Differential Radar Interferometry Research Articles

Complex analysis of earthquake deformations using SAR images: Examples from Croatia and Greece

This study presents an assessment of the displacements of the Earth’s crust generated by two earthquakes: one in Croatia on 29th December 2020 and one in Greece on 3rd March 2021. The main data source is SAR satellite images from Sentinel-1A and B (ascending and descending orbits) in the form of images of the amplitude and phase signals. The data is processed via SNAP software package. The results are obtained applying the differential radar interferometry method (DInSAR). The Line of Sight (LoS) displacements are converted into vertical displacements and compared with modeled deformations of the Earth’s surface using rectangle finite source model proposed by Okada.

Landslide Measurement in Glendroud Region (From the Central Part of Noor City) in Mazandaran Province Iran by Using Remote Sensing and Radar Interferometry Techniques

Studying and monitoring the amount of displacement caused by changes in the shape of the earth's surface is one of the important and practical studies in various topics of geology and geophysics, which plays a significant role in the prevention and behavior of natural disasters such as earthquakes, subsidence, and landslides. Among them, there are various methods for geodetic measurements and monitoring of these deformations, among them the radar interferometric technique with the capabilities of producing wide, frequent and continuous ground covers, as well as high temporal and spatial resolution, is one of the techniques has become importantand significant. Landslides in the Yilagh area of GlenrodRoyan, Noor city, caused a lot of damage to some residential areas, gardens and roads of several villages in the region. Due to the movement of the earth, water and electricity have been cut off in some areas. About one kilometer of the north-south road has been destroyed and the most damage has been done to the houses of Foulad welfare complex. After passing through a long period (more than 60 years) of drought, the country of Iran has faced various risks in recent years, especially in 2018 and 2019, including floods and landslides. The aim of this thesis is to obtain the amount of displacements caused by the landslide in Glenrod region in 2019 using sentinel-1 satellite images by using the differential radar interferometry method using snap software. In this regard, from 4 satellite images It has been used during the years 2019-2020, and according to the results obtained, the largest landslide during the second period was 15 cm, which is based on the information obtained from the mapping organization and the opinion of geologists and experts in the region who stated that the largest displacement in area under report was March 2019 and it matches with the findings carried out by the present authors.

An Enhanced Offset Tracking Method: Providing Auxiliary Information for DInSAR Phase Filtering in Urban Areas.

In the application of synthetic aperture radar differential interferometry in urban environments, it is easy to regard the phase change in the deformation band of buildings under construction as noise that requires filtering. This introduces an error into the surrounding area while over-filtering, resulting in an error in the magnitude of the deformation measurement results for the entire region and the loss of deformation details in the surrounding area. Based on the traditional DInSAR workflow, this study added a deformation magnitude identification step, determined the deformation magnitude by using enhanced offset tracking technology, supplemented the filtering quality map and removed the construction areas that affect the interferometry in the filtering stage. The enhanced offset tracking technique adjusted the ratio of contrast saliency and coherence via the contrast consistency peak in the radar intensity image, which was used as the basis for adjusting the adaptive window size. The method proposed in this paper was evaluated in an experiment on a stable region using simulated data and in an experiment on a large deformation region using Sentinel-1 data. The experimental results show that the enhanced method has a better anti-noise ability than the traditional method, and the accuracy rate is improved by about 12%. The supplemented quality map can effectively remove the large deformation area to prevent over-filtering while ensuring the filtering quality, and it can achieve better filtering results.

Grounding Zone of Amery Ice Shelf, Antarctica, From Differential Synthetic‐Aperture Radar Interferometry

AbstractWe employ a time series of Sentinel‐1 differential radar interferometry data from 2018 to detect the variability in grounding line position of the Fisher, Mellor, and Lambert glaciers, which drain about 47 billion tons of ice per year from East Antarctica. We observe kilometer‐scale tidal migration, two orders of magnitude larger than expected for ice flowing over a hard bed. The migration is not in phase with changes in oceanic tide. In two estuaries underlaid by subglacial channels, we observe two states of migration that switch on and off over time scales of several weeks. The range of vertical motion reveals a water column thickness of 2–20 cm. Such intrusions of seawater over wide grounding zones are not accounted for in physical models. Including them will add vigorous melting of grounded ice that will enhance the sensitivity of glaciers to ocean warming and increase projections of mass loss.

