Terrain Observation With Progressive Scans Research Articles

An Efficient Global Scale Sentinel-1 Radar Backscatter and Interferometric Processing System

We describe an efficient and cost-effective data access mechanism for Sentinel-1 Terrain Observation with Progressive Scans (TOPS) mode bursts. Our data access mechanism enables burst-based data access and processing, thereby eliminating the European Space Agency’s (ESA’s) Sentinel-1 Single Look Complex (SLC) data packaging conventions as a bottleneck to large scale processing. The pipeline throughput is now determined by the available computation resources and the efficiency of the analysis algorithms. For targeted infrastructure monitoring studies, we are able to generate coregistered, geocoded stacks of SLCs for any area of interest (AOI) in the world, in a few minutes. In addition, we describe our global scale radar backscatter and interferometric products, and associated pipeline design decisions that ensure geolocation consistency across the suite of derived products from Sentinel-1 data. Finally, we discuss the benefits and limitations of working with geocoded SLC data.

Monitoring Potential Geological Hazards with Different InSAR Algorithms: The Case of Western Sichuan

In recent years, the number of geological disasters in Sichuan Province has significantly increased due to the influence of earthquakes and extreme climate, as well as the disturbance to the geological environment by human activities. Thus, geological disaster monitoring is particularly important, which can provide some scientific basis for disaster prevention and reduction. In this paper, the interferometric synthetic aperture radar (InSAR) technology was introduced to monitor potential geological hazards, taking parts of Dujiangyan City, Wenchuan County, and Mao County in Sichuan Province, China as examples. Firstly, the data such as Sentinel-1A Terrain Observation with Progressive Scans (TOPS) Synthetic Aperture Radar (SAR) images and Precision Orbit Determination (POD) precise orbit ephemerides from 2018 to 2020, high-resolution optical satellite images and Digital Elevation Model (DEM) were collected. Secondly, the Differential InSAR (D-InSAR), Persistent Scatterer InSAR (PS-InSAR), Small Baseline Subset InSAR (SBAS-InSAR), Offset-Tracking, and Distributed Scatterer InSAR (DS-InSAR) algorithms were used to invert the surface deformation of the study area. Thirdly, according to the deformation results obtained by experiments, we used GF-1 and GF-2 optical images as a reference and combine the experimental results of InSAR algorithms to delineate the areas affected by geological disasters. A total of 49 geological disaster areas were obtained, mainly including landslides, collapses, and debris flow. Through field verification, the overall accuracy rate of InSAR deformation monitoring achieved 69.23%, and the accuracy rate of new potential hazards monitoring reached 63.64%. Among all InSAR methods, the DS-InSAR method outperformed and monitored the geological disaster areas well. Finally, the study area was divided into three elevation intervals and the applicability of different InSAR algorithms in different elevation intervals was discussed.

PS-ESD: Persistent Scatterer-Based Enhanced Spectral Diversity Approach for Time-Series Sentinel-1 TOPS Data Co-Registration

In Sentinel-1 terrain observation with progressive scan (TOPS) mode, this azimuth sweeping introduces an extra high-frequency Doppler term into the impulse response function, which requires the azimuth co-registration accuracy of 0.001 pixels to make the interferometric phase difference of adjacent bursts less than 3°. The enhanced spectral diversity (ESD) and developing versions are usually used to correct such residual azimuth misregistration. However, in fast decorrelation scenario, the distributed scatterers (DSs)-based ESDs need to perform lots of complex data processing to reduce the decorrelation impact on high-precision co-registration, including multilooking, spatial filtering, network construction, and least square adjustment. The DS-based co-registration methods are complicated and inefficient, which is not suitable for big SAR data processing. Therefore, this paper proposes a persistent scatterers-based ESD (PS-ESD): to estimate the amplitude dispersion index (ADI) with double samples over the burst overlap regions and select the satisfied PS pixels to compute the double differential phase under the one-master interferometric framework for correcting the time-series azimuth shifts. Based on the Sentinel-1 TOPS SAR data over the mountainous area in Three Gorges, China, experimental results have demonstrated that the proposed PS-ESD can achieve higher co-registration accuracy and faster convergence rate, especially in the case of dynamic co-registration of newly added TOPS images.

