The Daguangbao mega-landslide (China), induced by the 2008 Wenchuan earthquake (Mw = 7.9), with an area of approximately 8 km2, is one of the largest landslides in the world. Experts predicted that the potential risk and instability of the landslide might remain for many decades, or even longer. Monitoring the activity of such a large landslide is hence critical. Terrain Observation by Progressive Scans (TOPS) mode from the Sentinel-1 satellite provides us with up-to-date high-quality Synthetic Aperture Radar (SAR) images over a wide ground coverage (250 × 250 km), enabling full exploitation of various InSAR applications. However, the TOPS mode introduces azimuth-dependent Doppler variations to radar signals, which requires an additional processing step especially for SAR interferometry. Sentinel-1 TOPS data have been widely applied to earthquakes, but the performance of TOPS data-based time series analysis requires further exploitation. In this study, Sentinel-1 TOPS data were employed to investigate landslide post-seismic activities for the first time. To deal with the azimuth-dependent Doppler variations, a processing chain of TOPS time series interferometry approach was developed. Since the Daguangbao landslide is as a result of the collapse of a whole mountain caused by the 2008 Mw 7.9 Wenchuan earthquake, the existing Digital Elevation Models (DEMs, e.g. SRTM and ASTER) exhibit height differences of up to approximately 500 m. Tandem-X images acquired after the earthquake were used to generate a high resolution post-seismic DEM. The high gradient topographic errors of the SRTM DEM (i.e. the differences between the pre-seismic SRTM and the actual post-seismic elevation), together with low coherence in mountainous areas make it difficult to derive a precise DEM using the traditional InSAR processing procedure. A re-flattening iterative method was hence developed to generate a precise TanDEM-X DEM in this study. The volume of the coseismic Daguangbao landslide was estimated to be of 1.189 ± 0.110 × 109 m3 by comparing the postseismic Tandem-X DEM with the preseismic SRTM DEM, which is consistent with the engineering geological survey result. The time-series results from Sentinel-1 show that some sectors of the Daguangbao landslide are still active (and displaying four sliding zones) and exhibiting a maximum displacement rate of 8 cm/year, even eight years after the Wenchuan earthquake. The good performance of TOPS in this time series analysis indicates that up-to-date high-quality TOPS data with spatiotemporal baselines offer significant potential in terms of future InSAR applications.This work was supported by the National Natural Science Foundation of China under Grant No. 41474003. The research stay of Dr. Tomás at Newcastle University was funded by the Ministry of Education, Culture and Sport within the framework of Project PRX14/00100. Additional funding was obtained from the Spanish Government under projects TIN2014-55413-C2-2-P and ESP2013-47780-C2-2-R. Part of this work is also supported by the UK Natural Environmental Research Council (NERC) through the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET, ref.: come30001) and the LICS and CEDRRiC projects (ref. NE/K010794/1 and NE/N012151/1, respectively), the ESA-MOST DRAGON-3 projects (ref. 10607 and 10665), the ESA-MOST DRAGON-4 project (ref. 32244) and the Open Fund from the Key Laboratory of Earth Fissures Geological Disaster, Ministry of Land and Resources (ref.: gla2013001)

Landslide disasters occur frequently in the mountainous areas in southwest China, which pose serious threats to the local residents. Interferometry Synthetic Aperture Radar (InSAR) provides us the ability to identify active slopes as potential landslides in vast mountainous areas, to help prevent and mitigate the disasters. Quickly and accurately identifying potential landslides based on massive SAR data is of great significance. Taking the national highway near Wenchuan County, China, as study area, this paper used a Stacking-InSAR method to quickly and qualitatively identify potential landslides based on a total of 40 Sentinel SAR images acquired from November 2017 to March 2019. As a result, 72 active slopes were successfully detected as potential landslides. By comparing the results from Stacking-InSAR with the results from the traditional SBAS-InSAR (Small Baselines Subset) time series method, it was found that the two methods had a high consistency, with 81.7% potential landslides identified by both of the two methods. A detailed comparison on the detection differences was performed, revealing that Stacking-InSAR, compared to SBAS-InSAR may miss a few active slopes with small spatial scales, small displacement levels and the ones affected by the atmosphere, while it has good performance on poor-coherence regions, with the advantages of low technical requirements and low computation labor. The Stacking-InSAR method would be a fast and powerful method to qualitatively and effectively identify potential landslides in vast mountainous areas, with a comprehensive understanding of its specialty and limitations.

