an average of 25.4 %, 37.7 %, and 21.4 % in the E, N, and U directions, respectively. Additionally, it is found that the ROBS can bring up to 64 % improvement in positioning accuracy in the N direction, when the ROBS are located in the direction of GNSS signal shield. The results indicate that GNSS + ROBS have the potential to enhance precision and reliability of positioning in challenging environments.

Permafrost Early Deformation Signals before the Norilsk Oil Tank Collapse in Russia

Despite the profound roles of surface deformation monitoring techniques in observing permafrost surface stability, predetermining the approximate location and time of possibly occurring severe permafrost degradation before applying these techniques is extremely necessary, but has received little attention. Taking the oil tank collapse accident in the Norilsk region as a case, we explored this concern by analyzing the permafrost deformation mechanisms and determining early surface deformation signals. Regarding this case, we firstly applied the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique to obtain its permafrost surface deformation rate, then utilized a sine model to decompose its interannual deformation and seasonal deformation, and finally compared the relationship between the topographic slope and deformation rate. Based on experimental results, we reveal that when the annual average temperature continuously increases at a rate of 2 °C/year for 2∼3 consecutive years, permafrost areas with relatively large topographic slopes (>15°) are more prone to severe surface deformation during the summer thaw period. Therefore, this paper suggests that permafrost areas with large topographic slopes (>15°) should be taken as the key surveillance areas, and that the appropriate monitoring time for employing surface deformation monitoring techniques should be the summer thawing period after a continuous increase in annual average temperature at a rate of 2 °C/year for 2∼3 years.

A Review of Computer Vision-Based Structural Deformation Monitoring in Field Environments.

Computer vision-based structural deformation monitoring techniques were studied in a large number of applications in the field of structural health monitoring (SHM). Numerous laboratory tests and short-term field applications contributed to the formation of the basic framework of computer vision deformation monitoring systems towards developing long-term stable monitoring in field environments. The major contribution of this paper was to analyze the influence mechanism of the measuring accuracy of computer vision deformation monitoring systems from two perspectives, the physical impact, and target tracking algorithm impact, and provide the existing solutions. Physical impact included the hardware impact and the environmental impact, while the target tracking algorithm impact included image preprocessing, measurement efficiency and accuracy. The applicability and limitations of computer vision monitoring algorithms were summarized.

Separate modeling technique for deformation monitoring of concrete dams

Deformation monitoring is an important aspect of safety control for concrete dams. Deformation monitoring models (such as statistical models and hybrid models) are extensively applied to predict concrete dam deformation and derive confidence interval of normal deformation for anomaly detection. Deformation monitoring models for concrete dams mainly consist of hydrostatic component, temperature component, and aging component. The optimum parameters of individual components are simultaneously determined by least square method for monitoring data fitting. Thus, significant over-fitting of deformation monitoring models may be induced by mutual compensation among the parameters of model components. In this paper, the Separate Modeling Technique (SMT) is proposed for mitigating the over-fitting problem of deformation monitoring models for concrete dams. Firstly, the Empirical Mode Decomposition (EMD) is adopted to extract and visualize the aging component of displacement sequence. Proper mathematical formulation of the aging component can be established, and the problem of improperly presupposing the mathematical form of aging component in the process of constructing traditional deformation monitoring models is well addressed. In this study, the hydrostatic component is represented by the Hybrid Response Surface (HRS), which is formulated using numerical simulation with varying water levels and material parameters. The displacement variation caused by water level fluctuation is identified in terms of isothermal conditions and is used to calibrate the material parameters in the HRS. The temperature component is separated through subtracting the hydrostatic and aging components from displacement time series and then is expressed with proper mathematical formulations. Finally, hybrid models for displacement monitoring of concrete dams are established by combining the separately formulated components. The Separate modeling technique is applied to formulate crest displacement of the YL concrete gravity dam. The false alarm rate of displacement monitoring and a new model selection criterion (namely over-fitting coefficient) are adopted to compare various deformation monitoring models. It is shown that the over-fitting levels of deformation monitoring models can be effectively reduced using the SMT. The deformation monitoring models constructed with the SMT are of better accuracy in displacement prediction and present no false alarm of displacement monitoring for the tested period.

