Differential Interferometric Synthetic Aperture Radar Research Articles

On the RFI Detection in Differential Interferometric Synthetic Aperture Radar

Abstract. Synthetic Aperture Radar (SAR) can image the ground with a wide area and high resolution at all times and in all weather and has become an important means of remote sensing. Differential interferometry SAR technology can obtain high-precision surface deformation information by processing more than two SAR images before and after deformation. In recent years, it has attracted widespread attention and research. However, due to the increasing number of ground electronic devices, ground radio frequency interference (RFI) has become one of the main problems in differential interferometry SAR processing, seriously affecting the performance of differential interferometry SAR imaging and differential interferometry surface deformation monitoring applications. In this paper, a clutter cancellation interference enhancement detection algorithm is proposed. By clutter suppression in the primary and secondary images, the interference-to-signal ratio is increased, which effectively improves the interference detection capabilities. The effectiveness of the algorithm in this paper is verified by the on-orbit measured data of the Lutan-1 satellites.

Long-term subsidence over the Upper Silesia Coal Basin identified on differential LIDAR (2012–2021) and InSAR (2015–2020) data

Long-term subsidence over the Upper Silesia Coal Basin identified on differential LIDAR (2012–2021) and InSAR (2015–2020) data

A New Inversion Method for Obtaining Underwater Spatial Information of Subsidence Waterlogging Based on InSAR Technology and Subsidence Prediction

Surface waterlogging disasters due to underground mining and geological status have caused the abandonment of fertile land, seriously damaged the ecological environment, and have influenced the sustainable development of coal resource-based cities, which has become a problem that some mining areas need to face. However, the traditional underwater terrain measurement method using sonar encompasses a time-consuming and labor-intensive process. Thus, an inversion method for obtaining the underwater spatial information of subsidence waterlogging in coal mining subsidence waterlogging areas is proposed, based on differential interferometric synthetic aperture radar (D-InSAR) and the probability integral prediction method. First, subsidence values are obtained in the marginal area of the subsidence basin using D-InSAR technology. Then, the subsidence prediction parameters of the probability integral method (PIM) are inverted by a genetic algorithm (GA) based on the subsidence values. Finally, the underwater spatial information of subsidence waterlogging is calculated on the basis of the prediction parameters. The subsidence waterlogging area in the Wugou coal mine was adopted as the study area, and the underwater spatial information of subsidence waterlogging was inverted by the proposed method. The results show that this method can effectively provide the underwater spatial information of subsidence waterlogging, including the maximum subsidence value, waterlogging volume, subsidence waterlogging area, and underwater terrain in the subsidence waterlogging area. Compared with field-measured data from the same period, the RMSE of water depth is 99 mm, and the relative error is 9.9%, which proves that this inversion method is accurate and can meet engineering precision requirements.

The influence of groundwater use on land subsidence in Bandung City

Bandung is a developing city with a high need for groundwater for various needs. Many research studies say groundwater usage is one of the causes of land subsidence but the results mostly just take one side either land subsidence or groundwater. If land subsidence can be estimated through the value of groundwater use, then this can help prevent calamity. Therefore, a correlation between groundwater usage and land subsidence is sought to see how much groundwater usage influences land subsidence. Land subsidence research was conducted using the Differential Interferometric Synthetic Aperture Radar (DInSAR) system with the SNAP application. The data used is the use of groundwater from 2017 to 2022 and Sentinel 1-A imagery of six images for annual research and sixty-six images for monthly research. The yield of the average settlement each year from January 2017 to May 2022 is approximately 5cm with a linear regression coefficient of determination of 21% while the groundwater use regression with subsidence per month is not linear but wavy. From this conclusion, another research can be developed regarding other factors causing land subsidence besides the factor of groundwater use which can then be seen how much influence these factors have on land subsidence that occurs.