A Signal Model for PRF Dithering in Wide-Swath, Fine-Resolution InSAR

Wide-swath radar imaging requires that the time interval to collect each radar pulse echo is large and can often exceed the interpulse period. As it is difficult to both transmit and receive from the same antenna simultaneously, there will be “blind ranges” when the receive and transmit times overlap. This leads to gaps in the radar echo and thus degradation of system performance. Today, most wide-swath systems address this by segmenting the swath in range, such as in the ScanSAR or Terrain Observation with Progressive Scan (TOPS) mode operation, so that each subswath is within the range ambiguity limit. Some groups have started experimenting with the variations in the sweepSAR technology, in which the receive antenna tracks the radar echo across the swath, realizing a complete wide-swath range scan but leading to the echo gaps. Here, we look at minimizing the effect of blind ranges by varying the radar pulse-repetition frequency (PRF) and interpolating across the gaps to preserve azimuth signal continuity. If the pulse times are selected properly, the main effect is to raise the noise floor of the echoes. Geocoded magnitude images, interferograms and correlation images, and deformation time series show strong robustness with respect to dithering, demonstrating that choosing essentially random PRFs allows for accurate generation of SAR and Interferometric Synthetic Aperture Radar (InSAR) data products while retaining wide-swath, fine-resolution coverage.

The Multiple Aperture SAR Interferometry (MAI) Technique for the Detection of Large Ground Displacement Dynamics: An Overview

This work presents an overview of the multiple aperture synthetic aperture radar interferometric (MAI) technique, which is primarily used to measure the along-track components of the Earth’s surface deformation, by investigating its capabilities and potential applications. Such a method is widely used to monitor the time evolution of ground surface changes in areas with large deformations (e.g., due to glaciers movements or seismic episodes), permitting one to discriminate the three-dimensional (up–down, east–west, north–south) components of the Earth’s surface displacements. The MAI technique relies on the spectral diversity (SD) method, which consists of splitting the azimuth (range) Synthetic Aperture RADAR (SAR) signal spectrum into separate sub-bands to get an estimate of the surface displacement along the azimuth (sensor line-of-sight (LOS)) direction. Moreover, the SD techniques are also used to correct the atmospheric phase screen (APS) artefacts (e.g., the ionospheric and water vapor phase distortion effects) that corrupt surface displacement time-series obtained by currently available multi-temporal InSAR (MT-InSAR) tools. More recently, the SD methods have also been exploited for the fine co-registration of SAR data acquired with the Terrain Observation with Progressive Scans (TOPS) mode. This work is primarily devoted to illustrating the underlying rationale and effectiveness of the MAI and SD techniques as well as their applications. In addition, we present an innovative method to combine complementary information of the ground deformation collected from multi-orbit/multi-track satellite observations. In particular, the presented technique complements the recently developed Minimum Acceleration combination (MinA) method with MAI-driven azimuthal ground deformation measurements to obtain the time-series of the 3-D components of the deformation in areas affected by large deformation episodes. Experimental results encompass several case studies. The validity and relevance of the presented approaches are clearly demonstrated in the context of geospatial analyses.

Application of Time Series InSAR (SBAS) Method using Sentinel-1A Data for Land Subsidence Detection in Surabaya City

We studied land subsidence occurrence in Surabaya, considering the rapid urban growth in the city. It is evidenced by the increasing number of buildings (e.g., houses, apartments, offices) that have been realized before 2015 and the increasing transport activities in the industrial area. Land subsidence is a vertical deformation on the land surface that can be caused by landslides, earthquakes, soil consolidation process, or even human-made activities, depending on the material characteristics of the area. In this study, Time-series InSAR (TS-InSAR), specifically the Small Baseline Subset (SBAS) method, is applied to obtain the Line-of-Sight (LOS) velocities and time-series LOS displacements in Surabaya between May 2015 and September 2017. We used 28 Sentinel-1A data (IW mode) acquired by using Terrain Observation with Progressive Scan (TOPS) operation with the spatial resolution of 5 ´ 20 m and covers the area of 250 km2. DEM SRTM with 30 m spatial resolution was used to reduce topography effect contribution in the interferograms. Based on the SBAS method, interferogram pair selection is applied with the maximum value of 150 m for the perpendicular baseline and 100 days for the temporal baseline. The DInSAR process successfully generated seventy-four (74) interferogram pairs, and then by using SBAS algorithm, the LOS velocity and time-series LOS displacement were estimated. The results showed the varying displacements respond with the significant subsidence occurred in the North, East, and Southeast part of Surabaya. The SBAS result confirmed that the LOS velocity over the Surabaya area between May 2015 and September 2017 ranges from -40 to +30 mm/year. Significant land subsidence occurred in the Asemrowo area (North Surabaya) with the value of LOS displacement velocity up to -45 mm/yr.

