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We develop finite element models of the coseismic displacement field accounting for the 3D elastic structures surrounding the epicentral area of the 2019 Ridgecrest earthquake sequence containing two major events of Mw7.1 and Mw6.4. The coseismic slip distribution is inferred from the surface displacement field recorded by interferometric synthetic aperture radar. The rupture dip geometry is further optimized using a novel nonlinear‐crossover‐linear inversion approach. It is found that accounting for elastic heterogeneity and fault along‐strike curvilinearity improves the fit to the observed displacement field and yields a more accurate estimate of geodetic moment and Coulomb stress changes. We observe spatial correlations among the locations of aftershocks and patches of high slip, and rock anomalous elastic properties, suggesting that the shallow crust's elastic structures possibly controlled the Ridgecrest earthquake sequence. Most of the coseismic slip with a peak slip of 7.4 m at 3.6 km depth occurred above a zone of reduced S‐wave velocity and significant post‐Mw7.1 afterslip. This implies that viscous materials or fluid presence might have contributed to the low rupture velocity of the mainshock. Moreover, the zone of high slip on the northwest‐trending fault segment is laterally bounded by two aftershock clusters, whose location is characterized by intermediate rock rigidity. Notably, some minor orthogonal faults consistently end above a subsurface rigid body. Overall, these observations of structural controls improve our understandings of the seismogenesis within incipient fault systems. Plain Language Summary: On July 4 and 5, 2019, a magnitude 7.1 and 6.4 earthquake occurred near the town, Ridgecrest, California. The permanent surface movements induced by these events were captured by satellite images. Here, we develop realistic numerical models and innovational optimization algorithms to investigate the displacement fields and image the distribution of the earthquake slip. These events were hosted by a pair of orthogonal faults and their resolved orientations are similar to the nearby known fault structures. We discover that the fault slip and aftershock locations could be related to the local rock materials, suggesting that the variable elastic properties of the shallow crust might have influenced the development of the Ridgecrest earthquake sequence. As also supported by other seismic and geophysical datasets, most of the coseismic slip appeared over a zone of elastic weakness where could be relevant to subsurface viscous or fluid bodies, meanwhile, aftershocks tended to cluster within a shallow rigid body. Overall, the findings of this study provide insights into potential structural controls over the seismic occurrence and help improve our understandings of the seismogenesis within the western Mojave desert. Key Points: Heterogeneous velocity structures in the epicentral area are simulated in elastic modelsPeak slip occurred above a zone of reduced S‐wave velocity and documented afterslipMost aftershocks are located outside slip asperities and within a shallow brittle zone [ABSTRACT FROM AUTHOR]

Chinese coastal topography has changed significantly over the last two decades due to human actions such as the development of extensive land reclamation projects. Newly-reclaimed lands typically have low elevations (<10 m) and often experience severe ground subsidence. These conditions, combined with the more frequent occurrence of extreme sea-level events amplified by global climate change, lead to an increased risk of flooding of coastal regions. This work focuses on twelve Chinese coastal areas that underwent significant changes from 2000 to 2015 in their environments, correlated to relevant land reclamation projects. First, the ground changes between 2000 and 2015 were roughly computed by comparing the TanDEM-X and the Shuttle Radar Topography Mission (SRTM) digital elevation models of the investigated areas. These results indicate that six of the analyzed coastal zones have reclaimed more than 200 km2 of new lands from 2000 to 2015, with five of them in northern China. Second, we focused specifically on the city of Shanghai, and characterized the risk of flood in this area. To this purpose, two independent sets of synthetic aperture radar (SAR) data collected at the X- and C-band through the COSMO-SkyMed (CSK) and the European Copernicus Sentinel-1 (S-1) sensors were exploited. We assumed that the still extreme seawater depth is chi-square distributed, and estimated the probability of waves overtopping the coast. We also evaluated the impact on the territory of potential extreme flood events by counting the number of very-coherent objects (at most anthropic, such as buildings and public infrastructures) that could be seriously affected by a flood. To forecast possible inundation patterns, we used the LISFLOOD-FP hydrodynamic model. Assuming that an extreme event destroyed a given sector of the coastline, we finally computed the extent of the flooded areas and quantified its impact in terms of coherent structures potentially damaged by the inundation. Experimental results showed that two coastline segments located in the southern districts of Shanghai, where the seawalls height is lower, had the highest probability of wave overtopping and the most significant density of coherent objects potentially subjected to severe flood impacts. [ABSTRACT FROM AUTHOR]