Multisource remote sensing image fusion processing in plateau seismic region feature information extraction and application analysis – An example of the Menyuan Ms6.9 earthquake on January 8, 2022

Abstract A 6.9 magnitude earthquake hit Menyuan County, Haibei Prefecture, Qinghai Province, at 01:45 PM Beijing time on January 8, 2022 (17:45 PM GMT time on January 7, 2022). To explore the magnitude of the earthquake deformation and the affected area, this work combined optical remote sensing interpretation, interferometric synthetic aperture radar (InSAR) coseismic deformation extraction, and field surveys for research and analysis. Relying on the high-resolution Earth observation system of the Qinghai Remote Sensing Center for Natural Resources, high-resolution GF1D, GF2, and TRIPLESAT optical remote sensing images were acquired immediately after the earthquake. The airborne triangulation encryption method was used to carry out orthographic correction, fusion, and mosaic processing of digital orthophoto map (DOM) and digital surface model (DSM) images, and first-hand optical remote sensing images of the disaster areas were obtained. Based on differential InSAR (D-InSAR), small baseline subset InSAR (SBAS-InSAR) and lifting rail fusion methods, the coseismic deformation field and deformation rate of the lifting rail direction were obtained by using Sentinel-1A data processing before and after the earthquake. Combined with optical interpretation, InSAR deformation, and field investigation, the results show that the deformation trend of the line of sight (LOS) images to the north and south of the ascending and descending orbits show an obvious opposite trend. The surface shape variables are −50 to 45 cm and −65 to 72 cm, respectively, and the deformation rate before the earthquake reached 25 cm/year. The deformation field characteristics show that the earthquake was mainly due to thrust, and the coseismic deformation field fractured along the WNW‒ESE direction with a length of approximately 33 km. The areas affected by 10 mm, 20 cm, and 50 cm deformation magnitudes in the whole earthquake area were 975.14, 321.10, and 38.55 km2, respectively. Within 20 km, there were two main affected townships, namely, Sujitan Township and Huangcheng Mongolian Township. Within 50 km, there were four main affected towns and townships, namely, Sujitan Township, Mongolian Township of the Imperial city, Qingshizui town, and Haomen town.

Tracking Centimeter‐Scale Water Level Changes in Swedish Lakes Using D‐InSAR

AbstractLakes are valuable water resources that support aquatic and terrestrial ecosystems and supply fresh water for the agricultural, industrial, and urban sectors worldwide. Although water levels should be tracked to monitor these services, conventional gauging is unfeasible in most lakes. This study applies Differential Interferometric Synthetic Aperture Radar (D‐InSAR) to estimate small water level changes, less than 2 cm, in Swedish lakes over 6‐day intervals. We validated the method across the shores of 30 Swedish lakes with gauged observations in 2019. We used Sentinel‐1A/B images with a 6‐day temporal separation to construct consecutive interferograms and accumulated the phase changes in pixels of high coherence to build a time series of water levels. We find that the accumulated phase change obtained by D‐InSAR replicates the magnitude of water levels in seven lakes in Southern Sweden, where water levels change slowly, less than 2 cm per 6‐day period, as validated by in‐situ gauges. In addition, this study demonstrates the application of D‐InSAR to estimate the long‐term direction of water level change (i.e., increase or decrease) in all 30 lakes. This work reveals the utility of high temporal resolution water level observations in support of other satellite water level instruments such as conventional altimeters and the recently launched Surface Water and Ocean Topography Mission.

Distributed satellite system autonomous orbital control with recursive filtering

In this article, we propose a recursive orbital elements filter for autonomous control of Distributed Satellite Systems (DSS) that significantly reduces the variance of relative orbital elements between the observed and the desired satellite orbits. Leveraging satellite kinematics and control inputs data, combined with a model of relative dynamics, the filter provides smooth and continuous orbital control, while minimizing propellant consumption. In conjunction with Precise Point Positioning (PPP) navigation, the proposed filter enables onboard continuous low-thrust control compatible with high-performance electric propulsion. We also propose a restricted transverse/normal control law that simplifies the thruster's configurations and/or attitude manoeuvres required for propulsion pointing. The applicability and validity of our proposed techniques are verified by numerical simulations with two case studies: a constellation for Differential Interferometric Synthetic Aperture Radar (DInSAR) for global infrastructure monitoring; and a maritime domain awareness mission based on along-track interferometric synthetic aperture radar which requires single-pass interferometry for responsive ship traffic surveillance, and the coverage of a very large maritime zone with high revisit rates.