DETECTING DEFORMATION DUE TO THE 2018 MERAPI VOLCANO ERUPTION USING INTERFEROMETRIC SYNTHETIC APERTURE RADAR (INSAR) FROM SENTINEL-1 TOPS

This paper describes the application of Sentinel-1 TOPS (Terrain Observation with Progressive Scans), the latest generation of SAR satellite imagery, to detect displacement of the Merapi volcano due to the May–June 2018 eruption. Deformation was detected by measuring the vertical displacement of the surface topography around the eruption centre. The Interferometric Synthetic Aperture Radar (InSAR) technique was used to measure the vertical displacement. Furthermore, several Landsat-8 Thermal Infra Red Sensor (TIRS) imageries were used to confirm that the displacement was generated by the volcanic eruption. The increasing temperature of the crater was the main parameter derived using the Landsat-8 TIRS, in order to determine the increase in volcanic activity. To understand this phenomenon, we used Landsat-8 TIRS acquisition dates before, during and after the eruption. The results show that the eruption in the May–June 2018 period led to a small negative vertical displacement. This vertical displacement occurred in the peak of volcano range from -0.260 to -0.063 m. The crater, centre of eruption and upper slope of the volcano experienced negative vertical displacement. The results of the analysis from Landsat-8 TIRS in the form of an increase in temperature during the 2018 eruption confirmed that the displacement detected by Sentinel-1 TOPS SAR was due to the impact of volcanic activity. Based on the results of this analysis, it can be seen that the integration of SAR and thermal optical data can be very useful in understanding whether deformation is certain to have been caused by volcanic activity.

The Parallel SBAS Approach for Sentinel-1 Interferometric Wide Swath Deformation Time-Series Generation: Algorithm Description and Products Quality Assessment

We present an advanced differential synthetic aperture radar (SAR) interferometry (DInSAR) processing chain, based on the Parallel Small BAseline Subset (P-SBAS) technique, for the efficient generation of deformation time series from Sentinel-1 (S-1) interferometric wide (IW) swath SAR data sets. We first discuss an effective solution for the generation of high-quality interferograms, which properly accounts for the peculiarities of the terrain observation with progressive scans (TOPS) acquisition mode used to collect S-1 IW SAR data. These data characteristics are also properly accounted within the developed processing chain, taking full advantage from the burst partitioning. Indeed, such data structure represents a key element in the proposed P-SBAS implementation of the S-1 IW processing chain, whose migration into a cloud computing (CC) environment is also envisaged. An extensive experimental analysis, which allows us to assess the quality of the obtained interferometric products, is presented. To do this, we apply the developed S-1 IW P-SBAS processing chain to the overall archive acquired from descending orbits during the March 2015-April 2017 time span over the whole Italian territory, consisting in 2740 S-1 slices. In particular, the quality of the final results is assessed through a large-scale comparison with the GPS measurements relevant to nearly 500 stations. The mean standard deviation value of the differences between the DInSAR and the GPS time series (projected in the radar line of sight) is less than 0.5 cm, thus confirming the effectiveness of the implemented solution. Finally, a discussion about the performance achieved by migrating the developed processing chain within the Amazon Web Services CC environment is addressed, highlighting that a two-year data set relevant to a standard S-1 IW slice can be reliably processed in about 30 h.The presented results demonstrate the capability of the implemented P-SBAS approach to efficiently and effectively process large S-1 IW data sets relevant to extended portions of the earth surface, paving the way to the systematic generation of advanced DInSAR products to monitor ground displacements at a very wide spatial scale.