This work investigated the large-scale ground deformations threatening the Northern Urumqi district, China, which are connected to groundwater exploitation and the seasonal freeze–thaw cycles that characterize this frozen region. Ground deformations can be well captured by satellite data using a multi-temporal interferometric synthetic aperture radar (Mt-InSAR) approach. The accuracy of the achievable ground deformation products (e.g., mean displacement time series and related ground displacement time series) critically depends on the number and quality of the selected interferograms. This paper presents a straightforward interferogram selection algorithm that can be applied to identify an optimal network of small baseline (SB) interferograms. The selected SB interferograms are then used to produce ground deformation products using the well-known small baseline subset (SBAS) Mt-InSAR algorithm. The developed interferogram selection algorithm (ISA) permits the selection of the group of SB data pairs that minimize the relative error of the mean ground deformation velocity. Experiments were carried out using a group of 102 Sentinel-1B SAR data collected from 12 April 2017 to 29 October 2020. This research study shows that the investigated farmland region is characterized by a maximum ground deformation rate of about 120 mm/year. Periodic groundwater overexploitation, coupled with irrigation and freeze–thaw phases, is also responsible for seasonal (one-year) ground displacement signals, with oscillation amplitudes up to 120 mm in the zones of maximum displacement. [ABSTRACT FROM AUTHOR]

In this work, we study ground deformation of ocean-reclaimed platforms as retrieved from interferometric synthetic aperture radar (InSAR) analyses. We investigate, in particular, the suitability and accuracy of some time-dependent models used to characterize and foresee the present and future evolution of ground deformation of the coastal lands. Previous investigations, carried out by the authors of this paper and other scholars, related to the zone of the ocean-reclaimed lands of Shanghai, have already shown that ocean-reclaimed lands are subject to subside (i.e., the ground is subject to settling down due to soil consolidation and compression), and the temporal evolution of that deformation follows a certain predictable model. Specifically, two time-gapped SAR datasets composed of the images collected by the ENVISAT ASAR (ENV) from 2007 to 2010 and the COSMO-SkyMed (CSK) sensors, available from 2013 to 2016, were used to generate long-term ground displacement time-series using a proper time-dependent geotechnical model. In this work, we use a third SAR data set consisting of Radarsat-2 (RST-2) acquisitions collected from 2012 to 2016 to further corroborate the validity of that model. As a result, we verified with the new RST-2 data, partially covering the gap between the ENV and CSK acquisitions, that the adopted model fits the data and that the model is suitable to perform future projections. Furthermore, we extended these analyses to the area of Pearl River Delta (PRD) and the city of Shenzhen, China. Our study aims to investigate the suitability of different time-dependent ground deformation models relying on the different geophysical conditions in the two areas of Shanghai and Shenzhen, China. To this aim, three sets of SAR data, collected by the ENV platform (from both ascending and descending orbits) and the Sentinel-1A (S1A) sensor (on ascending orbits), were used to obtain the ground displacement time-series of the Shenzhen city and its surrounding region. Multi-orbit InSAR data products were also combined to discriminate the up–down (subsidence) ground deformation time-series of the coherent points, which are then used to estimate the parameters of the models adopted to foresee the future evolution of the land-reclaimed ground consolidation procedure. The exploitation of the obtained geospatial data and products are helpful for the continuous monitoring of coastal environments and the evaluation of the socio-economical impacts of human activities and global climate change. [ABSTRACT FROM AUTHOR]

Detection and continuous monitoring of Earth's ground surface changes, triggered by natural phenomena or induced by human activities, is nowadays possible using Earth Observation (EO) technologies. Indeed, the exploitation of remotely sensed data collected by constellations of new-generation satellite platforms, complemented with in-situ measurements and ground-based observation systems, represents a well-established practice to get valuable information on Earth's crust and subsurface dynamics. The effects of extreme natural or man-induced events (e.g., earthquakes, volcanic eruptions, flooding phenomena, sea-level rise, big fires, etc.) have severe societal and economic impacts. In particular, the technologies based on the use of Synthetic Aperture Radar (SAR) images reached significant improvements in the last decade due to the growing availability of vast amounts of data collected by multiple-satellite sensors operating at different frequency bands and with complementary viewing angles, polarization and acquisition modes. Accordingly, to process a large amount of SAR data in a timely fashion, up-to-date high-performance computing (HPC) methods and tools are required. This paper addresses the state-of-the-art of SAR technologies for the analysis of long sequences of multiple sets of SAR images and provides a perspective on the forthcoming improvements of these technologies. In particular, the emphasis is placed on novel interferometric SAR and change detection methods, giving an overview of how those processing techniques have been used for investigating sites located in South and Central America. Moreover, an overview of the new generation of SAR sensors' observational capability, especially in the field of ground deformation analysis for mitigating the risk associated with natural and human-induced hazards, is provided. COSMO-SkyMed, ALOS, Sentinel-1, and SAOCOM data are exploited to show how natural and human-induced terrain displacement phenomena can be detected and investigated in different portions (X-, L- and C-band) of the microwave spectrum using SAR technologies. [ABSTRACT FROM AUTHOR]

