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Detecting the slow motions of high and distant landslides in remote mountain areas has always been a problem. This paper takes the Woda landslide along the Jinsha River as an example to monitor landslide movement. Although some parts of the landslide body have been found to have moved in recent years, the timing and magnitude of motion have not been systematically monitored or interpreted. Here, we apply the SBAS time series strategy using 65-scene Sentinel-1A/B satellite InSAR images and study the spatial distribution and temporal behaviour of landslide movements between July 4, 2018, and August 29, 2020. Our research results show that the cumulative deformation on the left side of the landslide body with concentrated deformation was approximately 200 mm during the 2-year observation period. By calculating the relationship between the InSAR time series and the precipitation around the landslide, it is found that the landslide deformation is closely related to rainfall. GNSS technology is also deployed on the landslide mass and effectively complements InSAR technology. Simultaneously, based on the results of field surveys and hydrological data analysing the landslide's spatial deformation characteristics and deformation factors, the landslide deformation can also be inferred to be related to precipitation. The method used in this paper can be used for early recognition and early warning of high and remote landslides. [ABSTRACT FROM AUTHOR]

The Lenglongling Fault Zone (LLLFZ) is an important left‐lateral strike‐slip tectonic belt in the northeastern Tibetan Plateau (NETP), and the tectonic deformation and seismic activity of the LLLFZ reflect tectonic adjustments of the Qilian‐Haiyuan tectonic zone to the NETP. Although historical records of large earthquakes along the LLLFZ are not available, offset landforms reveal that large earthquakes have occurred. Therefore, offset landforms are used to study the seismic slip distribution to determine a fault slip model and earthquake recurrence behaviour based on an analysis of high‐resolution remote sensing images. Geomorphic markers associated with 316 systematically sinistrally deflected landforms were measured and analysed. The cumulative offset probability densities were analysed according to slip distributions measured along two segments of the fault. Offset density peaks in the eastern section of the fault decay exponentially with increasing offset size, suggesting that approximately seven palaeoearthquakes with an average slip of approximately 8 m occurred during the Holocene. The cumulative slips in the western segment increase gradually from west to east, with single‐event slips of approximately 2–3 m in the western part of the western segment and approximately 5–7 m in the eastern part. The seismic slip distributions of the LLLFZ indicate that the fault conforms to a quasi‐characteristic slip model. Both the eastern and western segments present typical left‐lateral strike‐slip movement. A magnitude of 8.0 was estimated for the LLLFZ palaeoearthquakes that occurred during the Holocene according to empirical relations. This study is helpful for understanding the tectonic deformation of the NETP. [ABSTRACT FROM AUTHOR]

For prediction of urban remote sensing surface temperature, cloud, cloud shadow and snow contamination lead to the failure of surface temperature inversion and vegetation‐related index calculation. A time series prediction framework of urban surface temperature under cloud interference is proposed in this paper. This is helpful to solve the problem of the impact of data loss on surface temperature prediction. Spatial and temporal variation trends of surface temperature and vegetation index are analyzed using Landsat 7/8 remote sensing data of 2010 to 2019 from Beijing. The geographically weighed regression (GWR) method is used to realize the simulation of surface temperature based on the current date. The deep learning prediction network based on convolution and long short‐term memory (LSTM) networks was constructed to predict the spatial distribution of surface temperature on the next observation date. The time series analysis shows that the NDBI is less than −0.2, which indicates that there may be cloud contamination. The land surface temperature (LST) modeling results show that the precision of estimation using GWR method on impervious surface and water bodies is superior compared to the vegetation area. For LST prediction using deep learning methods, the result of the prediction on surface temperature space distribution was relatively good. The purpose of this study is to make up for the missing data affected by cloud, snow, and other interference factors, and to be applied to the prediction of the spatial and temporal distributions of LST. This article is categorized under:Technologies > Machine Learning [ABSTRACT FROM AUTHOR]

This study investigates the 3 July 2015 (Mw=6.4) earthquake that affected Pishan County in Xinjiang, China. Using Synthetic Aperture Radar interferometry (InSAR), we mapped the near-field surface displacement of this event to better characterize the seismic source parameters. The inverted results suggest that a conjugate fault system could produce very similar deformation patterns as those observed in both ascending and descending InSAR observations, and the south-dipping fault is selected as the optimal fault responsible for the event. The selected fault was concentrated on a thrust fault with a strike of 112°, a dip of 25° and an average rake angle of 89°. The InSAR analysis reveals a fragmentation of the Western Kunlun north margin fault, and the overall deformation of the seismogenic fault is characterized by thrust motion, which is consistent with the transpressional tectonic characteristics of the major faults in this region. [ABSTRACT FROM AUTHOR]

