Crustal Deformation of the Kendeng Fault Branches Area from GNSS and InSAR Data in Surabaya City, Indonesia

Slip rates on active faults derived from the interseismic velocity field are critical to understanding seismic hazards in metropolitan cities. This study integrated the data from the Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR) to evaluate the interseismic velocities in the second-largest city in Indonesia, Surabaya, where branches of the Kendeng fault (the Surabaya and the Waru faults) pass through. Data from 16 campaign-mode GNSS stations collected between 2017 and 2020 from previous research are reprocessed to estimate the velocity field. Horizontal velocities under the ITRF frame range between -23.8 mm/yr and 47.9 mm/yr toward the southeast. Vertical velocities generally range between -1.3 mm/yr and -112.2 mm/yr. Sentinel-1A SAR data of both ascending and descending tracks acquired between November 2014 and July 2020 were used to generate the interferograms with the InSAR Scientific Computing Environment (ISCE) software. Furthermore, cumulative displacement time series were constructed using the Small BAseline Subset (SBAS) technique within the Generic InSAR Analysis Toolbox (GIAnT). This study also carried out the detection of outlier SAR epochs to improve the precision of Line-of-sight (LOS) velocity estimates. The LOS velocities range from -14.8 to 10.8 mm/yr in the ascending track and from -12.7 to 9.5 mm/yr in the descending track. These results will facilitate the detection of coupling behaviors on the Kendeng fault branches, which can improve our understanding of seismic risks in the Surabaya area.

Calculation of vertical displacement of the earth surface in the “Vostochny” open pit using radar data

The paper deals with the issues of assessment of the condition and changes in the land surface on the territory of the Vostochny open pit (Kemerovo region). The application of the multi-pass series of Sentinel-1 satellite radar data using the Small Baseline Subset (SBaS) method to determine the Earth surface displacement dynamics using constructed vertical displacement maps is demonstrated.

Multitemporal and Multisensor InSAR Analysis for Ground Displacement Field Assessment at Ischia Volcanic Island (Italy)

Volcanic islands are often affected by ground displacement such as slope instability, due to their peculiar morphology. This is the case of Ischia Island (Naples, Italy) dominated by the Mt. Epomeo (787 m a.s.l.), a volcano-tectonic horst located in the central portion of the island. This study aims to follow a long temporal evolution of ground deformations on the island through the interferometric analysis of satellite SAR data. Different datasets, acquired during Envisat, COSMO-SkyMed and Sentinel-1 satellite missions, are for the first time processed in order to obtain the island ground deformations during a time interval spanning 17 years, from November 2002 to December 2019. In detail, the multitemporal differential interferometry technique, named small baseline subset, is applied to produce the ground displacement maps and the associated displacement time series. The results, validated through the analysis and the comparison with a set of GPS measurements, show that the northwestern side of Mt. Epomeo is the sector of the island characterized by the highest subsidence movements (maximum vertical displacement of 218 mm) with velocities ranging from 10 to 20 mm/yr. Finally, the displacement time series allow us to correlate the measured ground deformations with the seismic swarm started with the Mw 3.9 earthquake that occurred on 21 August 2017. Such correlations highlight an acceleration of the ground, following the mainshock, characterized by a subsidence displacement rate of 0.12 mm/day that returned to pre-earthquake levels (0.03 mm/day) after 6 months from the event.

Feasibility of Artificial Slope Hazards Identification in Regional Mountainous Highway Using SBAS-InSAR Technique: A Case Study in Lishui, Zhejiang

Safety status of artificial slopes is significant for the operation and maintenance of highway to mitigate the risk; thus, slope hazard identification is necessary. In order to realize large-area and low-cost application for regional highway, taking the Longqing Highway (length of 55 km) as a case study, the SBAS-InSAR (Small Baseline Subset-Interferometric Synthetic Aperture Radar) technique is adopted to detect the ground deformation and conduct hazard identification based on slope dip, aspect, geological data and historical hazard record. Field survey is carried out to verify the identified potential hazards. Results show that the detected potential hazards are distributed mainly in the areas consisting of granite residual and the Quaternary soil. Six potential hazards identified by the SBAS-InSAR-based method are roughly in accordance with the on-site verification. It is suggested that the SBAS-InSAR technique has the ability to obtain the slope deformation accurately and reveal the safe condition of the slopes. The SBAS-InSAR technique can be suitable for assistance in regional highway slope inspection.