Monitoring the regional deformation of loess landslides on the Heifangtai terrace using the Sentinel-1 time series interferometry technique

The Heifangtai terrace of Gansu Province is a hotspot for loess landslide research, as massive and continuous landslides occur here every year. Detecting the spatial and temporal deformations of landslides and acquiring precursor information are very important for hazard prediction and risk management. In this paper, 51 newly launched Sentinel-1a scenes using the novel terrain observation with progressive scans (TOPS) mode from March 2015 to November 2017 are gathered, and a preprocessed chain of TOPS with the small baseline subset interferometric synthetic aperture radar technology is generated to obtain the deformation time-series. Our results show that (1) 44 active landslides with mean deformation velocities ranging from − 12.3 to − 58.57 mm yr−1 along the steepest slope, were detected and consisted of 18 loess-bedrock landslides, 12 loess flows, 7 loess flow-slides, and 7 loess slides; (2) four typical active regions and two potential risk places were recognized on the basis of high coherent point distribution, the average measured velocities along the steep slope and high-resolution orthographic images; (3) geological structures and special geomorphologies (e.g., cracks, sinkholes and concave gullies) can be mainly attributed to induce reactivity via long term irrigation. Finally, our research also demonstrates the potential ability of Sentinel-1 TOPS images to be applied to the monitoring of loess landslides, which is essential for risk mitigation and emergence management.

A Phase-Preserving Focusing Technique for TOPS Mode SAR Raw Data Based on Conventional Processing Methods

We present a new solution for the phase-preserving focusing of synthetic aperture radar (SAR) raw data acquired through the Terrain Observation with Progressive Scan (TOPS) mode. The proposed algorithm consists of a first interpolation stage of the TOPS raw data, which takes into account the Doppler Centroid frequency variations due to the azimuth antenna steering function, and allows us to unfold the azimuth spectra of the TOPS raw data. Subsequently, the interpolated signals are processed by using conventional phase-preserving SAR focusing methods that exploit frequency domain and spectral analyses algorithms, which are extensively used to efficiently process Stripmap and ScanSAR data. Accordingly, the developed focusing approach is easy to implement. In particular, the presented focusing approach exploits one of the available frequency domain Stripmap processing techniques. The only modification is represented by the inclusion, within the 2D frequency domain focusing step, of a spurious azimuth chirp signal with a properly selected azimuthal rate. This allows us to efficiently carry out the TOPS azimuth focusing through the SPECAN method. Furthermore, an important aspect of this algorithm is the possibility to easily achieve a constant and tunable output azimuth pixel size without any additional computing time; this is a remarkable feature with respect to the full-aperture TOPS-mode algorithms available in the existing literature. Moreover, although tailored on Sentinel-1 (S1) raw data, the proposed algorithm can be easily extended to process data collected through the TOPS mode by different radar sensors. The presented experimental results have been obtained by processing real Sentinel-1 raw data and confirm the effectiveness of the proposed algorithm.

DETECTING THE LAVA FLOW DEPOSITS FROM 2018 ANAK KRAKATAU ERUPTION USING DATA FUSION LANDSAT-8 OPTIC AND SENTINEL-1 SAR

The increasing volcanic activity of Anak Krakatau volcano has raised concerns about a major disaster in the area around the Sunda Strait. The objective of the research is to fuse Landsat-8 OLI (Operational Land Imager) and Sentinel-1 TOPS (Terrain Observation with Progressive Scans), an integration of SAR and optic remote sensing data, in observing the lava flow deposits resulted from Anak Krakatau eruption during the middle 2018 eruption. RGBI and the Brovey transformation were conducted to merge (fuse) the optical and SAR data. The results showed that optical and SAR data fusion sharpened the appearance of volcano morphology and lava flow deposits. The regions are often constrained by cloud cover and volcanic ash, which occurs at the time of the volcanic eruption. The RGBI-VV and Brovey RGB-VV methods provide better display quality results in revealing the morphology of volcanic cone and lava deposits. The entire slopes of Anak Krakatau Volcano, with a radius of about 1 km from the crater is an area prone to incandescent lava and pyroclastic falls. The direction of the lava flow has the potential to spread in all directions. The fusion method of optical Landsat-8 and Sentinel-1 SAR data can be used continuously in monitoring the activity of Anak Krakatau volcano and other volcanoes in Indonesia both in cloudy and clear weather conditions.

