Persistent Scatterer Interferometric Research Articles

Lembang Fault Deformation Study Using Sentinel-1A Image with Ps-Insar Method

Badan Nasional Penanggulangan Bencana (BNPB) states that the earthquakes that have occurred in the territory of Indonesia during 2018 were 11,418. Nearly 95 percent of earthquakes occur in fault areas and plate boundaries. In West Java, especially in the Bandung area there is a fault structure called the Lembang Fault which is mostly occupied by community settlements. The Lembang Fault is an active fault, therefore it is necessary to conduct research related to monitoring the Lembang Fault for disaster mitigation purposes. One of parameter to determine the level of activity of a fault is deformation. The amount of deformation can be analyzed through the remote sensing methods, one of them is the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) method. In this study the main data used is Sentinel-1A image data consist of eight scenes with acquisition time from January 2018 to March 2019. The results of the study concluded that the average deformation that occurred along the Lembang Fault was 2,485 mm with a graph that tends to rise. The area most affected by deformation is Cisarua Subdistrict with Line-of-Sight velocity of deformation of 28.4 - 48.9 mm / year. While the smallest deformation occurred in Lembang District with Line-of-Sight velocity of deformation of -2.3 - 19.2 mm / year.

GROUND DEFORMATION MONITORING OF RECLAIMED LANDS ALONG MANILA BAY FREEPORT ZONE USING PS-INSAR TECHNIQUE

Abstract. In response to escalating land demands, land reclamation plays a vital role, but this comes with the challenge of ground deformations that threaten livelihoods and safety. To address the growing concern, Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) is utilized. This remote sensing method is known for its cost-effectiveness, efficiency, and high-resolution capabilities, to monitor vertical ground deformations in Manila Bay Freeport Zone's reclaimed areas. Through adaptation and implementation of PS-InSAR via SARPROZ, measurements along the satellite’s line-of-sight (LOS) is integrated both for ascending and descending geometries using the Nearest Neighbor Vector (NNV) approach to decompose and derive precise vertical displacement values. Correlation analysis with annual leveling data from six benchmarks reveals a strong relationship with correlation coefficient > 0.80. The results indicate relative stability with localized subsidence due to differential settlement and nearby construction. The results from the PS-InSAR technique show that ground deformation on reclaimed lands is expected to continue. Hence, monitoring should be implemented to observe sustained settlements after reclamation, identify areas with significant deformations, detect building and structural deformations, and initiate solutions to reduce the risk of environmental hazards.

Investigation of Salanda Fault Zone, between Yesiloz and Gumuskent (Nevsehir-Turkey) with PSInSAR

In this study, the section of the Salanda fault zone between Yesiloz village and Gumuskent (Nevsehir, Turkey) was investigated by geodetic methods, and the amount of movement in this area was determined. We used a Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) to determine the line of sight (LOS) movement. Previous studies using geological and geomorphological indices have shown that the Salanda fault zone is active. For the first time in this study, 36 synthetic aperture radar (SAR) images acquired between January 8, 2020, and November 29, 2022, were used in PSInSAR analysis. When the annual velocity values of the stud area in the LOS direction were analysed, annual subsidence values of up to 7.6 mm and annual uplift values of up to 7.2 mm were revealed. These movements indicate that the Salanda fault is active and normal fault characteristics. However, it also has a dextral strike-slip component.

Study on the Movement of Overlying Rock Strata and Surface Movement in Mine Goaf under Different Treatment Methods Based on PS-InSAR Technology

The goaf treatment of underground metal mines is an important link in mining, and it is particularly important to master the laws of overlying rock strata and surface movement of goaf. In this paper, Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technology is used to monitor the surface subsidence of the Taibao lead-zinc mine, and the surface subsidence laws of goaf-closure, partial-filling, and full-filling treatments are analyzed by the time-series method. The findings indicate that the surface subsidence of the closed goaf is solely governed by the pillars, with the quality of these pillars playing a pivotal role in controlling such subsidence. Factors like stope span also influence the surface subsidence of partially filled goaf. Prior to compaction, it is primarily the pillars that control surface subsidence; however, after compaction, filling and pillars jointly regulate this phenomenon. Notably, in filled goaf, the quality of both roof and pillars significantly impacts surface subsidence. Before compaction occurs, control over surface subsidence is not evident, yet post-compaction, the filling is effective and tends to stabilize this process. The research findings are significant in enhancing goaf’s treatment efficacy, mitigating surface damage and minimizing ecological environmental impact.