Neotectonics of the Western Suleiman Fold Belt, Pakistan: Evidence for Bookshelf Faulting

The Suleiman Fold-Thrust Belt represents an active deformational front at the western margin of the Indian plate and has been a locus of major earthquakes. This study focuses on the western part of the Suleiman Fold-Thrust Belt that comprises two parallel NW–SE oriented faults: Harnai Fault and Karahi Fault. These faults have known thrust components; however, there remains uncertainty about the lateral component of motion. This work presents the new observation of surface deformation using the Small Baseline Subset (SBAS), Interferometric Synthetic Aperture Radar (InSAR) technique on Sentinel-1A datasets to decompose displacement into the vertical and horizontal components employing ascending and descending track geometries. The subsurface structural geometry of this area was assessed using 2D seismic and well data. In addition, geomorphic indices were calculated to assess the relative tectonic activity of the area. InSAR results show that the Karahi Fault has a ~15 mm right-lateral movement for descending and ~10 mm/for ascending path geometries. The Harnai Fault does not show any lateral movement. Seismic data are in agreement with the InSAR results suggesting that the Harnai Fault is a blind thrust. This work indicates that the block between these two faults displays a clockwise rotation that creates the “bookshelf model”.

UNDERSTANDING VERTICAL GROUND DISPLACEMENT FROM P-SBAS USING GETIS-ORD GI* STATISTIC

The Differential Synthetic Aperture Radar Interferometric (DInSAR) algorithm has already shown its importance in volcanicmonitoring. However, it is limited by atmospheric perturbations or temporal decorrelation, implying the existence of lowcoherencerecords that must be discarded. In vast studied areas, with thousands of points unevenly distributed, theinterpretation of the results is usually complicated. This text presents an analysis of the vertical component variation onTenerife island (Canary Islands), from 2005 to 2010, using Getis-Ord Gi* spatial statistic on ENVISAT DinSAR images.The ascending and descending images have been processed using the Parallel Small BAseline Subset (P-SBAS)algorithm, within ESA Grid Processing on Demand cloud environment. From Line of Sight results of both tracks, the verticaldeformation speeds have been calculated over 72,207 points with high coherence (> 0.7). Finally, the Gi* statistic hasbeen applied, obtaining a map with statistical significance, where the high values of Gi*, both positive and negative, implythe spatial clustering of likely ground movements. This map highlights areas with variable vertical kinematics on TenerifeIsland, contributing to understanding of its geodynamics. The displacements obtained coincide with previous studies, evenshowing possible new relationships between some phenomena that should be considered. The Gi* spatial statistic is anefficient and quick tool to extract information in a regional scale kinematic study.

Analysis of Surface Deformation in East Dongting Lake Based on 2016-2019 Sentinel-1A Dataset

In this study, 84 scenes Sentinel-1A satellite datasets from October 2016 to September 2019 were used to analyze surface deformation in East Dongting Lake, China, by employing the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) method. The data are divided into two seasons, i.e., the flood and dry seasons. It was suggested that the surface deformation is related to the distribution of the river network and water flow activities. During the dry season, the water flow is active along the internal river, scouring the surrounding soil. During the flood season, the water flow basically occurs around the external drainage network. By qualitatively comparing surface deformation and precipitation changes as well as changes in soil erosion, it is found that the deformation was highly related to soil erosion and seasonal precipitation. The precipitation in the flood period is heavy than that in the dry season. Therefore, the runoff with amount silt will scour the soil in the passing area, resulting obvious surface deformation. During the dry period, surface deformation is smaller due to the less precipitation.