Construction of “Space-Sky-Ground” Integrated Collaborative Monitoring Framework for Surface Deformation in Mining Area

Ground deformation measurements in mining areas play a key role in revealing the surface subsidence law, retrieving the subsidence parameters, warning of geological disasters and restoring the surface ecology. With the development of science and technology, there have emerged a great number of monitoring techniques and buildings of diverse protection levels. The diversity of monitoring techniques and the multiplicity of monitoring objects have brought challenges for surface deformation monitoring in the coal industry. Based on the existing deformation monitoring techniques, this paper established a framework of “space-sky-ground” collaborative monitoring system in mining area. We also constructed an AHP-TOPSIS (Analytic Hierarchy Process method- Technique for Order Preference by Similarity to an Ideal Solution) preference model of “space-sky-ground” collaborative monitoring of surface deformation in mining area, and carried out engineering application. Our study shows that the framework of the “space-sky-ground” collaborative monitoring system for surface subsidence in mining areas established in this paper, combined with the AHP-TOPSIS monitoring preference model, which can fully combine the advantages of each monitoring technique, overcome the limitations of a single monitoring technique, comprehensively obtain the surface subsidence data and work out the surface deformation subsidence pattern. This information provides a data and technical support for surface environment management.

InSAR as a tool for monitoring hydropower projects: A review

This paper provides a review of using Interferometric Synthetic Aperture Radar (InSAR), a microwave remote sensing technique, for deformation monitoring of hydroelectric power projects, a critical infrastructure that requires consistent and reliable monitoring. Almost all major dams around the world were built for the generation of hydropower. InSAR can enhance dam safety by providing timely settlement measurements at high spatial-resolution. This paper provides a holistic view of different InSAR deformation monitoring techniques such as Differential Synthetic Aperture Radar Interferometry (DInSAR), Ground-Based Synthetic Aperture Radar (GBInSAR), Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR), Multi-Temporal Interferometric Synthetic Aperture Radar (MTInSAR), Quasi-Persistent Scatterer Interferometric Synthetic Aperture Radar (QPSInSAR) and Small BAseline Subset (SBAS). PSInSAR, GBInSAR, MTInSAR, and DInSAR techniques were quite commonly used for deformation studies. These studies demonstrate the advantage of InSAR-based techniques over other conventional methods, which are laborious, costly, and sometimes unachievable. InSAR technology is also favoured for its capability to provide monitoring data at all times of day or night, in all-weather conditions, and particularly for wide areas with mm-scale precision. However, the method also has some disadvantages, such as the maximum deformation rate that can be monitored, and the location for monitoring cannot be dictated. Through this review, we aim to popularize InSAR technology to monitor the deformation of dams, which can also be used as an early warning method to prevent any unprecedented catastrophe. This study also discusses some case studies from southern India to demonstrate the capabilities of InSAR to indirectly monitor dam health.

Structural characterisation, internal deformation, and kinematics of an active deep-seated rock slide in a valley glacier retreat area

This study presents a multi-disciplinary approach for combining geological-geomorphological field mapping with different surface deformation monitoring techniques (i.e. extensometer, tachymetry, photogrammetry, airborne laser scanning (ALS), terrestrial laser scanning (TLS), uncrewed aerial vehicle (UAV)) to evaluate the impact of structural features on the formation process and deformation behaviour of the deep-seated Marzellkamm rock compound slide. The investigated rock slide is located in a high-alpine, glacier retreat environment in Northern Tyrol (Ötztal Alps, Austria) and formed in a well-foliated, fractured metamorphic rock mass. The total volume of the rock slide of approximately 13 Mm 3 was estimated based on geographic information system (GIS) analysis by comparing the surface topography and reconstructed geometry of the basal shear zone. In the upper part of the rock slide, annual mean velocities of up to 0.3 m/year were measured by a combined tachymetric-global navigation satellite system (GNSS) procedure. Based on multi-temporal terrain model analyses, the highest sliding velocities were obtained at the central slope foot area, reaching more than 1 m/year. Geological-geomorphological field mapping showed that the rock slide can be subdivided into two large rock slide systems with different geometry, formation age, and current activity. Furthermore, structural and geomorphological features (i.e. main and minor scarps, graben-structures, downhill- and uphill-facing scarps, tensile fractures, trenches), as well as surface deformation data, indicate the formation of six rock slide slabs. These slabs move downwards at different velocities and are separated by discrete shear zones, where slope displacement primarily accumulates. Large offsets along these shear zones indicate that internal slab deformation has only limited influence on the overall rock slide behaviour. At the Marzellkamm rock slide, pre-existing tectonic fault zones and planes were reactivated and used as weakness zones, playing a crucial role in the overall rock slide geometry and internal separation of the rock mass into slabs. Field survey and monitoring data suggest that a fully persistent, curved, non-circular basal shear zone has developed. Based on comprehensive analyses of mapping and deformation monitoring data, a geological-geometrical and kinematical model of the Marzellkamm rock slide was developed, providing a basis for site-specific hazard assessment and numerical modelling. • Two rock slide systems of six rock slide slabs of different deformation behaviour • Significant influence of pre-existing geological structures on rock slide formation • Deformation is controlled by the magnitude of shearing on separating shear zones. • Field survey indicates a fully persistent, curved, non-circular basal shear zone. • Two rock fall/avalanche events occurred at the lower part of the most active slabs.