INVESTIGATIONS ON INSAR DATA PROCESSING STANDARD FOR VOLCANO ISLAND MONITORING IN INDONESIA

Abstract. In critical situations such as disaster and humanitarian relief, the reliable geospatial data will present an appropriate decision on a timely manner. As fundamental datasets, large-scale topographic maps are are mandatory in order to perform geospatial analysis for many societal challenges. Indeed, Large Scale Topographic Mapping in Indonesia shall be accelerated in an innovative and productive way to consider the production efficiency, especially for the geospatial data acquisition as its primary source. Interferometric Synthetic Aperture Radar (InSAR) data acquisition presents some advantages, especially in conjunction with the security clearance and global weather as some main constraints for the geospatial data acquisition. In terms of disaster preparedness and emergency response, radar interferometry techniques can play an important role by generating a Digital Elevation Model (DEM) as an input to Decision Support Systems (DSS). In addition, the techniques of differential Interferometric Synthetic Aperture Radar (D-InSAR) can provide the earth surface deformation from time series Radar Datasets. A set of standards related to the InSAR data acquisition are essential, especially with regards to the improved sensors, and processing methods implemented by the worldwide space agencies nowadays. Hence, the precise definition of a standard is fundamental in order to prepare the InSAR data as one potential source of geospatial data and information, especially for LSTM data production. Generated time series of Digital Elevation Model (DEM) can identify the potential cause of 2018’s Sunda Strait tsunami (Tampubolon, 2019). It was related with the increasing eruption activity of Anak Krakatau (Child of Krakatoa). From DEM analysis, the Volcanic mudflow material avalanche has been detected before the tsunami hit the coastal surrounding area. In this paper, more advanced techniques was investigated by the combination between Time Series DEM Analysis and Ground Displacement detection. The focus on the integration between reliable TanDEM-X and up-to-date Sentinel 1A/B was proposed on another volcano island of Gamalama in Ternate. As TanDEM-X uses X-band as its medium wave, it can produce more reliable DEM as a reference data. On the other hand, Sentinel 1 uses C-band that can contribute to detect the ground deformation over the aforementioned volcano island. TanDEM-X uses a more robust and consistent approach to scan the earth surface by single data acquisition scheme, which is generally more accurate and reliable for the DEM generation. However, many factors influence the selection of a platform that can be best suited for radar interferometry. Initially, the German TanDEM-X Coregistered Singlelook Slant-range Complex (CoSSC) using bi-static InSAR approach has been implemented in order to generate DEMs comply with the LSTM specification in Indonesia. The basic principle is performing a simultaneous measurement of the same scene and identical doppler spectrum by using 2 sensors, thereby avoiding temporal decorrelation (DLR, 2012). Subsequently, the differential InSAR techniques by using Sentinel 1A/B has been performed in order to detect the ground deformation. Finally, tt can be shown that the reliable TanDEM-X data has increased the ground deformation resolution and accuracy in order to provide potential solution for disaster preparedness.

LU TAN-1 SAR SATELLITE CHARACTERISTICS AND PRODUCTIONS IN THE PHASE OF IN-ORBIT TEST

Abstract. Lu Tan-1 (LT-1) has finished the in-orbit test and will be delivered to the users in 2023. In this paper, we discussed the satellite characteristics including the satellite mission, the platform as well as the payload. The satellite constellation was designed following two main demands, i.e., digital elevation model (DEM) generation and deformation monitoring. Thus, we provided two kinds of productions. First was the DEM created using the images provided by helix bistatic formation. Second was the deformation products created using that of pursuit monostatic formation. The deformation products were finally classified into three different types given the processing technologies. They were deformation field provided by differential interferometric SAR (InSAR, DInSAR), deformation velocity field provided by stacking, and deformation time series provided by multi-temporal InSAR. DEM data were validated to be better than 5 m compared to ICESat. Deformation field, deformation velocity field, as well as deformation time series were validated to be better than 2.7 mm, 8.6 mm/yr and 3.7 mm, respectively.