Monitoring stability of embankment dams in response to 2019 Iran Flood event

<p>In April 2019, large parts of Khuzestan province in Iran were affected by intense record rainfall in the Zagros mountains. Persian Gulf catchment received approximately 30% of its long-term average rainfall over the course of a few days. Karkheh and Dez, two of the major rivers in this catchment, overflowed their banks. As several dams, including Karkheh, with the country's largest capacity, reached their limits, the water had to be released from the reservoirs, which resulted in flooding downstream of the dams. Several cities and more than 200 villages were flooded, and many people had to be evacuated. Many of the dams affected by the 2019 flood were embankment dams,  previously reported to exhibit post-construction settlements, at places reaching 13 cm/yr. Therefore, during and after the flood,  significant concerns were raised about their health and stability.</p><p>In this study, we use Sentinel-1 InSAR to monitor embankment dams' response in Khuzestan to the 2019 flood event. We process the full archive of Sentinel-1 using the Small Baseline Subset approach and estimate the time series of displacement for three different embankment dams in Khuzestan province. The first two studied dams are Karkheh and Gotvand, which have the country's largest capacities and became operational in 2001 and 2012, respectively. The third studied dam is the Masjed-Soleyman dam, previously reported to sustain a high displacement rate since its operation in 2002.</p><p>The Sentinel-1 InSAR displacement results indicate that all observed dams exhibit long-term post-construction settlement before the flood, with rates varies from approximately 1 cm/yr for the Karkheh dam to 5 cm/yr for Gotvand dam and 8 cm/yr for Masjed-Soleyman dam. The time series of displacement for Karkheh and Gotvand dams show gentle changes of displacement in response to the increase in water level following the flood. However, for the Masjed-Soleyman dam, the movement accelerates sharply after the flood with more than 2 cm of displacement on the crest in only two months. For the Masjed-Soleyman dam experiencing the most severe effect of the flood, we also analyzed high-resolution data from TerraSAR-X and COSMO-SkyMed. The results provide a detailed picture of the displacement pattern over the crest and the dam's body before and after the flood.</p>

Using minimal spanning tree based ICA optimization for volcanic unrest determination

<p>Over the years, various satellites like ERS-1, ERS-2 and Envisat has been in use for the interferometric capability for a wide range of geophysical and environmental applications. With the launches of Sentinel-1A and 1B satellites in 2014 and 2016 respectively, the availability of SAR data from every part of the world has been increased many folds. With short revisit times of 1-6 days, the Sentinel-1 and the planned Tandem-Land NISAR missions provide an unprecedented wealth of topography and surface change data using InSAR technique. Utilizing these Synthetic Aperture Radar (SAR) acquisitions, repeated approximately from the same point in space at different times, it is possible to produce measurements of ground deformations at some of the world’s active volcanoes and can be used to detect signs of volcanic unrest. Most of the existing traditional algorithms like Permanent Scatterer (PS) analysis and Small Baseline Subset (SBAS) technique are computationally extensive and cannot be applied in near real time to detect  precursory deformation and transient deformations. To overcome this problem, we have adapted a minimum spanning tree (MST) based spatial independent component analysis (ICA) method to automatically detect deformation signals of volcanic unrest. We utilize the algorithm’s capability to isolate signals of geophysical interest from atmospheric artifacts, topography and other noise signals, before monitoring the evolution of these signals through time in order to detect the onset of a period of volcanic unrest, in near real time. We demonstrate our approach on synthetic datasets having different signal strengths, varying temporally. We also present the results of our approach on the volcanic unrest of Mt. Thorbjörn in Iceland on 2020 and also the volcanic unrest of a volcano in Mexico from 2017 to 2019.</p>