Landslides are major geological hazards and frequently occur in mountainous areas with steep slopes, often causing significant loss. Interferometric Synthetic Aperture Radar (InSAR) has been widely used in landslide measurement over the last three decades. However, InSAR only can measure one-dimensional displacements (i.e. those in the radar’s line of sight (LOS) direction), resulting in the uncertainty between LOS displacement and the real slope displacement. In this paper, based on ascending and descending data from Sentinel-1 satellite, a wide-area potential landslide early identification was carried out using SBAS-InSAR in the whole of Mao County, a mountainous area in western Sichuan (China), with a total of 41 potential landslides successfully detected. Based on the quantitative analysis, the results show that the InSAR LOS measurement values are slope aspect and gradient-dependent. Finally, we innovatively derived a LOS displacement sensitivity map of InSAR in landslide measurement, revealing the relationship between LOS displacement, real displacements on slopes with arbitrary aspects and gradients, and SAR geometric distortion. This is a generalized finding useful for any slopes. It provides theoretical support to acquire and understand the real slope displacement from InSAR landslide measurement, which is vital to assist in correctly interpreting LOS displacement and carrying out subsequent quantitative geological engineering analysis.

Assessment of seismic hazard relies on estimates of how large an area of a tectonic fault could potentially rupture in a single earthquake. Vital information for these forecasts includes which areas of a fault are locked and how the fault is segmented. Much research has focused on exploring downdip limits to fault rupture from chemical and thermal boundaries, and along-strike barriers from subducted structural features, yet we regularly see only partial rupture of fully locked fault patches that could have ruptured as a whole in a larger earthquake. Here we draw insight into this conundrum from the 25 April 2015 M_w 7.8 Gorkha (Nepal) earthquake. We invert geodetic data with a structural model of the Main Himalayan thrust in the region of Kathmandu, Nepal, showing that this event was generated by rupture of a décollement bounded on all sides by more steeply dipping ramps. The morphological bounds explain why the event ruptured only a small piece of a large fully locked seismic gap. We then use dynamic earthquake cycle modeling on the same fault geometry to reveal that such events are predicted by the physics. Depending on the earthquake history and the details of rupture dynamics, however, great earthquakes that rupture the entire seismogenic zone are also possible. These insights from Nepal should be applicable to understanding bounds on earthquake size on megathrusts worldwide.

This paper presents a novel method for extracting the land vertical displacement rates (VDRs) in Shanghai (China) using the multi-platform SAR images collected between 2009 and 2010, i.e., the ascending/descending COSMO-SkyMed (CSK) X-band images and the descending TerraSAR (TSX) X-band images. Different from the conventional approach the proposed method estimates the VDRs by multi-temporal interferometric SAR processing (i.e., temporarily coherent point InSAR, TCPInSAR) and the localized least square (LS) solution, through which the horizontal displacement rates (HDRs) can be also derived as the by-product. The three types of displacement rates in the radar line of sight (LOS) are first estimated by TCPInSAR with use of the ascending/descending CSK and descending TSX data. Both the VDRs and HDRs are then estimated by a localized LS method on the basis of the three types of LOS displacement rates derived by TCPInSAR. For comparison purposes, the VDRs for the single-platform SAR data are also obtained through dividing the LOS displacement rates by the cosine of the radar incidence angle. The analysis with the aid of GPS data shows the horizontal motion due to the geological settings in Shanghai cannot be ignored, and the VDRs derived from the single-platform data are not accurate and reliable without taking into account the horizontal motion. The experimental results indicate the TCPInSAR-LS method can be used to efficiently improve the accuracy in the VDRs by integrating the multi-platform SAR data and considering both horizontal and vertical motion, thus overcoming the disadvantages in the conventional approach. The improved VDRs in Shanghai range between −22.8 and 9.6 mm/year, while the relative east-west motion rates range between −7.2 and 6.2 mm/year, and the relative north–south motion is subtle and can be ignored. Analysis of the improved VDRs shows that a slightly uplifting area of about 70 km² appears in the west downtown of Shanghai, and a subsiding bowl appears in the Hongkou District of Shanghai. The validation indicates that the uplifting trend can be ascribed to the measures conducted by the Shanghai municipal government, i.e., decreasing the groundwater pumping volume and increasing the groundwater recharge volume.