The M 6.4 Menyuan earthquake occurred on the northern side of the Lenglongling fault (LLLF) in the mid-western of the Qilian-Haiyuan fault zone on January 21, 2016. The earthquake epicenter was distant from the Minle-Damaying and Huangcheng-Shuangta faults, eastern of the Northern Qilian Shan fault zone. A near northwest-striking rupture plane intersects the two faults at a certain angle. The focal mechanism solution shows that this was a thrust-type earthquake, slightly different from the strike-slip movement with a thrust component of the LLLF. Field geological mapping, tectonic geomorphology analysis, trench excavation and C dating reveal that (1) the LLLF has been obviously active since the Holocene, and may behave with characteristic slip behavior and produce M 7.3-7.5 earthquakes; (2) the LLLF appears as a flower structure in terms of structure style, and dips NNE at a steep angle; and (3) the most recent earthquake event occurred after 1815-1065 a BP. An associated fault, the Northern Lenglongling fault (NLLLF), is located at the northwestern end of the LLLF. Consequently, the NLLLF was continually subject to tectonic pushing effects from the left-lateral shear at the end of the LLLF, and, accordingly, it bent and rotated outward tectonically. Subsequently, the fault deviated from the dominant rupture azimuth and activity weakened. In the late Quaternary, it behaved as a thrust fault with no obvious deformation at the surface. This is indicated by the arc shape, with a micro-protrusion northeastward, and no geologic or geomorphic signs of surface rupturing since the late Quaternary. However, such faults could still rupture at depth, producing moderate-strong earthquakes. The geometric and kinematic properties of the NLLLF are in good agreement with the occurrence and kinematic properties of nodal plane 2, and with the distribution characteristics of the aftershocks and seismic intensity. Therefore, the NLLLF is a more suitable seismogenic structure for the M 6.4 Menyuan earthquake. In addition, the thrust movement of the NLLLF accommodates subsequent movement of the LLLF. During the historical evolution of the NLLLF, the LLLF and the NLLLF have affected the local topography through tectonic uplift. [ABSTRACT FROM AUTHOR]

Yangbajain contains the largest geothermal energy power station in China. Geothermal explorations in Yangbajain first started in 1976, and two plants were subsequently built in 1981 and 1986. A large amount of geothermal fluids have been extracted since then, leading to considerable surface subsidence around the geothermal fields. In this paper, InSAR time series analysis is applied to map the subsidence of the Yangbajain geothermal fields during the period from December 2011 to November 2012 using 16 senses of TerraSAR-X stripmap SAR images. In the case of the TerraSAR-X data, most orbital fringes were removed using precise orbits during the interferometric processing. However, residual orbital ramps remain in some interferograms due to the uncertainties in the TerraSAR-X orbits. To remove the residual orbital ramps, we estimated a best-fit ‘twisted plane’ for each epoch interferogram using quadratic polynomial models based on a network approach. This method removes most of the long-wavelength signals, including orbit ramps and atmospheric effects. The vertically stratified component (Topography Correlated Atmospheric Delay, TCAD) was also removed using a network approach. If the influence of seasonal frozen ground (SFG) is not taken into consideration, our results show that the subsidence rate around power plant I (the south plant) is approximately 20 mm/yr with a peak of 30 mm/yr. The subsidence rate around power plant II (the north plant) is approximately 10 mm/yr, when accounting for the influence of SFG on the power plant and its surrounding ground surface. Our results show that ground motion is caused by seasonal frozen ground and is strongly related to the temperature change. [ABSTRACT FROM PUBLISHER]

Using the Bam earthquake as an example, we apply the multiple-aperture interferometry (MAI) algorithm to measure the azimuth (AZI) displacement with multiple mode synthetic aperture radar (SAR) images (ScanSAR and image modes) and further on produce the 3-D coseismic displacement maps using well-known models: multiple independent interferometric SAR (InSAR) with different viewing angles and combining MAI with conventional InSAR. The 3-D displacement maps show that, besides accuracy of SAR observation, inversion model is another major perturbing factor limiting the accuracy of 3-D component reconstruction. That is, in the former model, the smaller the difference of incidence angles is, the more easily influenced by ill-conditioned systems the estimated parameters are. Based on characteristics of error sources of SAR observations, we classify observation errors into random error, systematic error, and gross error. Moreover, their characteristics of error propagation are analyzed in the two models, respectively. Error propagation analysis indicates that random errors only affect variability of inversion result, while systematic error and gross error cause not only variability but also bias or uncertainty in estimated parameters. The presented error analysis method provides a more comprehensive understanding of bias or uncertainty of 3-D estimated components, which will be a useful tool for evaluating errors in displacement fields obtained from SAR observations. In this letter, we also group multiple InSAR and MAI observations to estimate 3-D components using weighted least squares whose weights are given by the Förstner posterior variance estimation, which may avoid an ill-conditioned system, reducing line-of-sight and AZI random noises and improving accuracies of estimated 3-D components. [ABSTRACT FROM PUBLISHER]

Due to temporal and spatial decorrelation and other noise, the integer-cycle jumps always appear in the unwrapped phase. It is well known that phase unwrapping errors represent one of the major limitations of Interferometric SAR (InSAR). A phase closure method is presented to detect and correct phase unwrapping errors for discrete coherent points in InSAR time series analysis. Its application to ENVISAT Advanced Synthetic Aperture Radar (ASAR) data over the coastal zone of Cang-zhou, Hebei Province showed a significant improvement in the InSAR time series results, with the number of valid coherent pixels increasing from 68 000 to 186 400 and the root mean square (RMS) decreasing from 13. 1 mm to 5. 3 mm and 17. 5 mm to 4. 3 mm for two deforming areas respectively. [ABSTRACT FROM AUTHOR]