Spatiotemporal Characteristics of the Mud Receiving Area Were Retrieved by InSAR and Interpolation

The mud receiving area is an important sand storage area for dredging sea sand reclamation and sand-dumping in the waterway. The sediment accumulation area generated in the process of sand dumping and sand storage has an impact on the surrounding transportation facilities and the normal use of the entire sand storage area. From 6 August 2021 to 9 May 2022, The Sentinel-1A 24-view SLC data covering the sludge area were used to monitor the safety around the seawall road by InSAR technology. Synthetic aperture radar differential interferometry (Differential InSAR, D-InSAR) technology can obtain surface micro deformation information through single-time differential interference processing, mainly used for sudden surface deformation. D-InSAR technology detected five accumulation areas with a thickness of more than 10 cm near the seawall road, earth embankment, and cofferdam, and TS-InSAR (Time series InSAR) technology was used to retrieve the deformation of the surrounding road. The road settlement is a slight settlement distributed between ±5 mm/a. This paper uses the leveling results combined with variance analysis to verify the fusion of different TS-InSAR methods while considering the area of data loss due to causes such as loss of coherence. This paper also considers the common ground continuity and uses the adjacent interpolation and bilinear interpolation algorithm to improve knowledge of the study area seawall road and the surrounding soil embankment deformation data of the road. Compared with the leveling data, the difference between the missing data and the leveling data after interpolation is stable at about 1–7 mm, which increases the risk level of part of the road which needs to be maintained. It provides a reference method to make up for the missing data caused by ground incoherence.

МОНІТОРИНГ ВЕРТИКАЛЬНИХ ЗМІЩЕНЬ ЗЕМНОЇ ПОВЕРХНІ ПРАВОБЕРЕЖЖЯ КАНІВСЬКОГО ВОДОСХОВИЩА

Monitoring of vertical displacements of the earth's surface on the right bank of the Kaniv Reservoir in the Vytatchiv-Stajky region was carried out using the differential radar interferometry (DinSAR) technique. According to the results of observations during the spring period from 2015 to 2023, active landslide areas are displayed. The DinSAR method is briefly described, emphasising data filtering steps for landslide activation mapping. A high data correlation was recorded, and the presence of zones of active shifts on the shore of the reservoir was confirmed. The spread and intensity of landslide manifestations are determined by the peculiarities of the geological and geomorphological structure of the territory, its tectonic, neotectonic and seismic regimes, and hydrological and climatic conditions. Limitations of the method arising from the temporal decorrelation of the radar signal in regions with a large amount of vegetation are determined. Due to the significant decorrelation between the obtained results of forested and watered areas, the DinSAR technique, a digital elevation model (DEM), analysis of base surface maps and the results of spectral index calculations were combined to identify regions of active landslides caused by waterlogging of the Dnieper slopes. The study demonstrates the feasibility of using DinSAR to detect and monitor surface deformation.

Automatic-Detection Method for Mining Subsidence Basins Based on InSAR and CNN-AFSA-SVM

Mining subsidence disasters are common geological disasters. Accurate and effective identification of their deformation position is significant in preventing and controlling geological disasters and monitoring illegal mining. In this study, deep learning, combined with a support vector machine (SVM), has been used to establish an automatic-detection method for mining subsidence basins using Sentinel-1A data. The Huainan mining area was selected as the experimental area to verify the method. The interferogram was obtained using differential radar interferometry (D-InSAR) to process the Sentinel-1A radar data of seven landscapes, and the mining subsidence basin and other targets were extracted manually as training samples. Subsequently, AlexNet, VGG19, and ResNet50 convolutional neural networks (CNNs) were used to extract feature vectors of mining subsidence basins for the SVM classifier, and mining subsidence basins were detected in a large-area InSAR interferogram. Non-maximum suppression was used to remove the repeated search box to improve the detection accuracy of mining subsidence basins; the artificial fish swarm algorithm with strong optimization ability and good global convergence is introduced into SVM parameter optimization to construct an improved ResNet50_SVM model. The experimental results show that: (1) the three CNN_SVM methods can accurately detect dry-mining subsidence basins automatically in large regional interference maps, providing an essential scientific basis for the government to monitor illegal mining activities and prevent and control geological disasters in mining areas; (2) the accuracy of the CNN_SVM automatic-detection methods for mining subsidence basins is approximately 80%, and that of ResNet50_SVM for mining subsidence basin detection is 83.7%, superior to that of AlexNet_SVM and VGG19_SVM; (3) the accuracy of the improved ResNet50_SVM based on AFSA algorithm is 88.3%, which is better than the unimproved Resnet50_SVM model.