3D DEFORMATION MEASUREMENT OF CONCRETE WALL USING CLOSE-RANGE PHOTOGRAMMETRY

Abstract. Due to the development of digital image processing, digital photogrammetry is becoming an interesting research area in the field of structural monitoring in civil engineering. This study presents a photogrammetric measurement technique for concrete wall deformation monitoring in the destructive experiment. The non-contact photogrammetric measurement technique which provides surface deformation, is more flexible than the contacted single-point measurement technique (e.g., linear variable displacement transducers, LVDT). The major steps of the proposed scheme include (1) camera calibration, (2) orientation modeling, (3) 3D dense matching, and (4) filtering and interpolation for surface deformation. This experiment used two non-metric digital cameras to measure the deformation of a concrete wall in destructive experiment. The validation compared the image-derived and ranger-derived displacements during the experiment with mean error and standard errors of 32 epochs were −0.02mm and 0.81mm, respectively. The correlation between image-derived displacement and LVDT-derived displacement was 0.9803. The advantage of photogrammetry is to derive surface deformation which covered the whole wall during the experiment. In summary, this study demonstrated that photogrammetry is a useful measurement technique for concrete wall destructive experiment.

Detailed Geodetic Technique Procedures for Structural Deformation Monitoring and Analysis

The understanding of the detailed procedures of the geodetic technique for structural deformation monitoring and analysis is required to enable a reliable and cost-effective monitoring system for the monitoring of engineering structures, be developed. To do this, the different stages that are involved in deformation studies using the geodetic method are explained in detail. As a result, this paper presents detailed geodetic technique procedures for structural deformation monitoring and analysis. Data collection, data processing, result presentation and analysis stages are discussed in detail. Keywords: deformation, monitoring, analysis, least squares, geodetic, technique, epoch. DOI: 10.7176/JSTR/6-07-02

Application of the SBAS-DInSAR technique for deformation monitoring in Tunis City and Mornag plain

The ground deformation phenomena are the result of the application of natural stress (tectonic) or anthropogenic stress (overexploitation of groundwater, embankment) on the soil. The land deformation may cause several impacts on the environment and human life. A good understanding of the deformation behaviour of the soil is essential to mitigate risks on the infrastructure and environment. In this study, a radar interferometry is carried out to analyse the mobility of an urban and suburban area of Greater Tunis region. The interferometric synthetic aperture radar (SAR) technique has been proven to be an effective methodology for detecting and monitoring soil displacement with millimetre accuracy and also, improving our understanding of the current deformations in the study area. Indeed, the application of differential SAR interferometry made it possible to determine the origin of the surface deformations related to natural or anthropic phenomena. In this paper, the interferometric method of small baseline subset (SBAS) developed by Berardino et al. 2002has been chosen, in order to monitor the spatial and temporal pattern of the deformation phenomena in Greater Tunis region. The analysis of Envisat ASAR (2003–2007, descending satellite orbit) and Sentinel 1B (2016–2018, ascending satellite orbit) SAR data allowed us to create deformation velocity maps associated with line of sight displacement time series. The results obtained by this method showed the existence of subsidence phenomenon in the urban areas (Tunis City) as well as in the rural areas (Mornag plain). In the first site (Tunis City), the subsidence rate reaches up to 13.98 mm/year and 19 mm/year during 2003–2007 and 2016–2018, respectively. The ground deformation that is detected around the region of Tunis Lake and Sebkhet Essijoumi, is probably due to the nature of the highly compressible and thickness alluvial deposits and whose substratum depth sometimes reaches more than 60 m. In the second studied site, ground subsidence was identified in the whole plain of Mornag. Indeed, the comparison between piezometric data and time series deformations shows that the trend of soil subsidence is coherent with the dynamic change in groundwater levels. Furthermore, the analysis of velocity deformation, geological data and hydrogeological information allows us to associate all the detected settlement patterns to groundwater overexploitation and compressible alluvium all over the plain. This overexploitation of groundwater in Mornag plain is mainly caused by the expansion of agricultural and industrial activities and the decrease in annual rainfall in recent years (from 2003 to 2018).