Validating Railway Infrastructure Deformation Monitoring: A Comparative Analysis of Field Data and TerraSAR-X PS-InSAR Results

Railway infrastructure maintenance faces a challenge posed by the laborious task of monitoring widespread deformation, which is critical for ensuring safety. This study utilized the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique with high-resolution TerraSAR-X satellite images to measure and analyze deformation at the operating track. Tailored through parameter optimization to fit regional topography and validated against field measurements, PS-InSAR was applied across a 30km by 50km area over two years. The analysis demonstrated that PS-InSAR could efficiently generate high-accuracy time-series data, capable of detecting both the uplift and subsidence processes. It highlighted the importance of augmenting single-point subsidence values with comprehensive time-series analysis for a complete deformation assessment. The study concluded that PS-InSAR is an accurate and cost-effective tool for large-scale linear infrastructure monitoring, despite technological constraints such as radar imaging frequency and the lack of high-resolution sources. Consideringthese constraints, future research will prioritize developing an enhanced algorithm capable of analyzing both urban and suburban areas, accommodating varying numbers of point scatterers.

Satellite Synthetic Aperture Radar, Multispectral, and Infrared Imagery for Assessing Bridge Deformation and Structural Health—A Case Study at the Samuel de Champlain Bridge

A space-borne remote sensing method was applied, validated, and demonstrated in a case study on the Samuel de Champlain Bridge in Montreal, Canada. High-resolution C-band radar satellite imagery was analyzed using the Persistent Scatterer Interferometric Synthetic Aperture Radar technique to derive bridge displacements and compare them against theoretical estimates. Multispectral and long-wave thermal infrared satellite imagery acquired during the InSAR observation period and historical environmental data were analyzed to provide context for the interpretation and understanding of InSAR results. Thermal deformation measurements compared well with their theoretical estimates based on known bridge geometry and ambient temperature data. Non-thermal deformation measurements gave no evidence of settlement during the 2-year monitoring period, as would normally be expected for a newly constructed bridge with its foundation on bedrock. The availability of environmental data obtained from multispectral and thermal infrared satellite imagery was found to be useful in providing context for the bridge stability assessment. Ambient temperature measurements from thermal infrared satellite imagery were found to be a suitable alternative in cases where data from in situ temperature sensors or nearby weather stations are not available or not fit for purpose. No strong correlation was found between the river conditions and bridge deformation results from the InSAR analysis; this is partly due to the fact that most of these effects act along the river flow in the north–south direction, to which the satellite sensor is not sensitive.

Estimation of active surface deformation using PSInSAR technique of the Central Himalayan region

The Kumaun Himalaya is considered as the most active part of the Central Seismic gap in the Indian Sub-continent. In this paper, we presented active surface deformation rates of the Kumaun region from February 2017 to February 2021 using the Persistent Scatterer Interferometric Synthetic Aperture Radar (PSI) technique. The cumulative displacement that occurred during the span of 4 years is ±55 mm, whereas the Line of Sight (LOS) deformation velocity rate ranges is ±7 mm/yr. Apart from PSI, we also estimated the b-value of the Kumaun region from 1803 to 2021 (399 events) and its value is 0.54 ± 0.03. A distinct NE-SW trend of b-value is observed where earthquakes with M > 6 occurred towards NE of this trend. The PSI-derived deformation reveals that the central part of the Inner Lesser Himalaya along with the Main Central Thrust (MCT) zone is dominated by uplift. The zone between the Munsiari Thrust (MT) and MCT in the central region shows the maximum uplift ranging 5–7 mm/yr which exactly lies above the mid-crustal ramp of the Main Himalayan Thrust (MHT). Our results are well corroborated with available observations of geodetic strain and peak ground acceleration values. However, the deformation patterns and high-velocity rates in the central part of the study area between MT and MCT indicate the accumulation of high stress.

