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On February 22, 2023, a devastating landslide occurred on the mining slope of an open-pit coal mine in Inner Mongolia, China, leading to the mining area being buried and 53 fatalities. The source area of the landslide measured approximately 500 m in both length and width, with an estimated volume of the deposited material reaching approximately 5 million cubic metres. Based on the severe impact of this incident, our study conducted preliminary research using a combination of methodologies, including particle image analysis, synthetic aperture radar interferometry, interpretation of optical remote sensing data, and post-event news reports analysis. The results indicated that the landslide lasted 23 s from initiation to cessation of movement. The historical deformation indicated that prior to the resumption of the mining activities, only localized deformation was observed at the rear edge of the landslide. However, when mining activities resumed in April 2021 and extended to the vicinity of the north slope, the deformation range and rate in the source area of the landslide rapidly increased. The investigation deduced that the soft foundation at the slope bottom and mining activities are the primary causative factors of this event. Mining activities, which stripped coal seams within the slope and surface rock masses, led to the expansion of tension cracks within the landslide body, weakening resisting forces at the leading edge and thus playing a significant role in destabilizing the landslide body. The evolution of the landslide from incubation to instability could be divided into four stages: early microcrack development, slow creep, accelerated deformation after resumption of mining, and ultimate instability. Therefore, it is of great significance to advance real-time deformation monitoring and early warning systems specifically those designed for mining slope areas by comprehensive measures. Furthermore, enhancing the high-frequency monitoring capabilities of synthetic aperture radar satellites is crucial to reducing the occurrence of these catastrophic events. [ABSTRACT FROM AUTHOR]

Recurrence of large-scale ancient landslides often manifests as catastrophic events, so it is important to assess their stability by monitoring the deformation process. In this study, the Da'ao ancient landslide along the Jinsha River in China was investigated and analyzed. Field investigation showed that the landslide body is being experienced deforming with many new failures. Three sliding events can be identified according to different main scarps. The Permanent Scatterer Synthetic Aperture Radar Interferometry (PS-InSAR) data further revealed that the most obvious deforming area is in the middle and toe part of the sliding body with the largest cumulative displacement of 55 mm during 2017 to 2021. Additionally, the relatively stable zone and the accelerating deforming zone are divided by displacement rate. This indicates that the Da'ao landslide is becoming unstable. At the same time, the Particle Flow Code (PFC) simulation verified that the risk of landslide recurrence is likely when subjected to strong earthquakes or heavy rainfall, and the resulting sidings could dam the Jinsha River. In addition, the analysis results suggested that the displacement rates were approximately 5 mm/year and 13.3 mm/year before and after the Ms 5.2 earthquake, respectively, which occurred on 04/21/2019. The deformation changed with seasonal variation during 2017–2021 and lagged behind precipitation, while the earthquake can increase the amount and rate of displacement. The results presented here can help us to understand how landslides recur over time and their deformation and failure mechanisms, which is useful for disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

The magnitude (spatial location, area, and volume) of landslides is a crucial parameter for estimating the quantitative risk and preventing landslide hazards. This study proposes a novel approach to forecast the volume of potential landslides in alpine-canyon terrain by combining the empirical relationship linking landslide volume (V) to characteristics and synthetic aperture radar interferometry (InSAR) technology in the northeast of the Qinghai-Tibet Plateau, China. First, a historical landslide inventory with detailed characteristics was established by reviewing literature and field investigation. Then, the relationship between volume and characteristics of landslides was analyzed based on the least-squares linear regression of the logarithmic transformation. Finally, the relationships of the colluvial landslides (V = 0.170 × L 0.982 × W 1.589 × H 0.471) and loess landslides (V = 0.170 × L 0.796 × W 2.151 × H 0.048) were obtained after verifying several landslides. The ground deformation rate was generated, and 217 potential landslides were detected using 47 descending Sentinel-1A images acquired from January 11, 2020, to July 16, 2021, and 40 ascending Sentinel-1A images acquired from January 11, 2020, to April 23, 2021. Through the established relationships, the total volumes of all potential colluvial and loess landslides were estimated to be 8.77 × 108 m3 and 5.74 × 108 m3, respectively. This study provides an improved empirical relationship to better forecast the volume of potential landslides in alpine-canyon terrain. Furthermore, the study helps in understanding the future dynamic evolution of potential landslides using InSAR technology, which provides scientific understanding to assess and prevents potential landslide hazards and risks in the Bailong River basin. [ABSTRACT FROM AUTHOR]