ADVANCED ANALYSIS TOOLS FOR THE EUROPEAN GROUND MOTION SERVICE DATA

Abstract. This paper is focused on Advanced Differential Interferometric SAR (A-DInSAR). In the first part, the paper describes the European Ground Motion Service (EGMS), a new service of the Copernicus Land Monitoring Service. The EGMS provides consistent, regular, standardized, harmonized and reliable information regarding natural and anthropogenic ground motion over Europe. It is derived from A-DInSAR analysis of Copernicus Sentinel-1 data. The EGMS includes three main products: Basic, i.e. basic deformation maps delivered for individual and consistent frames of image stacks; Calibrated, i.e. deformation map integrated into a reference Global Navigation Satellite System network; and Ortho, which includes the East-West and Up-Down deformation, obtained by combining the ascending and descending results. The second part of the paper describes examples of data analysis. The first one is a clustering of PSI results, which highlights the so-called Active Deformation Areas (ADAs). The second one is an automatic classification of the ADAs. The third analysis concerns the differential deformation maps, which are useful to highlight areas where high deformation gradients occur. Such gradients are often associated to damages in buildings and infrastructures.

Co-seismic surface displacement of the June 21, 2022 MW6 Khōst, Afghanistan earthquake from InSAR observations

A robust estimation of the earthquake location, seismic moment, and fault geometry is essential for objective seismic hazard assessment. Seismic events in a remote location, specifically in the absence of seismic and GNSS networks, can be investigated effectively using the InSAR-based technique. This study adopts the Differential Interferometric SAR (DInSAR) technique to quantify the co-seismic surface displacement caused by the June 21, 2022, Khōst MW6 earthquake that occurred along the western plate boundary between the Indian and Eurasian plate. The interferograms show that the maximum surface deformation occurred on the northwest and southwest of the fault line. From coherence, the Line of Sight (LOS) displacement, and the co-seismic surface displacement analysis, it has been observed that surface deformation was most pronounced in the southwest region of the fault line, and the surface has moved to the opposite direction along the fault line, which indicates a sinistral slightly oblique strike-slip movement. This InSAR-based observation appears consistent with the seismic waveforms derived from co-seismic surface displacements. Further, it has been argued that the slip deficit accumulated during the period of the last about 48 years along the frontal region of the northward extension of the Suleiman range and associated fault zone is qualitatively estimated at about 1.5 m, which is consistent with the seismic waveforms derived finite slip model.

Reconnaissance to characterisation of land subsidence due to groundwater overdraft and oil extraction in and around Mehsana City, Gujarat, India by long-term hybrid differential interferometric SAR technique

We present a framework for studying reconnaissance to characterisation of land subsidence in the slowly subsiding city of Mehsana, Gujarat, India, due to groundwater overdraft and oil extraction. Considering interferometric synthetic aperture radar (InSAR) data availability constraints, we first conducted a long-term conventional Differential InSAR (DInSAR) investigation followed by time-series advanced DInSAR analyses by Persistent Scatterer InSAR (PSInSAR). We identified land subsidence in different parts of the study area, with subsidence rates ranging from ≤ -1 cm/yr to ≥ -3 cm/yr. During the entire observation period (2004–2019), the core urban area has been consistently subsiding with differential subsidence rates of −1.7 to −2.1 cm/yr during 2004–2006, −1.6 to −1.7 cm/yr during 2007–2011 and −2.6 to −2.9 cm/yr during 2016–2018 in conventional DInSAR and −2.5 to −3.2 cm/yr in advanced DInSAR. The subsidence measurements by collateral DInSAR observations in multifrequency and/or multi-imaging modes during 2016–2017 agree well in terms of the spatial extent of subsiding areas and the rates of subsidence. We characterised land subsidence in four type areas due to the diverse causes based on the temporal behaviour of land subsidence: (a) densely-populated city centre, (b) dairy plants and other industries in urban/peri-urban areas, (c) emerging urban clusters in peri-urban/rural areas, and (d) oilfields with agri-horticulture farms in the rural areas. We found a consistently increasing land subsidence trend in ‘a’, reducing land subsidence in ‘b’, newly emerging and rapidly growing land subsidence in ‘c’, and spatially-extensive subtle land subsidence in ‘d’. From the temporal nature of groundwater level (GWL) decline and land subsidence, we inferred that the land subsidence has been occurring primarily due to groundwater overdraft associated with urban growth, industry and agri-horticultural farms and secondarily due to oil extraction in the southeastern part of the study area. A comparison of annual rainfall difference from the long-term average vs GWL change vs land subsidence shows that the rainfall deficit during 2–3 consecutive years and groundwater overdraft are primarily related to land subsidence in the study area.