Time‐series InSAR monitoring of surface deformation in Yakutsk, a city located on continuous permafrost

AbstractPermafrost, known for its high sensitivity to climate change and human activities, plays a crucial role in comprehending the environmental sustainability of Arctic cities. Yakutsk, being the largest city situated in continuous permafrost, has suffered irreversible damage to surface buildings due to the widespread permafrost thaw. Therefore, it is imperative to conduct detailed monitoring and assessment of surface deformation to ensure the stable operation of building facilities and to plan urban development situated above the permafrost. This study utilized 138 scenes of Sentinel‐1B images captured between 2017 and 2021 to process the surface deformation variations of Yakutsk using the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS‐InSAR) method. The surface deformation rate map reflects that the study area is undergoing extensive surface subsidence. The cumulative deformation time series maps effectively trace the temporal and spatial evolution of surface deformation, with the highest surface subsidence rates exceeding 40 mm/year and maximum cumulative subsidence exceeding 250 mm. In‐depth analysis of the obtained results indicated that the permafrost in Yakutsk is undergoing degradation, and the primary reason for surface subsidence is the thawing of foundation soils and the degradation of ice‐bearing permafrost. This study provides basic data for the investigation of geohazards caused by surface subsidence in Yakutsk.

Land subsidence susceptibility mapping in urban settlements using time-series PS-InSAR and random forest model

Land subsidence in urban settlements is globally becoming prevalent and severe due to sea level rise and accelerated construction. However, few studies have analyzed the susceptibility of land subsidence in urban settlements and the subsidence rate thresholds that have a great impact on the reliability of the land subsidence susceptibility map (LSSM). This work aims to provide a novel LSSM framework for decision makers to conduct risk control in regional urban settlements. Herein, the COSMO-SkyMed Synthetic Aperture Radar (SAR) data from July 2016 to June 2021 was acquired for remote sensing interpretation in Wuhan, China. Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technology, combined with geostatistical analysis, was employed to map regional land subsidence rates. A total of 12 impact factors, identified through Pearson correlation coefficient (PCC) and multicollinearity tests, were selected as input features for the machine learning model. The performance of the model was assessed using Receiver Operating Characteristic (ROC) curves, and the segmentation of PS points for land subsidence rate was discussed. Furthermore, the correspondence between the measured ground-level observations and the predicted LSSM was compared. The results demonstrate that the random forest (RF) model outperforms other models in the test set, achieving an Area Under the Curve (AUC) of 0.940. The optimal threshold of −10 mm/year is proposed for segmenting PS points, which exhibits the strongest reliability in the distribution characteristics of the susceptibility index (SI). Combined with a high-performance hybrid model, this work is expected to provide a promising reference for land subsidence susceptibility prediction in similar urban settlements worldwide.

Land Subsidence Prediction and Analysis along Typical High-Speed Railways in the Beijing–Tianjin–Hebei Plain Area

High-speed railways in the Beijing–Tianjin–Hebei (BTH) Plain are gradually becoming more widespread, covering a greater area. The operational safety of high-speed railways is influenced by the continuous development of land subsidence. It is necessary to predict the subsidence along the high-speed railways; thus, this work is of critical importance to the safety of high-speed railway operation. In this study, we processed Sentinel-1A data using the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique to acquire the land subsidence in the typical BTH area. Then, we combined the Empirical Mode Decomposition (EMD) and Gradient Boosting Decision Tree (GBDT) methods (EMD-GBDT) to forecast land subsidence along high-speed railways. The results revealed that some parts of the high-speed railways in the BTH plain had passed through or approached the land subsidence area; the maximum cumulative subsidence of the Beijing–Shanghai, Tianjin–Baoding and Shijiazhuang–Jinan high-speed railways reached 326 mm, 384 mm and 350 mm, respectively. The forecasting accuracy for land subsidence along high-speed railways was enhanced by the EMD-GBDT model. The Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) were 0.38 mm to 0.56 mm and 0.23 mm to 0.38 mm, respectively.

Ground Displacements in NY Using Persistent Scatterer Interferometric Synthetic Aperture Radar and Comparison of X- and C-Band Data

In this study, we investigated the quality of Interferometric Synthetic Aperture Radar (InSAR) data to measure surface displacements in upstate New York, an area with dense vegetation, snowy winters, and strong seasonal signals. We used data from the German Space Agency’s TerraSAR-X and TanDEM-X satellites (X-band, 3.1 cm radar wavelength) as well as the European Space Agency’s Sentinel-1 satellite (C-band, 5.6 cm radar wavelength); both datasets covered a ~3-year time period from 2018 to 2021. Using persistent scatterer interferometry (PSI), we were able to observe several deforming features in the region with sub-centimeter/year deformation rates. We also examined a version of the X-band data that we spatially averaged to the same pixel size as the Sentinel-1 imagery in order to separate out the effects of wavelength and pixel size on PSI accuracy and coverage. Overall, the largest number of stable PS points was found in the full-resolution X-band data, which was followed by the C-band data and then by the downsampled X-band data. Our analysis also included a subset of snow-free imagery so that we could assess the effect that snow-covered images had on the distribution and accuracy of PS points and the resulting time series. This analysis revealed that PS populations increased by 50–60% for the snow-free data when compared with analyses using the full datasets. The average deformation rates inferred from the time series generated using only snow-free images were nearly identical to those estimated from the full time series. We assessed the accuracy of the inferred rates through comparisons between the results of different datasets and with limited ground survey data. We found that all of the inferred deformation rates from each of the datasets agreed with in situ measurements in an area of known ground subsidence above an underground salt mine in Lansing, NY. The S1 datasets, however, had higher levels of noise.

