On 6 February 2023, a devastating doublet of earthquakes with magnitudes of Mw 7.8 and Mw 7.6 successively struck southeastern Turkey near the border of Syria. The earthquake sequence represents the strongest earthquakes in Turkey during the past 80 years and caused an extensive loss of life and property. In this study, we processed Sentinel-1 and GPS data to derive the complete surface displacement caused by the earthquake sequence. The surface displacements were adopted to invert for the fault geometry and coseismic slip distribution on the seismogenic faults of the earthquake sequence. The results indicate that the coseismic rupture of the Turkey earthquake sequence was dominated by left-lateral strike slips with a maximum slip of ~10 m on the East Anatolian Fault Zone (EAFZ) and the Sürgü fault (SF). Significant surface ruptures are recognized based on the geodetic inversion, which is consistent with the analysis of post-earthquake satellite images. The cumulative released moment of the two earthquakes reached 9.62 × 10²⁰ Nm, which corresponds to an event of Mw 7.95. Additionally, the interseismic fault slip rates and locking depths along the central and western segments of the EAFZ were estimated using the high-resolution long-term velocity field. The results reveal significant lateral variations of fault slip rates and locking depths along the central and western segments of the EAFZ. Generally, the estimated fault locking zone showed good spatial consistency with the coseismic fault rupture of the Mw 7.8 shock on the EAFZ. The static coulomb failure stress (CFS) change due to the Mw 7.8 earthquakes suggests that the subsequent Mw 7.6 event was certainly promoted by the Mw 7.8 shock. The stress transfers from the fault EAFZ to the fault SF were realized by unclamping the interface of the fault SF, which significantly reduces the effective normal stress on the fault plane. Large CFS increases in the western Puturge segment of the EAFZ, which was not ruptured in the 2020 Mw 6.8 and the 2023 Mw 7.8 earthquakes, highlight the future earthquake risk in this fault segment.

Previous studies have shown that thermal infrared radiation (TIR) anomalies occur in the vicinity of fractures that form when a rock is loaded to failure. Different types of fracturing modes correspond to different TIR anomaly trends. However, the spectral features and the mechanisms responsible for the TIR changes in the fracturing stage remain poorly understood. In this paper, experiments involving observations of the thermal infrared spectrum (8.0–13.0 μm) of loaded sandstone during the fracturing stage were conducted under outdoor conditions. The experiment yielded the following results: (1) Different fracturing modes can lead to different trends in the spectral radiance variation; (2) when an extensional fissure appeared on the rock surface, the radiance increased with a local peak in the 8.0–9.7 μm range; (3) when local bulging formed at the surface, the radiance decreased, with a local valley in the 8.0–9.7 μm range. The radiance variation caused by morphologic changes is the combined result of changes in both the temperature and the emissivity. The characteristic waveband corresponding to the reststrahlen features (RF) of quartz was mainly related to the emissivity change. This study provides a preliminary experimental foundation for the detection of crustal surface fractures via satellite-based remote sensing technology.

The knowledge of Arctic Sea ice coverage is of particular importance in studies of climate change. This study develops a new sea ice classification approach based on machine learning (ML) classifiers through analyzing spaceborne GNSS-R features derived from the TechDemoSat-1 (TDS-1) data collected over open water (OW), first-year ice (FYI), and multi-year ice (MYI). A total of eight features extracted from GNSS-R observables collected in five months are applied to classify OW, FYI, and MYI using the ML classifiers of random forest (RF) and support vector machine (SVM) in a two-step strategy. Firstly, randomly selected 30% of samples of the whole dataset are used as a training set to build classifiers for discriminating OW from sea ice. The performance is evaluated using the remaining 70% of samples through validating with the sea ice type from the Special Sensor Microwave Imager Sounder (SSMIS) data provided by the Ocean and Sea Ice Satellite Application Facility (OSISAF). The overall accuracy of RF and SVM classifiers are 98.83% and 98.60% respectively for distinguishing OW from sea ice. Then, samples of sea ice, including FYI and MYI, are randomly split into training and test dataset. The features of the training set are used as input variables to train the FYI-MYI classifiers, which achieve an overall accuracy of 84.82% and 71.71% respectively by RF and SVM classifiers. Finally, the features in every month are used as training and testing set in turn to cross-validate the performance of the proposed classifier. The results indicate the strong sensitivity of GNSS signals to sea ice types and the great potential of ML classifiers for GNSS-R applications.

