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Located on the southeastern periphery of the Tibetan Plateau, the Xianshuihe fault (XSHF) is an active left-lateral strike-slip fault renowned for its frequent and intensive seismic activities. This highlights the necessity of employing advanced geodetic methodologies to precisely evaluate the fault kinematics and seismic hazard potential along this fault. Among these techniques, interferometric synthetic aperture radar (InSAR) stands out for its high spatial resolution and regular revisit intervals, enabling accurate mapping of interseismic deformation associated with fault motion. However, the precision of InSAR in measuring deformation encounters several challenges, particularly artifacts stemming from phase unwrapping errors and atmospheric phase delays. In this study, we utilize ascending and descending Sentinel-1 InSAR images spanning from January 2017 to January 2023 to drive the line-of-sight (LOS) mean crustal velocities associated with the XSHF with emphasis on phase unwrapping errors and atmospheric delay corrections. Then, the reliability of the derived LOS velocities is assessed using independent observations from the Global Navigation Satellite System (GNSS). The inferred fault slip rate along the XSHF shows significant along-strike variations, gradually decreasing from ~11.1 mm/yr at the Luhuo section to ~6.6 mm/yr at the Kangding section and then sharply increasing to ~13.0 mm/yr towards its eastern terminus at the Moxi section. The fault locking depth shows similar along-strike variations, decreasing from ~19.5 km in the northwestern part to ~4.8 km at the Kangding section, before increasing to 19.6 km at the Moxi segment. Notably, apparent surface fault creeping, characterized by a slip rate of ~2.7 mm/yr, is observed at the Kangding segment, likely resulting from postseismic slip following the 2014 Mw 6.3 Kangding earthquake. [ABSTRACT FROM AUTHOR]

The Pamir, situated in central Asia, is a result of the ongoing northward advance of the Indian continent, leading to compression of the Asian landmass. While geodetic and seismic data typically indicate that the most significant deformation in Pamir is along its northern boundary, an Mw 7.2 earthquake on 7 December 2015 and an Mw 6.8 earthquake on 23 February 2023 have occurred in the remote interior of Pamir. These two Mw ≥ 6.5 earthquakes, with good observations of satellite synthetic aperture radar data, provide a rare opportunity to gain insights into rupture mechanics and deformation patterns in this challenging-to-reach region. Here, we utilize spaceborne synthetic aperture radar data to determine the seismogenic faults and finite slip models for these two earthquakes. Our results reveal that the 2015 earthquake ruptured a ~88 km long, left-lateral strike-slip fault that dips to northwest. The rupture of the 2015 earthquake extended to the ground surface over a length of ~50 km with a maximum slip of ~3.5 m. In contrast, the 2023 earthquake did not rupture the ground surface, with a maximum slip of ~2.2 m estimated at a depth of ~9 km. Notably, the seismogenic fault of the 2015 earthquake does not align with the primary strand of the Sarez–Karakul fault system (SKFS), and the 2023 earthquake occurred on a previously unmapped fault. The well-determined seismogenic faults for the 2015 and 2023 earthquakes, along with the SKFS and other distributed faults in the region, suggest the existence of a wide shear zone extending from south to north within the central Pamir. [ABSTRACT FROM AUTHOR]

Interferometric Synthetic Aperture Radar (InSAR) enables detailed investigation of surface landslide movements, but it cannot provide information about subsurface structures. In this work, InSAR measurements were integrated with seismic noise in situ measurements to analyse both the surface and subsurface characteristics of a complex slow-moving landslide exhibiting multiple failure surfaces. The landslide body involves a town of around 6000 inhabitants, Villa de la Independencia (Bolivia), where extensive damages to buildings have been observed. To investigate the spatial-temporal characteristics of the landslide motion, Sentinel-1 displacement time series from October 2014 to December 2019 were produced. A new geometric inversion method is proposed to determine the best-fit sliding direction and inclination of the landslide. Our results indicate that the landslide is featured by a compound movement where three different blocks slide. This is further evidenced by seismic noise measurements which identified that the different dynamic characteristics of the three sub-blocks were possibly due to the different properties of shallow and deep slip surfaces. Determination of the slip surface depths allows for estimating the overall landslide volume (9.18 · 107 m3). Furthermore, Sentinel-1 time series show that the landslide movements manifest substantial accelerations in early 2018 and 2019, coinciding with increased precipitations in the late rainy season which are identified as the most likely triggers of the observed accelerations. This study showcases the potential of integrating InSAR and seismic noise techniques to understand the landslide mechanism from ground to subsurface. [ABSTRACT FROM AUTHOR]

Although the Papuan fold and thrust belt (PFTB) is thought to accommodate convergence between the Pacific and Australian plates, the possible strain partitioning and its kinematic controls in the region are poorly understood. On 25 February 2018, a devastating Mw 7.5 earthquake jolted the southern area of the PFTB, central Papua New Guinea. The detailed imaging of the source parameters of this large earthquake is an urgent demand for a better understanding of the tectonism in the region. Here we used spaceborne interferometric synthetic aperture radar data to carefully determine the possible ruptured faults and associated fault geometries and further estimated the detailed slip of the 2018 Mw 7.5 earthquake. We find that the earthquake involved multiple faults failure, and a four‐segment fault model can reasonably produce the complex coseismic deformation, especially the observed bimodal displacements. The earthquake was dominated by reverse fault motion, and significant slip of up to ~0.7 m was documented on faults extending at depths great than 25 km. An integrated analysis of the fracture complexities suggests that possible strain partitioning in the PFTB could be tightly coupled with regional fault geometries and lithospheric properties. Our findings on the deep brittle failures suggest that crustal shortening across the PFTB could primarily control the growth of fold and thrust belt in the central Papua New Guinea. Key Points: Complete coseismic surface deformation generated from InSAR helps determine ruptured faults and constrain the complex source parametersThe 2018 Mw 7.5 Papua New Guinea earthquake was characterized by deep‐seated reverse faulting with ruptures extending into depths of 25 kmThis event revealed the possible strain partitioning in the Papuan fold and thrust belt and can help explain its growth [ABSTRACT FROM AUTHOR]