Coseismic Deformation Field of the Mw 7.3 12 November 2017 Sarpol-e Zahab (Iran) Earthquake: A Decoupling Horizon in the Northern Zagros Mountains Inferred from InSAR Observations

The study of crustal deformation fields caused by earthquakes is important for a better understanding of seismic hazard and growth of geological structures in tectonically active areas. In this study, we present, using interferometric measurements constructed from Sentinel-1 Terrain Observation with Progressive Scan (TOPS) data and ALOS-2 ScanSAR, coseismic deformation and source model of the Mw 7.3, 12 November 2017 earthquake that hit northwest of the Zagros Mountains in the region between Iran–Iraq border. This was one of the strongest seismic events to hit this region in the past century, and it resulted in an uplift area of about 3500 km2 between the High Zagros Fault (HZF) and Mountain Front Fault (MFF) with a maximum amount of 70 cm south of Miringe fault. A subsidence over an area of 1200 km2 with a maximum amount of 35 cm occurred near Vanisar village at the hanging wall of the HZF. Bayesian inversion of interferometric synthetic aperture radar (InSAR) observations suggests a source model at a depth between 14 and 20 km that is consistent with the existence of a decoupling horizon southwest edge of the northern portion of the Zagros Mountains near the MFF. Moreover, we present evidence for a number of coseismically induced rockslides and landslides, the majority of them which occurred along or close to pre-existing faults, causing decorrelation in differential interferograms. Exploiting the offset-tracking technique, we estimated surface motion by up to 34 and 10 m in horizontal and vertical directions, respectively, due to lateral spreading on a big coseismic-induced landslide near Mela-Kabod. Field observations also revealed several zones of en echelon fractures and crack zones developed along a pre-existing fault passing through Qasr-e Shirin City, which exhibited secondary surface slip by up to 14 cm along its strike.

A Common “Stripmap-Like” Interferometric Processing Chain for TOPS and ScanSAR Wide Swath Mode

This article describes the technical implementation of a “stripmap-like” interferometric processing flow that could be used for both Terrain Observation with Progressive Scans (TOPS) and ScanSAR. In this “stripmap-like” approach, the discontinuous bursts of wide swath mode for the same subswath are stitched into a continuous single look complex (SLC) image at the very beginning of the processing chain. For users who wish not to get into the complexity behind the wide swath mode and simply want to use the interferometric products, this implementation provides the identical processing steps and output products to the stripmap case. This implementation also features a user-friendly processing interface, where all the wide-swath-related processes are hidden under the hood. In addition, this approach makes the best use of an existing standard InSAR processing software. In this article, the complete common processing chain for TOPS and ScanSAR is elaborated and some key issues are discussed, starting from stitching, deramping to coregistration and enhanced spectral diversity (ESD). The authors also introduce a quick implementation of fine coregistration during the ESD step that does not require resampling the slave image using the conventional method.

The Parallel SBAS-DInSAR Processing Chain for the Generation of National Scale Sentinel-1 Deformation Time-Series

In this work we present a fully parallel and automatic interferometric processing chain, based on the well-known advanced DInSAR algorithm referred to as Parallel Small BAseline Subset (P-SBAS), for the effective and massive generation of Sentinel-1 (S-1) Interferometric Wide Swath (IWS) displacement time-series and corresponding mean deformation velocity maps of very wide areas. The strategy chosen to implement such a parallel processing chain fully benefits from the Terrain Observation with Progressive Scans (TOPS) mode characterizing the IWS acquisitions of the S-1 constellation for systematic monitoring of large land and coastal areas. The TOPS mode consists of a series of bursts that can be considered as separate images to be independently processed. Such a data structure fosters the parallelization of the S-1 IWS interferometric data processing, which can be automatically carried out through the exploitation of both high-performance distributed computing infrastructures and efficient algorithms for tackling the huge data flow provided by the S-1 constellation.To demonstrate the capability of the presented S-1 P-SBAS processing chain to deal with the huge volume of data acquired by the S-1 constellation, we process a very extended dataset acquired over the Italian territory from which we compute the mean velocity maps and associated deformation time-series.