Patch-Like Reduction (PLR): A SAR Offset Tracking amplitude filter for deformation monitoring

As complementary to Synthetic Aperture Radar (SAR) Differential Interferometry (DInSAR), SAR Offset Tracking (OT) is an efficient tool for large ground deformation monitoring in situations when DInSAR cannot work. However, SAR images are affected by speckle noise and some strong point-like scatters which can cause what is known as Patch Like (PL), a kind of errors that can be seen as homogeneous patches of almost constant deformation in the results. These errors are clearly visible in the results as non-consistent deformations along time, but they are difficult to detect with the traditional metrics that evaluate the cross-correlation results, like the Signal to Noise Ratio (SNR). This paper addresses this problem and proposes a simple amplitude filter to reduce PL named as Patch Like Reduction (PLR). The main idea is to find a sensor and scene independent threshold to remove the high amplitude pixels prone to cause PL. Five different SAR data sets and in-field GPS measurements are used to determine the optimal threshold and evaluate the performance of the proposed method. The results show that PL effects can be reduced with the proposed amplitude filter. The processing parameters of the improved OT processing chain are optimized as well to preserve the results resolution as much as possible. • The causes of Patch Like errors in Offset Tracking results have been investigated. • An amplitude filter (PLR) has been proposed to reduce PLs. • The filter threshold is automatically defined from images amplitude distributions. • The filter improves OT results by reducing the changes of PL appearance. • Template sizes and tapering windows have been optimized in terms of resolution.

Active landslides in the Rogun Catchment, Tajikistan, and their river damming hazard potential

The region of Tajikistan where the Rogun Hydropower Project is currently under construction has experienced large and catastrophic slope failures in the past, often triggered by earthquakes. Co-seismic slope failures are thus common and pose a high hazard potential; however, to date, no specific analysis of slope activity in this area has been presented in international journals. Here, we present an inventory of active landslides identified through satellite imagery analysis and in particular by exploiting space-borne differential radar interferometry. Surface displacements provide the basis for the detection of active slope instabilities, which are then further classified by using geomorphological indicators visible in optical satellite imagery. Additionally, the proximity of active landslides to tectonic lineaments, as well as regional seismicity, is analysed to investigate potential relationships and to provide an integrated river damming hazard potential. The results show that approximately 31% of all detected landslides would have a high damming hazard potential upon catastrophic failure, highlighting the importance of such phenomena for efficient long-term land use planning and management of hydropower plants.

Efficient Approach for Atmospheric Phase Screen Mitigation in Time Series of Terrestrial Radar Interferometry Data Applied to Measure Glacier Velocity

The accuracy of surface displacements measured by differential radar interferometry is significantly degraded by the atmospheric phase screen (APS). This article presents a practical and efficient approach for APS mitigation based on the coherent pixels technique (CPT) displacement velocity estimation algorithm. In the proposed approach, all motionless coherent pixels closest to the moving area are defined as seeds surrounding the moving area at the integration step of the CPT. This arrangement consequently minimizes the integration path and the APS effect in the final velocity result. It is designed for terrestrial radar interferometry (TRI) applications. A piecewise processing chain is further introduced as a continuous operational mode processing framework to derive arbitrary temporal displacement patterns in this work. Three-day datasets measured by Ku-band TRI over a mountainous region in the canton of Valais, Switzerland, were used for validation. Through this validation, a comparative study of five algorithms was carried out. This evaluation showed the efficiency of the proposed approach. The proposed approach does not require phase unwrapping, kriging interpolation, and spatio-temporal covariance inference for APS mitigation, which is appropriate for continuous TRI operation.