Ground deformation is one of the most significant challenges faced by many coastal mega-cities, with major societal and economic impacts. In this context, the possibility to monitor the temporal evolution of the ground subsidence processes, which may also last for several years, is of great relevance. This goal can be obtained by applying differential SAR interferometry (DInSAR) techniques to sequences of multiple-satellite synthetic aperture radar (SAR) images. Moreover, the growing availability of large archives of SAR images collected by different SAR instruments nowadays leads to the need of developing new data merging techniques, which may take profit from the complementary information recoverable from every single set of data. In this work, a novel data merging approach for the generation of long-tem ground displacement time-series, based on the use of the modified Quantile-Quantile Adjustment (MQQA) algorithm, is proposed. Specifically, the methodology has successfully been applied to study the long-term evolution of the ground subsidence occurred in the coastal area of Shanghai from February 2007 to April 2017. A cross-comparison analysis between DInSAR and ground truth data has also been carried out, showing that the average root mean square error (RMSE) between the obtained displacement time-series and available ground truth data is of about 3 mm. This outcome confirms the validity of the novel DInSAR-based MQQA combination method. [ABSTRACT FROM AUTHOR]

Highlights • Long-term flood risk was assessed using InSAR techniques and a hydrodynamic model. • SLR and land subsidence result in minor but non-linear impacts on coastal flooding. • Evolving flood risk largely depends on exposure and vulnerability of coastal area. Abstract In this paper, we study long-term coastal flood risk of Lingang New City, Shanghai, considering 100- and 1000-year coastal flood return periods, local seal-level rise projections, and long-term ground subsidence projections. TanDEM-X satellite data acquired in 2012 were used to generate a high-resolution topography map, and multi-sensor InSAR displacement time-series were used to obtain ground deformation rates between 2007 and 2017. Both data sets were then used to project ground deformation rates for the 2030s and 2050s. A 2-D flood inundation model (FloodMap-Inertial) was employed to predict coastal flood inundation for both scenarios. The results suggest that the sea-level rise, along with land subsidence, could result in minor but non-linear impacts on coastal inundation over time. The flood risk will primarily be determined by future exposure and vulnerability of population and property in the floodplain. Although the flood risk estimates show some uncertainties, particularly for long-term predictions, the methodology presented here could be applied to other coastal areas where sea level rise and land subsidence are evolving in the context of climate change and urbanization. [ABSTRACT FROM AUTHOR]

• Synergic use of InSAR coherence and SAR backscattering for crop growth monitoring. • A high correlation between growth stages and the radar coherence and backscatter. • Compared to VH polarization VV indicated more sensitivity to phonological stages. • InSAR coherence allows to estimate the main growth stages of the different crops. • SAR backscatter provides information on the entire growth phase. In this study, we investigate the synergic use of synthetic aperture radar (SAR) backscattering (i.e., sigma nought σ0) and InSAR coherence (γ) maps as a tool for crop growth monitoring. Experiments were carried out using Sentinel-1 TOPS SAR data and field observations in one of the State General Directorate of Agriculture Enterprise farms in Konya (Central Turkey). The phenological stages of maize, sunflower, and wheat have been analyzed and compared to coherence and backscatter time series of Sentinel-1 data on multiple tracks and polarizations. The results evidence a strong correlation between different phenological stages of the crops and the InSAR coherence. Specifically, the observed coherence values are the highest for the maize (γ asc , desc = 0.47) and sunflower (γ asc = 0.49, γ desc = 0.48) after plowing the fields and seeding the crops. The coherence decreases with the plants' growth and reaches the lowest values for maize, sunflower, and wheat (γ = 0.08, γ = 0.09 and γ = 0.07, respectively) when the ground is completely covered by plants. Then, a coherence increase is observed after the harvesting time (γ = 0.51, γ = 0.50 and γ = 0.42 for maize, sunflower, and wheat, respectively). In terms of multi-temporal SAR backscattering, we find significant changes of the σ0 values during the crops' growing stages due to the changes in their leaf geometry and physical structure. The highest σ0 values for the maize, sunflower, and wheat are obtained as −9.18 dB, −5.24 dB and −10.05 dB, respectively, for the ascending orbit, in mid growing stages. Results show the improved capacity of SAR-driven measurements for agriculture monitoring and precise farming activities when InSAR coherence and backscattering are synergistically used. Specifically, the coherence allows estimating the main growth stages of the different crop types. Moreover, SAR backscattering provides reliable information on the whole growth stages during the agricultural season, and it might be profitably exploited for crop assessment. [ABSTRACT FROM AUTHOR]