A Comprehensive Review on Mining Subsidence and its Geo-environmental Impact

Over the course of several decades, subsidence has exerted a notable impact on the mining sector. The preponderance of subsidence occurrences is evident within coal mines. Remote sensing and Geographic Information Systems (GIS) have emerged as principal instruments for the evaluation and characterization of subsidence phenomena. The manifestation of mininginduced subsidence engenders concerns encompassing roof collapse, infrastructural damage, and the formidable challenge of preserving human lives. The repercussions of mining-related subsidence extend to indigenous flora and subterranean water reservoirs. This phenomenon critically impedes the sustainable advancement of mining zones, precipitates the depletion of natural reservoirs, and engenders a host of ecological and environmental predicaments that cast an adverse influence on socio-economic dynamics. Within mining contexts, subsidence manifests as both vertical and horizontal ground displacement, presenting as fissures, depressions, troughs, and sinkholes. The present article furnishes a comparative discourse on diverse methodologies harnessed for the assessment of mining-induced subsidence. The scholarly community has employed a repertoire of eight predominant techniques, as delineated in the conclusive remarks of this study. Over the bygone two decades, considerable strides have been taken, enabling the deployment of sophisticated paradigms, such as remote sensing and GIS, Light Detection and Ranging (LiDAR), and Differential Interferometric Synthetic Aperture Radar (DiNSAR), for the identification and quantification of land subsidence phenomena.

LOS Deformation Correction Method for DInSAR in Mining Areas by Fusing Ground Data without Control Points

The traditional leveling, total station, and global navigation satellite system (GNSS) and the new differential interferometric synthetic aperture radar (DInSAR) and terrestrial laser scanning (TLS) systems have their own advantages and limitations in the deformation monitoring of mining areas. It is difficult to obtain accurate deformation information only using single-source measurement data. In this study, we propose an LOS deformation correction method for DInSAR in mining areas by fusing ground data without control points. Based on free space data, small deformations at the edges of mining influence areas accurately obtained using DInSAR. By combining leveling/GNSS and TLS methods, it was possible to obtain large deformations in central areas without the need for control points located outside the mining influence range. For overcoming the non-uniform coordinates of the “space–ground” data and the limited overlap of the effective measurement ranges, the subsidence prediction model was employed to assist in its fusion. In addition, in LOS deformation correction, we retained the non-full cycle phase of DInSAR and replaced the full cycle phase with the one from the data fusion. Engineering experiments have shown that the correction results preserve the differences in the LOS deformations at the edge areas of the mine influence range, and they recover the lost LOS deformations at the center areas. Using the difference in the LOS deformation before and after correction as the verification indicator, the maximum absolute value of the errors after correction was 143 mm, which was approximately 6.4% of the maximum LOS deformation. In addition, there were still two errors that were large (−112 mm and −89 mm, respectively), and the absolute values of errors were not more than 75 mm. For all errors, the mean absolute value was 36 mm. Compared with 399 mm before correction, the error was reduced by 91%. This study provides technical support and theoretical reference for deformation monitoring and control in mining areas.

Analysis of Vertical Deformation and Potential Formation of New Faults Cause by Earthquake Using the DInSAR Method (Case Study: 2022 Cianjur Earthquake)

In this study, we focus on the repetitive nature of earthquakes along known fault lines and their potential to create new fault segments. Our primary aim is to enhance our understanding of fault patterns and distribution, facilitating more efficient and accurate earthquake disaster mitigation efforts. Our research specifically targets the vertical deformation resulting from the 2022 Cianjur Earthquake. To achieve this, we employed a sophisticated technique involving data processing from the Sentinel 1A satellites using the Differential Interferometric Synthetic Aperture Radar (DInSAR) method. This method allowed us to derive earthquake-induced displacement values in meters with an impressive level of accuracy, down to the centimeter scale. Our analysis revealed a conspicuous fringe pattern in the interferogram phase data, which did not align with the nearby Cimandiri Fault. This discrepancy led us to suspect the emergence of a new fault or fault segment. By comparing Sentinel 1A satellite images before and after the earthquake, we observed phase differences ranging from -3.112 to 3.117 phases. These recurring phase differences clustered at coordinates 6?48'48" South Latitude and 107?06'05" East Longitude, pinpointing the epicenter of the Cianjur earthquake on November 21, 2022. Furthermore, we calculated line-of-sight (LoS) displacement values ranging from 0 to minus 102 millimeters, indicating vertical subsidence in the vicinity of the 2022 Cianjur earthquake. In conclusion, our research underscores the utility of the DInSAR method for assessing Earth's surface deformation patterns, making it a valuable tool for various earthquake-related analyses.