Monitoring the State of the Landslide Zone on the Bureya River in 2018–2019 with Radar and Optical Satellite Images

Results are presented from monitoring the current state of the area of the landslide on the Bureya River in 2018–2019 using images from synthetic aperture radars and optical sensors of the Sentinel multisatellite system. Differential radar interferometry shows the stability of the landslide’s surface in the first four months after the landslide and since the end of July 2019. The small-scale dynamics of the surface are revealed within the landslide circus. It is shown that interferometry cannot be used to observe large modifications of the shoreline, in contrast to optical images, where the effects of the collapse of shoreline fragments and shoreline flooding were clearly observed. Ongoing landslide activity within the landslide circus and area of shoreline collapse is detected using satellite images. Continuous monitoring of this and other dangerous landslide zones on the Bureya River is needed.

Technologies for obtaining and processing of space radar images for monitoring the state of the Earth’s surface

The paper presents the main results of the analysis of the efficiency and suitability of satellite differential radar interferometry methods using free software products and satellite imagery for general purposes. The work used data from the Copernicus program of the European Aerospace Agency; processing was carried out for radar images of the Sentinel-1 satellite family. The result of the research is a series of recommendations on the use of the considered technology and the possibility of its implementation in enterprises, taking into account the revealed features, advantages and disadvantages.

Application of DInSAR and Spatial Statistics Methods in Analysis of Surface Displacements Caused by Induced Tremors

Induced seismicity is one of the negative phenomena caused by anthropogenic activities that include mining of minerals. This phenomenon manifests itself as sudden and unpredictable shocks of rock mass, which can cause surface deformation and damage to ground infrastructure. Until the advent of satellite radar interferometry that enables analysis of historical events, the characteristics of these unexpected surface deformations were difficult to assess. The main aim of the research was the spatial analysis of the geometry of surface displacements caused by eight induced tremors in the Rudna copper mine (SW Poland) and the dependence of deformation characteristics (vertical displacements, extent) on the induced shock energy. For this purpose, Sentinel-1 satellite imagery, the differential radar satellite interferometry (DInSAR) method and geographic information systems (GIS) based spatial statistics were used. Vertical displacements were mapped on the basis of 37 calculated interferograms. Spatial statistics on the pixel-to-pixel level were performed in the GIS Map Algebra environment. In the result, descriptive and spatial statistics characterizing deformations caused by individual shocks were calculated. The average values of vertical displacements ranged from −44 to −119 mm. Strong, statistical correlation between the extent, maximum vertical displacement, and energy values was determined. In addition, geometries of the formed deformation areas were analyzed and presented graphically. The results obtained in this research constitute development of a knowledge base on surface displacements caused by induced tremors in underground copper mining.

Ongoing automated ground deformation monitoring of Domuyo - Laguna del Maule area (Argentina) using Sentinel-1 MSBAS time series: Methodology description and first observations for the period 2015–2020

Synthetic Aperture Radar (SAR) Differential Interferometry (DInSAR) and its extensions to manage time series are nowadays well-known and mastered techniques to perform among others land-motion monitoring.We present here a fully automated monitoring service based on DInSAR and Multidimensional Small Baseline Subset (MSBAS) methods. The automated processing chain named “InSAR automated Mass processing Toolbox for multidimensional Time series” (MasTer) is demonstrated with the peculiar case of the Laguna del Maule and Domuyo volcanoes, which are known to undergo significant inflation up to several cm or tens of cm per year.The here-described monitoring service is made of three components: an InSAR command line processor, the MSBAS processor and a number of shell scripts automatizing all tasks, from data downloading to updated displacement maps and time series. Thanks to the European Commission Copernicus Service, data are freely available every 12 or 6 days along each orbit, depending on ESA acquisition plan. Linear deformation rate maps and time series of vertical and East-West ground deformation computed by the MasTer tool are updated every 1–6 days on a web page, according to the S1 data availability. Interested user can request additional time series at coherent pixels that wouldn't be displayed on the web page and receive them by e-mail within a minute.Processing chain and preliminary observations at Domuyo and Laguna del Maule test site are presented and commented. The nearly 6 years long 2D time series of ground deformation allow highlighting recent changes in the well-known deformation at both volcanoes: Domuyo inflation stabilizes since beginning of 2019 while deformation at Laguna del Maule seems to gently accelerate since mid 2018. New deformation features are also identified, such as a 2 km wide 3 cm/yr circular subsidence at Laguna del Maule as well as a 2 cm/yr downward and 1 cm/yr eastward movement located to the East of Laguna Fea.