SURFACE DEFORMATION MONITORING AND DRIVING FORCE ANALYSIS IN THE YELLOW RIVER DELTA BASED ON PS-INSAR TECHNOLOGY

Abstract. Aiming at the land subsidence in the Yellow River Delta region, based on the Sentinel-1A data of 52 scenes from 2020 to February 2022, Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) were adopted to extract the surface deformation information of the Yellow River Delta region. Firstly, the deformation characteristics of typical subsidence feature points are analyzed, and then the correlation between groundwater, precipitation and land subsidence are analyzed. The result show that the settlement area distribution of the Yellow River Delta is not uniform, mainly distributed in underground brine mining area and oil extraction area, the maximum settlement center is located in Yongan Town, the settlement amount reaches −302.7 mm, the main reason of the settlement is excessive exploitation of underground brine salt. By analyzing the correlation between groundwater, precipitation and land subsidence in the Yellow River Delta, it can be seen that the effect of groundwater content change on land subsidence was the most serious, and the correlation coefficient is 0.875. In general, the subsidence of the Yellow River Delta is mainly caused by the over-exploitation of underground fluids such as fresh water, brine and oil without timely compensation.

The Monitoring and Analysis of Land Subsidence in Kunming (China) Supported by Time Series InSAR

As urban construction has been leaping forward recently, large-scale land subsidence has been caused in Kunming due to the special hydrogeological conditions of the city; the subsidence scope has stretched out, and the subsidence rate has been rising year by year. As a consequence, Kunming’s sustainable development has seriously hindered. The PS-InSAR (Persistent Scatterer Interferometric Synthetic Aperture Radar) and the SBAS-InSAR (Small Baseline Subsets Interferometric Synthetic Aperture Radar) technologies were adopted to process the descending Sentinel-1A data stacks from July 2018 to November 2020 to monitor the land subsidence of Kunming, so as to ensure the sustainable development of the city. Moreover, the causes were analyzed. As revealed by the results, (1) the overall subsidence trend of Kunming was large in the south (Dian lakeside), whereas it was relatively small in the north. The significant subsidence areas showed major distributions in Xishan, Guandu and Jining district. The maximal average subsidence rates of PS-InSAR and SBAS-InSAR were −78 mm/a and −88 mm/a, respectively. (2) The ground Subsidence field of Kunming was analyzed, and the correlation coefficient R2 of the two methods was reported as 0.997. In comparison with the leveling data of the identical period, the root mean square error (RMSE) is 6.5 mm/a and 8.5 mm/a, respectively. (3) Based on the urban subway construction data, geological structure, groundwater extraction data and precipitation, the causes of subsidence were examined. As revealed by the results, under considerable urban subways construction, special geological structures and excessive groundwater extraction, the consolidation and compression of the ground surface could cause the regional large-area subsidence. Accordingly, the monthly average precipitation in Kunming in the identical period was collected for time series analysis, thereby indicating that the land subsidence showed obvious seasonal variations with the precipitation. The results of this study can provide data support and facilitate the decision-making for land subsidence assessment, forecasting and construction planning in Kunming.

Identification of active deformation zone associated with the 28th April 2021 Assam earthquake (Mw 6.4) using the PSInSAR time series