Slope failures frequently occur in open-pit mines, resulting in significant losses. Identifying the precursory displacements and triggering factors for detecting unstable slopes is critical for reducing and preventing their impact. This study proposes combining satellite radar interferometry and infrared thermography with numerical simulation to determine unstable slopes in an open-pit mine. First, interferometric synthetic aperture radar (InSAR) is utilized to capture deformation information in a line-of-sight direction in terms of velocity to locate the long-time movement on a large scale. The application of infrared thermography enables the detection of peculiar features based on the different thermal patterns occurring along the slope and the interpretation of critical sectors matching with the instability zones highlighted by the InSAR. In particular, areas with various surface temperatures were associated with vegetated spots, new benches, bare sectors, and contact between different lithologies. By means of three-dimensional stability analyses, the associated interferometry movement confirmed the slope instability, and a critical failure surface was found using two-dimensional numerical simulation. The efficacy of the proposed approach is verified through a massive slope failure in the Qidashan open-pit mine in Liaoning, China. It predicts the slope failures caused by intense rainfall and reveals the progressive failure mechanism. The practical application has demonstrated the feasibility and accuracy of the proposed approach for detecting failure precursors, providing a novel procedure for remotely identifying critical slopes in an open-pit with frequent mining activity. [ABSTRACT FROM AUTHOR]

Zongling landslides are the typical karst landslides located in the southwest of China, which have severely threatened the lives of local people. It is of great significance to monitor the real surface deformation of the unstable slopes for the hazard prevention by using the InSAR technology owing to its high precision and frequent revisit. However, the decorrelation effect and atmospheric delay caused by dense vegetation and alpine terrain result in less effective targets to monitor the full deformation of karst landslides. Besides, the derived deformation along one line-of-sight (LOS) direction can result in the misunderstanding of the real kinematics landslide process. In this study, we combine the multi-temporal distributed scatterer InSAR technology (DS-InSAR) and the multi-platform SAR measurements to derive the multi-dimension deformation time series of Zongling landslides. First, both ALOS/PALSAR-2 datasets and Sentinel-1A images from ascending and descending orbits are employed to acquire the deformation along the LOS direction using the DS-InSAR method, where dense effective targets can be achieved, and the deformation patterns can be revealed. Then, the multi-dimensional small baseline subset (MSBAS) method is used to retrieve the horizontal and vertical deformation of Zongling landslides, which further improve the temporal sampling of the deformation time series. Finally, the comprehensive analyses of driving factors and failure mode are conducted according to the spatial–temporal deformation characteristics, and field investigation. The results indicate that this technical route can not only retrieve the landslide deformation with high spatial–temporal sampling density, but also provide new insight into the driven effect of natural factors and mining activities on karst landslides. [ABSTRACT FROM AUTHOR]

China's Mars exploration mission has stimulated tremendous interest in planetary science exploration recently. To propose potential scientific research projects, this study presents a concept simulation for the measurement of Martian atmospheric winds using the Doppler Michelson interferometry technique. The simulation is based on the satellite instrument initially designed for the Dynamic Atmosphere Mars Observer (DYNAMO) project to measure vertical profiles of winds from the 1.27 μm airglow observations in the Martian atmosphere. A comprehensive DYNAMO measurement simulation forward model based on an orbit submodel, an atmospheric background field submodel, and an instrument submodel is developed using the Michelson equation. The simulated interferogram signal over the field of view (FOV) calculated by the forward model is associated with the filter transmittance function, column emission rate of airglow, wind velocity, temperature, and the Michelson phase. The agreement between the derived atmospheric signals from the simulated interferogram without altitude inversion and the input parameters used to initiate the forward model confirms the validity of the forward model. [ABSTRACT FROM AUTHOR]