Measuring the location and width of the Antarctic grounding zone using CryoSat-2

Abstract. We present the results of mapping the limit of the tidal flexure (point F) and hydrostatic equilibrium (point H) of the grounding zone of Antarctic ice shelves from CryoSat-2 standard and swath elevation data. Overall we were able to map 31 % of the grounding zone of the Antarctic floating ice shelves and outlet glaciers. We obtain near-complete coverage of the Filchner–Ronne Ice Shelf. Here we manage to map areas of Support Force Glacier and the Doake Ice Rumples, which have previously only been mapped using break-in-slope methods. Over the Ross Ice Shelf, Dronning Maud Land and the Antarctic Peninsula, we obtained partial coverage, and we could not map a continuous grounding zone for the Amery Ice Shelf and the Amundsen Sea sector. Tidal amplitude and distance south (i.e. across-track spacing) are controlling factors in the quality of the coverage and performance of the approach. The location of the point F agrees well with previous observations that used differential satellite radar interferometry (DInSAR) and ICESat-1, with an average landward bias of 0.1 and 0.6 km and standard deviation of 1.1 and 1.5 km for DInSAR and ICESat measurements, respectively. We also compared the results directly with DInSAR interferograms from the Sentinel-1 satellites, acquired over the Evans Ice Stream and the Carlson Inlet (Ronne Ice Shelf), and found good agreement with the mapped points F and H. We also present the results of the spatial distribution of the grounding zone width (the distance between points F and H) and used a simple elastic beam model, along with ice thickness calculations, to calculate an effective Young modulus of ice of E=1.4±0.9 GPa.

The Punatsangchhu-I dam landslide illuminated by InSAR multitemporal analyses

We use multitemporal analyses based on Synthetic Aperture Radar differential interferometry (DInSAR) to study the slope adjacent to the large Punatsangchhu-I hydropower plant, a concrete gravity dam under construction in Bhutan since 2009. Several slope failures affected the site since 2013, probably as a consequence of toe undercutting of a previously unrecognised active landslide. Our results indicate that downslope displacement, likely related to the natural instability, was already visible in 2007 on various sectors of the entire valley flank. Moreover, the area with active displacements impinging on the dam site has continuously increased in size since 2007 and into 2018, even though stabilization measures have been implemented since 2013. Stabilisation measures currently only focus on a small portion of the slope, however, the unstable area is larger than previously evaluated. Highly damaged rock is present across many areas of the entire valley flank, indicating that the volumes involved may be orders of magnitude higher than the area on which stabilisation efforts have been concentrated after the 2013 failure. The results highlight that satellite-based DInSAR could be systematically used to support decision making processes in the different phases of a complex hydropower project, from the feasibility study, to the dam site selection and construction phase.

Monitoring mining-induced subsidence by integrating differential radar interferometry and persistent scatterer techniques

ABSTRACT Surface subsidence is a dominant component of the displacement vector triggered by underground mining. Over the last few decades, Differential Interferometry Synthetic Aperture Radar (DInSAR) has been used to efficiently monitor this phenomenon with great spatial and temporal coverage. More advanced multi-temporal DInSAR (MTInSAR) algorithms have been proposed to overcome some of the limitations of conventional DInSAR. However, advanced MTInSAR approaches are also not perfect in terms of measuring mining subsidence (e.g., temporal decorrelation, ambiguity, nonlinearity). For this reason, we propose a fusion of the Persistent Scatterer Interferometry (PSInSAR) and DInSAR results. By combining these complementary techniques, the atmospheric errors in PSInSAR data are reduced and larger deformation rates could have been detected more accurately (thanks to DInSAR) than by an approach solely based on PS-InSAR. This allows to measure areas with fast-moving subsidence (1 m/year) due to ongoing underground coal exploitation. Data from ascending and descending orbits of Sentinel-1A\\B were used to obtain the vertical deformation component. The resulting integrated vertical deformation map was compared with the results from levelling benchmarks. The Root Mean Square Error (RMSE) calculated based on this comparison was 22 mm. Moreover, the maximal vertical cumulative subsidence detected in the study area was 1.05 m/year.