The co-seismic deformation of the 28th April 2021 Assam earthquake with a magnitude of 6.4 has been investigated using the Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR). The results obtained from the PSInSAR are validated with the results of the Global Positioning System (GPS). It is observed that the co-seismic deformation of the earthquake is not visible because of the atmospheric noise. Therefore, we used the Sentinel-1 time-series data of the area to minimize the atmospheric noise effect the data using the Atmospheric Phase Screening (APS) processing of Sentinel-1 time series data. The time-series analysis shows minor changes that occurred during the earthquake. Firstly, the detection of coherence-based changes was carried out to identify the most affected areas, caused by the earthquake. The results of time series analysis suggest that the region located to the north of the Brahmaputra River is subsiding at a much faster rate (−25 to -75 mm/y) than its southern counterpart, where the southern part is subsiding with an average velocity of −0.1 to −15 mm/y. The subsided locations identified using the PSInSAR are further confirmed by the presence of liquefaction features, ground cracks, and tilted buildings related to post-liquefaction ground settlement. To see the deformation along the Bomdila Fault (BF), re-analysis of the available GPS results has been carried out and the derived results reveal a significant amount of deformation (∼4 mm/y) associated with BF and Jorhat Fault (JF); whereas the deformation associated with Kopili Fault (KF) is 3.14 mm/y. Further, our results suggest the presence of compressional strain in the BF zone, while extensional strain in the KF zone. The earthquake focal mechanism analysis suggests that the event of the April 2021 was primarily associated with the BF rather than the KF.

Sentinel-1 Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) for Long-Term Remote Monitoring of Ground Subsidence: A Case Study of a Port in Busan, South Korea

Reclamation has allowed rapid land expansions for economic zones, residential areas, airports, industrial parks, and seaports. Meanwhile, the reclaimed lands often pose a risk of ground subsidence, jeopardizing functions of aboveground infrastructures, buildings, and facilities and threatening human lives. Therefore, it is critical to systematically monitor and manage the reclaimed lands after construction and minimize geohazard risks. This paper presents a case study on long-term remote monitoring of ground subsidence in reclaimed land using satellite synthetic aperture radar (SAR) data and the Persistent Scatterer Interferometric SAR (PS-InSAR) technique. The case study explores the excessive and persistent ground subsidence in Busan New Port, South Korea, which occurred since 2007. We employ large stacks of Sentinel-1 data acquired from the ascending and descending tracks for reliable estimation of ground subsidence and utilize the hyperbolic model, providing an updated prediction tool. A benchmarking and media fact-checking approach consistently supports our PS-InSAR analysis results. The time-series results show that the maximum subsidence rate is approximately −85 mm/yr along the radar line-of-sight (LOS). PS-InSAR can assist in saving expensive and laborious mapping and operational field-survey services and offers essential guidance for the next phase of future construction of Busan New Port.

Analyzing urbanization induced groundwater stress and land deformation using time-series Sentinel-1 datasets applying PSInSAR approach

Urban intensification has taken a serious toll on the groundwater reserves which is one of the primary sources of fresh water on earth. Exploitation of groundwater has exponentially increased over time, especially in urban landscapes, with ever increasing demands to cater the growing population and development processes. This emphasizes on the importance of proper monitoring of the groundwater variations, which is a difficult process for not being directly accessible for physical measurements. Therefore, it is essential to develop advanced innovative indirect methods to help long-term monitoring of groundwater reserves at a relatively higher resolution, so that local level variations and their impact could be studied in case of excessively exploited zones, like cities. Recent studies have linked land-subsidence to over-exploitation of groundwater, which can be critical for urban scenario, which requires longer duration for replenishment. Thus, this study focuses on monitoring of the groundwater variations using time-series Sentinel-1 Interferometric SAR (InSAR) datasets by retrieving land deformation by PsInSAR (Persistent Scatterer Interferometric SAR) technique; applying phase information of permanent scattering candidates. 58 and 60 images were acquired during ascending and descending passes respectively between 9/10/2014 to 2/7/2020 for the study area i.e., Lucknow city (India) and its surroundings. The field measurements of groundwater level for various seasons (pre and post monsoons) were acquired from the Central Groundwater Board, Government of India (CGWB). Besides, Landsat 5 and 8 datasets were utilized to analyze the pattern of urban growth for a 30-year period and predict the near future scenario. In-depth analysis of all the components revealed a direct relationship between land deformation, groundwater variations and urban expansion. A high correlation coefficient of 0.886 was observed between groundwater level variation and the retrieved deformation measured along the groundwater wells along the deformation zones. Therefore, the overall analysis and results indicate that PsInSAR technique has great potential for estimating the groundwater levels and surface deformation at higher resolution and could be easily applied for any other city for continuous assessment.