Identification of Vulnerability Due to the Pasaman M6.2 Earthquake on 25 February 2022 Using Satellite-Based Methods and Field Surveys

The Pasaman earthquake which occurred on 25 February 2022, with a magnitude of 6.2, caused casualties and infrastructure damage. Vulnerability identification determines the potential extent to which a system or unit tends to be damaged. Vulnerability identification in this study was carried out based on four vulnerability indicators, namely: rate of soil movement from satellite image processing, soil type classification based on Vs30, corrected isoseismal shakemap, and residential area maps. Each indicator, with their respective weightage, is then scored and summed to evaluate the vulnerability of areas in the vicinity of Pasaman earthquake. The processing of Sentinel-1 SLC satellite data using the advanced Differential Interferometric Synthetic Aperture Radar (DInSAR) produces a deformation rate around area of epicenter. Areas that have high vulnerability generally have a value of ground movement rate in the form of subsidence above 5 cm/year. These areas were predominantly residential and experienced significant damage during the earthquake. The soil type in these regions was classified as medium soil, and the intensity of shocks during the earthquake was categorized as VI MMI or higher. This study was conducted in the area near the epicenter of the Pasaman earthquake, such as in the district Pasaman, Bonjol, Pasaman, Palembaya, and Lubuk Basung. A study of disaster vulnerability identification is carried out to reduce the losses and minimizing the exposure of the population to disasters. The results of vulnerability identification can be used as part of education and literacy to reduce the risk of earthquake disasters.

The 2023 Mw 7.8 and 7.6 Earthquake Doublet in Southeast Türkiye: Coseismic and Early Postseismic Deformation, Faulting Model, and Potential Seismic Hazard

Abstract On 6 February 2023, Mw 7.8 and 7.6 earthquakes struck southeast Türkiye and northwest Syria. They are the largest earthquakes in Türkiye in over 80 yr, causing significant damage and fatalities. We used Advanced Land Observation Satellite-2 and Sentinel-1 Synthetic Aperture Radar images to obtain near-field coseismic displacements by Differential Interferometric Synthetic Aperture Radar (DInSAR) and pixel offset tracking (POT). Discontinuities of the surface deformation suggest that the Mw 7.8 event ruptured ∼320 km along the East Anatolian fault, and the Mw 7.6 event ruptured ∼150 km near Elbistan, southern Türkiye. We inverted these earthquakes' fault geometry and slip distribution based on Global Navigation Satellite Systems, DInSAR, and POT displacements. The estimated fault slip model shows that the first Mw 7.8 event ruptured a steeply southeast-dipping fault, and the seismogenic fault of the second Mw 7.6 event is north-dipping with complex geometry. The dip angle of subfaults of the Mw 7.6 earthquake decreases from east to west. Faults responsible for the two earthquakes are dominated by left-lateral strike-slip motion, with the maximum slip of ∼9.1 m. Early postseismic deformation within two months exhibits displacement discontinuities in the Amanos and Pazarcık segments and the Çardak fault, suggesting that the afterslip partially compensated the coseismic slip deficit at the shallow depths. Furthermore, static Coulomb failure stress changes induced by the two earthquakes indicate that the southwestern Pütürge segment of the East Anatolian fault has a high risk of future rupture.