Monitoring of the landslide area state on Bureya river in 2018-2019 according to radar and optical satellite images

The monitoring results of the current state of landslide area on the Bureya River in 20182019 are given using images from synthetic aperture radars and optical sensors of Sentinel multi-satellite system. Differential radar interferometry technique allowed to reveal the stability of the landslide surface in the first four months after the landslide and since the end of July 2019. Small-scale dynamics of the surface within the landslide circus was detected. It is shown that the interferometric technique is inapplicable for the observation of the large-scale modifications of the shoreline unlike the optical images where the effects of the collapse of the shoreline fragments and shoreline flooding were clearly observed compared also with radar amplitude images. The ongoing landslide activity within the landslide circus and the coastline collapse area was detected using satellite images. It requires the establishment of continuous monitoring of this and other dangerous landslide zones on Bureya River.

Using PS-InSAR with Sentinel-1 Images for Deformation Monitoring in Northeast Algeria

Constantine city, Algeria, and its surroundings have always been affected by natural and human-induced slope instability and subsidence. Neogene clay-conglomeratic formations, which form the largest part of Constantine city, are extremely sensitive to the presence of water, which makes them susceptible to landslides. Fast and accurate identification and monitoring of the main areas facing existing or potential hazardous risks at a regional scale, as well as measuring the amount of displacement is essential for the conservation and sustainable development of Constantine. In the last three decades, the application of radar interferometry techniques for the measurement of millimeter-level terrain motions has become one of the most powerful tools for ground deformation monitoring due to its large coverage and low costs. Persistent scatterer interferometry (PS-InSAR) has a demonstrated potential for monitoring a range of hazard event scenarios and tracking their spatiotemporal evolution. We demonstrate the efficiency of Sentinel-1 data for deformation monitoring in Constantine located in the northeast of Algeria, and how an array of information such as geological maps and ground-measurements are integrated for deformation mapping. We conclude this article with a discussion of the potential of advanced differential radar interferometry approaches and their applicability for structural and ground deformation monitoring, including the advantages and challenges of these approaches in the north of Algeria.

Investigation of slope instabilities in NW Bhutan as derived from systematic DInSAR analyses

In this work we present a methodology based on remote sensing data to map and classify unstable slopes in high alpine areas and apply this methodology to the Himalaya of northwestern Bhutan. We leverage on radar images acquired by the ESA Envisat and the JAXA ALOS-1 satellites between 2007 and 2011. Synthetic aperture radar differential interferometry (DInSAR) is used to identify and quantify recent ground surface displacements associated with potentially unstable slopes. Optical satellite images and a high-resolution digital surface model is used for the geomorphological classification of individual landforms and deposits associated with displacements. The analysis of the geomorphological characteristics reveals that displacements are associated with: rock slides, mountain slope deformation and rock slope deformation (77.5%), soil creep (4%), soil slides (1.9%) and rock glaciers (12.3%); 4.3% of the detected displacements remain of unknown origin. The method applied here for the assessment of activity likelihood uses a very large number of interferograms obtained with images acquired by different satellites. The method, which is new and replicable, takes advantage of the combination of different acquisition geometries and then combines indices of vegetation cover, layover, velocity estimate and temporal sampling associated with each detected active area to assign a weight. The analysis shows that a cluster of unstable slopes exists in the northwest, potentially related to the presence of an important regional lineament and the distribution of permafrost. Comparatively little ongoing activity is detected in the south, but field validation documents substantial landslide activity in the recent geological past. The dataset here generated, containing 700 potentially unstable areas with an associated activity likelihood, is a novel dataset that makes an essential basis of future analysis to investigate rock slope instability distribution and predisposing factors. Moreover, this dataset represents a new important step towards future landslide hazard assessment in the Himalaya of Bhutan.