Monitoring the deformation of the earth’s surface in the zone of influence construction

The issues of ensuring the safe construction and operation of buildings and structures in a metropolis are considered. A description of the monitoring technique is given, which is to control the deformation process during new construction near existing buildings. The necessity of performing geodetic observations of deformations of the earth’s surface is emphasized. A precalculation of the accuracy of determining the position of deformation grades located in the influence zone of an object under construction is given. Based on the simulation results, control zones are identified in which it is proposed to monitor the process of deformation of the soil mass at the boundary of the pit. The advantages of the integrated deformation monitoring technique over traditional observation methods are presented.

Monitoring Land Surface Displacement over Xuzhou (China) in 2015–2018 through PCA-Based Correction Applied to SAR Interferometry

Land surface deformation in metropolitan areas, which can cause varying degrees of hazard to both human lives and to properties, has been documented for decades in cities worldwide. Xuzhou, is one of the most important energy and industrial bases in eastern China, and has experienced significant land subsidence due to both excessive extraction of karst underground water and exploitation of mineral resources in recent decades. Furthermore, Xuzhou has recently undergone rapid urbanization in terms of urban expansion and underground construction, which could induce additional pressure on the urban land surface. However, most previous research on land surface deformation in the Xuzhou urban areas has been conducted based on traditional ground-based deformation monitoring techniques with sparse measurements. Little is known about the regional spatiotemporal behavior of land surface displacement in Xuzhou. In this study, a detailed interferometric synthetic aperture radar (InSAR) time series analysis was performed to characterize the spatial pattern and temporal evolution of land surface deformation in central areas of Xuzhou during 2015–2018. A method based on principal component analysis was adopted to correct artifacts in the InSAR signal. Results showed the correction strategy markedly reduced the discrepancy between global navigation satellite systems and InSAR measurements. Noticeable land subsidence (−5 to −41 mm/yr) was revealed widely within the Xuzhou urban areas, particularly along subway lines under construction, newly developed districts, and in old coal goafs. Remarkable consistent land uplift (up to +25 mm/yr) was found to have significantly affected two long narrow areas within the old goafs since 2015. The possible principal influencing factors contributing to the land surface displacements such as subway tunneling, building construction, mining, underground water levels and geological conditions are then discussed.

Deformation Estimation for Time Series InSAR Using Simulated Annealing Algorithm.

Time series interferometric synthetic aperture radar SAR (TSInSAR) is one of the most important surface deformation monitoring techniques, and has been widely used in geodesy. Deformation estimation is one of the main steps of TSInSAR processing, so an effective and efficient algorithm is necessary. Present algorithms have some limitations such as computing c osts or errors caused by local extremums. In this work, a novel deformation estimation method based on the simulated annealing (SA) algorithm is proposed to handle this problem. The SA algorithm uses a random search to avoid local extremums and thus can be more likely to get the global optimal solution of deformation. By adopting a better annealing method, this algorithm gets high precision deformation results in less time than most present algorithms. In addition, it can estimate complex nonlinear deformation without adding any computing costs. The results, tested on the real SAR data, confirm the reliability and effectiveness of the SA-based deformation estimation algorithm.

DEFORMATION MONITORING IN AND AROUND THE NATIONAL CAPITAL REGION OF INDIA USING DINSAR TECHNIQUE

Abstract. Urbanization increases the pressure on land and ground water. Due to pressure on land and over extraction of the ground water for modernization and development, deformation of land increase. The traditional deformation monitoring techniques are costly and time taking. The Differential Interferometry Technique (DInSAR) has capability to monitor regional scale deformation. Recently Vasundra region of the NCR has experienced a road subsidence near to the multiple stories building. In the study we have attempted to identify the Vasundra and nearby region by the DInSAR technology to identify the deformation in Delhi and NCR focused on the Vasundra area of Ghaziabad, Uttar Pradesh, India. This is one of the developed and planned area in the Ghaziabad District. The Sentinel-1 C data has been used to monitor the deformation in that area. The Vasundra area has been deformed due to heavy rainfall and water logging in the surrounding area by which the road has been subsided up to 30 feet. Using the sentinel data we were able to identify the subsidence in Vasundra and nearby areas. Since the Sentinel scene was very big so a clear picture of the deformation indication in the NCR region are found which need more in-depth study further. Conclusively it can be said that DInSAR technique with Microwave data is a competent tool to monitor the minute deformation.