The Stability Analysis of Mt. Gongga Glaciers Affected by the 2022 Luding MS 6.8 Earthquake Based on LuTan-1 and Sentinel-1 Data

On 5 September 2022, an MS 6.8 earthquake occurred in Luding county, Sichuan province, China, with the epicenter located approximately 20 km from the main peak of Mount (Mt.) Gongga. The dynamic situation of Mt. Gongga glaciers has received widespread attention. In this study, Mt. Gongga was selected as the study area, and L-band LuTan-1 (LT-1) satellite data were used for differential interferometric synthetic aperture radar (D-InSAR) processing to obtain the coseismic landform in Luding. Based on Sentinel-1A images, pixel offset tracking (POT) technology was used to obtain the surface movement velocities of the glaciers before, during, and after the earthquake. The results showed that the overall preseismic movement of the glaciers was fast in the area where the ice cascade of the Hailuogou Glacier reached a maximum average deformation rate of 0.94 m/d. Moreover, time-series monitoring of the postseismic glaciers showed that the surface flow velocities of some glaciers in the study area increased after the earthquake. The flow velocity at the main peak of Mt. Gongga and the tongue of the Mozigou Glacier accelerated for a period after the earthquake. The study concluded that the earthquake was one of the direct causes of the increase in glacier flow velocity, which returned to a stable state more than 70 days after the earthquake. The relevant monitoring results and research data can provide a reference for earthquake-triggered glacial hazards and indicate the effectiveness of LT-1 in identifying and monitoring geological hazards.

VALIDATION OF FULL-RESOLUTION DINSAR-DERIVED VERTICAL DISPLACEMENT IN CULTURAL HERITAGE MONITORING: INTEGRATION WITH GEODETIC LEVELLING MEASUREMENTS

Abstract. Towards revealing the potential of satellite Synthetic Aperture Radar (SAR) Interferometry (InSAR) for efficient detection and monitoring of Cultural Heritage (CH) encouraging resilient built CH, this study is devoted to the validation of InSAR-derived vertical displacements with a full-resolution perspective taking advantage of high-precision geodetic levelling measurements. Considering the Cathedral of Como, northern Italy, as the case study, two different Persistent Scatterer Interferometry (PSI) techniques have been applied to Cosmo-SkyMed high-resolution SAR images acquired in both ascending and descending orbit tacks within the time interval of 2010–2012. Besides using the simplified approach for obtaining the vertical displacement velocity from Line of Sight (LOS) velocity, a weighted, localized, multi-track Vertical Displacement Extraction (VDE) approach is proposed and evaluated, which uses the technical outcome of Differential InSAR (DInSAR) and spatial information. The results, using a proper PSI technique, showed that the accuracy level of extracted vertical displacement velocities in a full-resolution application is ca. 0.6 [mm/year] with a dense concentration of InSAR-Levelling absolute errors lower than 0.3 [mm/year] which are reliable and reasonable levels based on the employed validation framework in this study. Also, the weighted localized VDE can significantly decrease the InSAR-Levelling errors, adding to the reliability of the InSAR application for CH monitoring and condition assessment in practice.

Coseismic Source Model of the February 2023 Mw 6.8 Tajikistan Earthquake from Sentinel-1A InSAR Observations and Its Associated Earthquake Hazard

On 23 February 2023, an Mw 6.8 earthquake struck the border of Tajikistan and Xinjiang China, the source mechanism remains controversial according to different seismic inversions. To better comprehend the source characteristics and the surface deformation pattern, we used the ascending and descending orbital Sentinel-1A SAR data to obtain the coseismic deformation of this earthquake based on the traditional two-pass differential interferometric synthetic aperture radar (InSAR). The source model is inverted from the InSAR coseismic deformation results. The possible Coulomb Failure Stress (CFS) transfer is analyzed based on the preferred source model. The results illustrate that the earthquake ruptured a blind left-lateral strike-slip fault of strike 28.1° with a maximum slip of 1.53 m and the total geodetic moment is 1.99 × 1019 N·m (Mw 6.83). The strike direction and the fault characteristics suggest the Seismogenic fault is a secondary fault of the Sarez–Karakul Fault System. The 2015 Mw 7.2 Sarez Earthquake plays a triggering role in the occurrence of the 2023 Tajikistan earthquake. Earthquake hazard on Sarez–Karakul Fault System and Sarez–Murghab Thrust System is enhanced due to the Coulomb stress loaded by the Tajikistan earthquake.