On 4 and 6 July 2019, an M_w 6.4 foreshock and an M_w 7.1 main shock successively struck the city of Ridgecrest in eastern California. These two events are the most significant earthquake sequences to strike in this part of California for the past 20 yr. We used both continuous global positioning system (GPS) measurements and interferometric synthetic aperture radar (InSAR) images taken by the Sentinel-1 and ALOS-2 satellites in four different viewing geometries to fully map the coseismic surface displacements associated with these two earthquakes. Using these GPS and InSAR measurements both separately and jointly, we inverted data to find the coseismic slip distributions and fault dips caused by the two earthquakes. The GPS-constrained slip models indicate that the M_w 7.1 main shock was predominately controlled by right-lateral motions on a series of northwest-trending faults, while the M_w 6.4 foreshock involved both right-lateral slipping on a northwest-trending fault and left-lateral slipping on a northeast-trending fault. The two earthquakes both generate significant surface slip, with the maximum inferred slip of 5.54 m at the surface. We estimate the cumulative geodetic moment of the two earthquakes to have been 4.93 × 10¹⁹ Nm, equivalent to M_w 7.1. Furthermore, our calculations of the changes in static Coulomb stress suggest that the M_w 7.1 main shock was promoted significantly by the M_w 6.4 foreshock. This latest Ridgecrest earthquake sequence ruptured only the northern part of the seismic gap between the 1992 M_w 7.3 Landers earthquake and the 1872 M 7.4–7.9 Owens Valley earthquake. The earthquake risk in this area, therefore, remains very high, considering the significant accumulation of strain in the Eastern California Shear Zone, especially in the southern part of the seismic gap.

The Sikkim–Bhutan seismic gap has witnessed a long earthquake quiescence since the 1714 M7.5~8.5 earthquake. The state of stress accumulation beneath the Sikkim–Bhutan Himalaya and its spatial correlation with seismicity remains unclear due to the lack of geodetic measurements and the low levels of seismic activity. We compile Global Positioning System (GPS) measurements in southern Tibet with the available velocities in the Sikkim–Bhutan Himalaya to reveal the characteristics of strain buildup on the Main Himalayan Thrust (MHT). We correct non-tectonic hydrological loading effects in a GPS time series to accurately determine the Three-Dimensional (3D) velocities of each continuous station. Extensive GPS measurements yield convergence rates of 16.2~18.5 mm/y across the Sikkim–Bhutan Himalaya, which is quite consistent with that observed elsewhere in the Himalaya. Based on a double-ramp structure of the MHT, a refined 3D coupling image is inverted using a dense network of GPS velocities. The result indicates significant along-strike variations of fault coupling beneath the Sikkim–Bhutan Himalaya. The locking width (coupling > 0.5) of western Bhutan reaches ~100 km, which is 30~40% wider than Sikkim and eastern Bhutan. An obvious embayment of decoupling zone near the border between Sikkim and western Bhutan is recognized, and coincides spatially with the rupture terminates of the 1934 Mw8.2 and the 1714 M7.5~8.5 earthquakes, indicating that the large megathrust earthquakes along the Sikkim–Bhutan Himalaya are largely segmented by the spatial variation of frictional properties on the MHT. Using a new compilation of seismic records in the Sikkim–Bhutan Himalaya, we analyze the spatial correlation between fault coupling and seismic activity. The result suggests that the seismicity in the Bhutan Himalaya is broadly distributed, instead of restricted in the lower edge of the interseismic locking zone. This implies that the seismic activity in the Bhutan Himalaya is not uniquely controlled by the stress accumulation at the downdip end of the locked portion of the MHT.