Rapid population growth combined with recent drought events and decades of political instability have left the residents of Kabul facing water scarcity, significantly relying on groundwater. Groundwater overexploitation might have induced various magnitudes of ground subsidence, however, to date, no comprehensive study of ground subsidence in Kabul has been conducted. In this study, we investigated the spatio-temporal evolution of ground deformation phenomena and its main governing processes in Kabul from 2014 to 2019 using C-Band Sentinel-1 derived Interferometric Synthetic Aperture Radar (InSAR) time-series from both ascending and descending orbits to extract the two-dimensional (2D) surface displacement field. Four subsidence bowls were distinguished with highly variable spatial extents and deformation magnitudes over four separate aquifer basins, with the maximum value of −5.3 cm/year observed in the Upper Kabul aquifer basin. A wavelet analysis suggests that there is a strong correlation between the groundwater level variations and subsidence. Investigation of hydrogeological data further reveals that the observed subsidence could be attributed to the presence of highly compressible clayey soils. This detailed space-borne regional survey provides new insights into the main governing mechanism of land subsidence in Kabul and may direct better mitigation plans of potential hazards. [ABSTRACT FROM AUTHOR]

The 2019 Mw 7.5 New Ireland earthquake occurred at an equatorial area where the dense vegetation prevents remote sensing techniques such as C- or X-band interferometric synthetic aperture radar (SAR) from acquiring coherent phase measurements. Therefore, in this paper, multiple remote sensing techniques including the L-band interferometric SAR, the range and azimuth offset tracking of SAR intensities, and the offset tracking of optical images were employed to map its co-seismic deformation field and to determine the slip distribution. The surface rupture was clearly and consistently captured by all offset observations, with the ground fault trace striking at an angel of 315° and extending over 10 km. An iterative weighting strategy based on the residual root mean square of inversions using individual datasets was developed to determine the relative weight of each dataset, allowing for the joint inversion of the fault geometry, the refinement of the dip angle, and the determination of the best fitting slip distribution. The resultant model indicates a nearly left-lateral strike-slip motion on the Weitin fault that ruptured to the surface with a maximum slip of 6.10 m, occurring at a depth of ~10 km, and a geodetic moment release of 1.03 × 1020 Nm, corresponding to a magnitude of Mw 7.31. The distribution of aftershocks shows about 70% of aftershocks were located in the area with increased Coulomb failure stress and few aftershocks in the subduction zone to the south of the Weitin fault were triggered by this event. [ABSTRACT FROM AUTHOR]

Satellite radar imagery can record surface deformation over a wide range in both phase and amplitude formats, with Interferometric Synthetic Aperture Radar (InSAR) achieving millimetre accuracy. Based on these satellite radar observations, landslide detection at a large scale can be enhanced, which is beneficial to landslide risk assessment and disaster mitigation. However, there are still several challenges in the landslide detection with satellite radar observations. This talk presents an automated SAR-based landslide detection system under development which addresses the five main challenges of conventional InSAR for landslide detection.The first challenge is dense vegetation that affects the coherence of SAR data. The effects can be weakened by use of SAR imagery with a long wavelength (e.g. S-band or L-band), a short temporal resolution, and/or a high spatial resolution (e.g. 1 m or even higher), and/or advanced InSAR time series. The second challenge is to deal with landslides with large deformation gradients, which can be addressed by SAR offset tracking and range split-spectrum interferometry (RSSI) methods with relatively low precision. We have developed an integrated approach to combine the RSSI and conventional InSAR to capture the large surface displacements of fast-moving landslides more precisely. Atmospheric effects represent another challenge of conventional InSAR for landslide detection, especially in mountain areas. The Generic Atmospheric Correction Online Service (GACOS) developed at Newcastle University is used to reduce atmospheric effects on radar observations and simplify the following time series analysis. The fourth challenge is the impacts of SAR geometry such as shadow and layover. The impacts can be pre-analysed using a high-resolution external DEM. Since very high-resolution (VHR) DEMs are often not available whilst processing VHR radar images (e.g. 1m or higher TerraSAR-X), a machine learning approach has been developed to identify water bodies, shadow and layover areas. The geometry impacts can be weakened with the joint use of descending and ascending tracks, different tracks with different incidence angles, or radar images from different radar missions. The fifth challenge is topographic effects in areas with high buildings or steep slopes, which could easily lead to phase unwrapping errors. A baseline linear combination approach has been developed to address it. In our automated SAR-based landslide detection system under development, the GACOS-assisted InSAR time series technique is employed to delimit deformation acceleration zones and detect extremely-slow-to-slow moving landslides. SAR offset tracking and RSSI are used in parallel to capture large displacements and detect moderate-to-fast moving landslides. Machine learning algorithms are developed to automatically map post-event landslides triggered by earthquakes or heavy rains. [ABSTRACT FROM AUTHOR]