Inferring 2D Local Surface-Deformation Velocities Based on PSI Analysis of Sentinel-1 Data: A Case Study of Öræfajökull, Iceland

Two-dimensional deformation estimates derived from Persistent Scatterer Interferometric (PSI) analysis of Synthetic Aperture Radar (SAR) data can improve the characterisation of spatially and temporally varying deformation processes of Earth’s surface. In this study, we examine the applicability of Persistent Scatterer (PS) Line-Of-Sight (LOS) estimates in providing two-dimensional deformation information, focusing on the retrieval of the local surface-movement processes. Two Sentinel-1 image stacks, ascending and descending, acquired from 2015 to 2018, were analysed based on a single master interferometric approach. First, Interferometric SAR (InSAR) deformation signals were corrected for divergent plate spreading and the Glacial Isostatic Adjustment (GIA) signals. To constrain errors due to rasterisation and interpolation of the pointwise deformation estimates, we applied a vector-based decomposition approach to solve the system of linear equations, resulting in 2D vertical and horizontal surface-deformation velocities at the PSs. We propose, herein, a two-step decomposition procedure that incorporates the Projected Local Incidence Angle (PLIA) to solve for the potential slope-deformation velocity. Our derived 2D velocities reveal spatially detailed movement patterns of the active Svínafellsjökull slope, which agree well with the independent GPS time-series measurements available for this area.

Response of drainage to tectonics and PS-InSAR derived deformation study in Bilaspur, northwestern Himalaya, India

The study of drainage patterns in tectonically active regions is conducive to the prediction of regional geomorphology. Subtle subsurface changes can be detected by drainage conditions and manifested in the form of drainage anomalies. The Satluj valley of Bilaspur, which is traversed by numerous faults in northwest Himalayan region, was selected to analyze the effect of active tectonics on drainage evolution. With the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique, SENTINEL-1A data were used to estimate the active surface deformation between September 2015 and December 2020. The results show that the region between Barasar Thrust (BrT) and Main Central Thrust (MCT) is undergoing deformation of ±12 mm/yr. The Stream Power Incision Model (SPIM) was used to predict deformation patterns. To validate the tectonic activity generated by the drainage network, seismic b-values were calculated, indicating the accumulating stresses. This study shows the importance of drainage anomalies in tectonically active areas. When used in close combination with other seismotectonic parameters, drainage anomalies can be effective in delineating tectonically active regions.

Reconstruction of active surface deformation in the Rishi Ganga basin, Central Himalaya using PSInSAR: A feedback towards understanding the 7th February 2021 Flash Flood

Active surface deformation, displacement pattern, and erosional variability is estimated using the geomorphologically sensitive morphometry along with the Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique using the Sentinel-1Adata (119 images) acquired between 07- 02-2017 and 10-02-2021. The average velocities for this dataset are estimated to be between ±11 mm/y. The Raunthi River catchment from where the flood was triggered is undergoing ~8 mm/y subsidence and ~10 mm/y uplift. Compared to this the basin wide deformation (Rishi Ganga basin) is estimated to be around ±10 mm/y with commulative ground displacement of around ±45 mm. The times series analysis suggests an increase in the ground displacement by around 5 mm/y and seems to be responsible for the expansion of pre-existing cracks in the vicinity of the Vaikrita Thrust (VT) and subsequent failure of the northern face of Nandi Peak on 7th February 2021. The Global Positioning System (GPS) derived strain distribution pattern indicate a relatively higher accumulation of strain (>0.35µ strain/y). The normalized steepness index (ksn) variation along the longitudinal section of Rishi Ganga and Raunthi River sub-basin in Central Himalayan region shows anomalous increase at the glacio-fluvial transitional processes. Moreover, the χ profiles as well as planform plots shows anomalously lower values within the Raunthi River sub-basin when compared with the Rishi Ganga basin. Based on the lower values of χ it is observed that Raunthi River sub-basin is undergoing high erosion which can be caused by the presence of sheared lithology and incision of the relict glacial and paraglacial sediments. We negate the suggestion that abrupt rise in the temperature was the major triggering mechanism for the recent disaster, instead it is the sheared lithology and pre-existing fissure developed because of differential uplift and subsidence in Raunthi River that led to the wedge failure and subsequent flash flood. Had the climate was the major driver of the recent tragedy ?, it should have impacted multiple hanging glaciers in the Rishi Ganga valley. Therefore, the study calls for detailed geomorphological, structural and glaciological investigation in regions dominated by glacial and paraglacial processes in the strategic regions of the Himalaya. Towards this, the state of art PSInSAR technique seems to provide fast and reliable detection of terrain instability/stability along with identification of potential areas of slope failures in near future in the glacial and preglacial zones.

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.