Wuhan Surface Subsidence Analysis in 2015–2016 Based on Sentinel-1A Data by SBAS-InSAR

The Terrain Observation with Progressive Scans (TOPS) acquisition mode of Sentinel-1A provides a wide coverage per acquisition and features a repeat cycle of 12 days, making this acquisition mode attractive for surface subsidence monitoring. A few studies have analyzed wide-coverage surface subsidence of Wuhan based on Sentinel-1A data. In this study, we investigated wide-area surface subsidence characteristics in Wuhan using 15 Sentinel-1A TOPS Synthetic Aperture Radar (SAR) images acquired from 11 April 2015 to 29 April 2016 with the Small Baseline Subset Interferometric SAR (SBAS InSAR) technique. The Sentinel-1A SBAS InSAR results were validated by 110 leveling points at an accuracy of 6 mm/year. Based on the verified SBAS InSAR results, prominent uneven subsidence patterns were identified in Wuhan. Specifically, annual average subsidence rates ranged from −82 mm/year to 18 mm/year in Wuhan, and maximum subsidence rate was detected in Houhu areas. Surface subsidence time series presented nonlinear subsidence with pronounced seasonal variations. Comparative analysis of surface subsidence and influencing factors (i.e., urban construction, precipitation, industrial development, carbonate karstification and water level changes in Yangtze River) indicated a relatively high spatial correlation between locations of subsidence bowl and those of engineering construction and industrial areas. Seasonal variations in subsidence were correlated with water level changes and precipitation. Surface subsidence in Wuhan was mainly attributed to anthropogenic activities, compressibility of soil layer, carbonate karstification, and groundwater overexploitation. Finally, the spatial-temporal characteristics of wide-area surface subsidence and the relationship between surface subsidence and influencing factors in Wuhan were determined.

A Slip Gap of the 2016Mw 6.6 Muji, Xinjiang, China, Earthquake Inferred from Sentinel‐1 TOPS Interferometry

ABSTRACT We use Sentinel‐1A/1B Terrain Observation with Progressive Scans (TOPS) data to map coseismic and postseismic displacements for the 25 November 2016 M w 6.6 Muji earthquake in southwestern Xinjiang, China. Two tracks (T27 and T107) of the TOPS data captured the coseismic deformation area with a maximum line‐of‐sight deformation of ∼0.25 m in the descending track (T107). The inverted best‐fitting coseismic slip model in this study shows that the mainshock was a right‐lateral strike‐slip rupture on the western segment of the Muji fault, with an optimal dip angle of 80°±4°. Two separated slip zones exist in the coseismic slip model, with the maximum slip of 1.6 m located in the western slip zone. The total geodetic moment is 9.87×10 18 N·m, equivalent to an earthquake of M w 6.6. Our model shows that a patch between the two slip zones remained unruptured during the mainshock, indicating a potential future seismic risk. Aftershocks recorded in the first 45 days after the mainshock delineate the modeled rupture patches well. The components of the regional Global Positioning System velocities parallel to the Muji fault have been inverted to obtain an interseismic slip rate of ∼10 mm/yr on this structure. The recent large strike‐slip earthquakes in this area, that is, the 2015 M w 7.2 Tajikistan earthquake (left‐lateral) and 2016 M w 6.6 Muji earthquake (right‐lateral), may be an indicator of conjugate fault systems at the west boundary between the Indian and Eurasian plates in response to north–south convergence produced by the collision of the two plates.

First Comparison of Sentinel-1 and TerraSAR-X Data in the Framework of Maritime Targets Detection: South Italy Case

The Sentinel-1A is the first of two satellites that composes the Sentinel-1 radar mission. Both satellites operate a C-band synthetic aperture radar (SAR) system to give continuity to the European SAR program. SAR is a flexible sensor able to fulfil users/applications requirements in terms of resolution and coverage thanks to different operational modes and polarizations. With the in-orbit availability of very-high-resolution X-band SAR sensors, the Sentinel-1 satellites have been designed to achieve wide coverage at medium to high resolution. The interferometric wide swath (IWS) mode implemented with the terrain observation with progressive scan (TOPS) technique is the standard acquisition mode over European waters and land masses. IWS in dual-polarization (VV/VH) combination offers 250-km swath at $\hbox{5 m} \times \hbox{20 m}$ (range $\times$ azimuth) spatial resolution. These specifications are in line with the needs of the European Maritime and Security Agency (EMSA) for oil spill and ship detection applications included in the CleanSeaNet program. The main goals of this paper are: assessment of medium-to-high-resolution C-band Sentinel-1 data with very-high-resolution X-band TerraSAR-X data for maritime targets detection; synergetic use of multiplatforms satellite SAR data for target features extraction; evaluation of polarimetric target detectors for the available co-polarization and cross-polarization Sentinel-1A IWS VV/VH products. The objectives are achieved by means of real, almost coincident C-band and X-band SAR data acquired by Sentinel-1A and TerraSAR-X satellites over Gulf of Naples and Catania (South Italy). Furthermore, the obtained results are supported by recorded ground truth vessel reports via terrestrial automatic identification system (AIS) stations located in the area.

Space Geodetic Observations and Modeling of 2016 Mw 5.9 Menyuan Earthquake: Implications on Seismogenic Tectonic Motion

Determining the relationship between crustal movement and faulting in thrust belts is essential for understanding the growth of geological structures and addressing the proposed models of a potential earthquake hazard. A Mw 5.9 earthquake occurred on 21 January 2016 in Menyuan, NE Qinghai Tibetan plateau. We combined satellite interferometry from Sentinel-1A Terrain Observation with Progressive Scans (TOPS) images, historical earthquake records, aftershock relocations and geological data to determine fault seismogenic structural geometry and its relationship with the Lenglongling faults. The results indicate that the reverse slip of the 2016 earthquake is distributed on a southwest dipping shovel-shaped fault segment. The main shock rupture was initiated at the deeper part of the fault plane. The focal mechanism of the 2016 earthquake is quite different from that of a previous Ms 6.5 earthquake which occurred in 1986. Both earthquakes occurred at the two ends of a secondary fault. Joint analysis of the 1986 and 2016 earthquakes and aftershocks distribution of the 2016 event reveals an intense connection with the tectonic deformation of the Lenglongling faults. Both earthquakes resulted from the left-lateral strike-slip of the Lenglongling fault zone and showed distinct focal mechanism characteristics. Under the shearing influence, the normal component is formed at the releasing bend of the western end of the secondary fault for the left-order alignment of the fault zone, while the thrust component is formed at the restraining bend of the east end for the right-order alignment of the fault zone. Seismic activity of this region suggests that the left-lateral strike-slip of the Lenglongling fault zone plays a significant role in adjustment of the tectonic deformation in the NE Tibetan plateau.

Deformation and Source Parameters of the 2015 Mw 6.5 Earthquake in Pishan, Western China, from Sentinel-1A and ALOS-2 Data

In this study, Interferometric Synthetic Aperture Radar (InSAR) was used to determine the seismogenic fault and slip distribution of the 3 July 2015 Pishan earthquake in the Tarim Basin, western China. We obtained a coseismic deformation map from the ascending and descending Sentinel-1A satellite Terrain Observation with Progressive Scans (TOPS) mode and the ascending Advanced Land Observation Satellite-2 (ALOS-2) satellite Fine mode InSAR data. The maximum ground uplift and subsidence were approximately 13.6 cm and 3.2 cm, respectively. Our InSAR observations associated with focal mechanics indicate that the source fault dips to southwest (SW). Further nonlinear inversions show that the dip angle of the seimogenic fault is approximate 24°, with a strike of 114°, which is similar with the strike of the southeastern Pishan fault. However, this fault segment responsible for the Pishan event has not been mapped before. Our finite fault model reveals that the peak slip of 0.89 m occurred at a depth of 11.6 km, with substantial slip at a depth of 9–14 km and a near-uniform slip of 0.2 m at a depth of 0–7 km. The estimated moment magnitude was approximately Mw 6.5, consistent with seismological results.

TOPSAR: Terrain Observation by Progressive Scans

In this paper, a novel (according to the authors' knowledge) type of scanning synthetic aperture radar (ScanSAR) that solves the problems of scalloping and azimuth-varying ambiguities is introduced. The technique employs a very simple counterrotation of the radar beam in the opposite direction to a SPOT: hence, the name terrain observation with progressive scan (TOPS). After a short summary of the characteristics of the ScanSAR technique and its problems, TOPSAR, which is the technique of design, the limits, and a focusing technique are introduced. A synthetic example based on a possible future system follows