Exploration of geothermal resources has become one of the major drivers for urbanization and economic transformation in southeast China, and it calls for temporal and spatial resolution improvements on conventional geophysical techniques under complex near-surface conditions. A dense seismic network including 192 sensors, with its aperture around 4.8 km, was deployed to record ambient noise for local-scale geothermal reservoir imaging in central Zhejiang Province, southeast China. With the ultrashort (less than 5 days) observation, a subset of the total station pairs was extracted to conduct seismic interferometry and dispersion measurements. This customized subnet was qualified to be an overdetermined system to achieve similar performance of entire network for the eikonal tomography with higher efficiency. The recorded high-frequency noise sources turned out to be rather homogeneous distributions, except for the dominant direction of northern Jinhua urban area. Azimuthal effects and wavelength restriction of dispersion measurements were quantified by simulating source–receiver responses under non-equipartitions of energy. The azimuth–velocity variations of field dataset verified that phase velocity measurements using the tested wavelength restriction were robust under different source–receiver orientations. The obtained phase velocity maps were comparable with the geological map. Furthermore, the inverted body wave velocities coincide well with the borehole data. Shear wave velocity profiles revealed corresponding fracture and depression structures of the reservoir. Finally, multiple geophysical properties delineate the shallow geothermy to be karst fissure water heated at certain earth temperature gradient. [ABSTRACT FROM AUTHOR]

On September 14, 2019, a reactivated landslide with a volume of 1.3 × 107 m3 occurred in Changhe Town, Tongwei County, Gansu Province, China. As a result, a provincial highway, brickfield, and bridge were destroyed. Based on field investigation, interferometric synthetic aperture radar (InSAR) as well as unmanned aerial vehicle (UAV) photogrammetry, high-resolution remote sensing imagery, and digital elevation model, we addressed the surface displacement, travel distance, topographic changes, and causative factors of the Changhe landslide. The result shows the combination of ascending and descending orbit datasets can not only be used to monitor the landslide surface displacement but also to verify the deformation results. This landslide is a typical retrogressive landslide where large pre-failure deformation exists in the lower part of the landslide body. We detected the surface travel distance of the landslide and found spatial differences exist in the surface travel distance of the landslide. The deposit volume slightly exceeds erosion volume due to decompaction during the landslide. The frequency distribution of the basic topographic factors before and after the landslide is different, which indicates that the landslide event significantly changed the local topography and geomorphology. This study provides an insight into the spatiotemporal evolution of the landslide and has practical importance for early warning of landslides and risk mitigation. [ABSTRACT FROM AUTHOR]

Local climate zone (LCZ) maps that describe the urban surface structure and cover with consistency and comparability across cities are gaining applications in studies of urban heat waves, sustainable urbanization and urban energy balance. Following the standard World Urban Database and Access Portal Tools (WUDAPT) method, we generated LCZ maps for over 20 individual cities and 3 major economic regions in China. Based on the confusion matrices constructed by manual comparison between the predicted classes and ground truths, we highlight the following: (1) notable variation in overall accuracies (i.e., 60%–89%) among cities were observed, which was mainly due to class incompleteness and distinct proportions of natural landscapes; (2) building classes in selected cities were poorly classified in general, with a mean accuracy of 48%; (3) the sparsely built class (i.e., LCZ 9), which is rare in the selected Chinese cities, had the lowest classification accuracy (32% on average), and the class of low plants had the widest accuracy range. The findings indicate that the standard WUDAPT method alone is insufficient for generating LCZ products that demonstrate practical value, especially for built-up areas in China, and the misclassification is largely caused by the lack of building height data. This result is confirmed by a refinement test, in which the urban DEM retrieved from Sentinel-1 data with radar interferometry technique was used. The study shows a detailed and comprehensive assessment of applying the WUDAPT method in China and a feasible refinement strategy to improve the classification accuracy, especially for the built-up types of LCZ. The study could serve as a useful reference for generating quality-ensured LCZ maps. This study also examines and explores the relationship between socio-economic status and LCZ products, which is essential for further implementations. [ABSTRACT FROM AUTHOR]

After the deadly Ms 8.0 Wenchuan earthquake, the Wenjiagou landslide produced steep topography, a narrow gully and abundant loose sediments; these factors have contributed to the high debris flow risk in the Wenjiagou area during subsequent rainy seasons. At least five debris flows have occurred in the Wenjiagou area between September 24, 2008, and September 18, 2010, which resulted in seven casualties and an economic loss of approximately 446 million RMB. To reduce the risk of debris flows and landslides, the Wenjiagou Valley Debris Flow Control Project (WVDFCP), which cost over 2 billion RMB, was carried out and completed in 2011. The control measures of the project effectively reduced the scale and damage of the following debris flows. In this paper, the recent deformation of the giant landslide and its effect on the WVDFCP are evaluated by applying a time-series interferometric synthetic aperture radar (InSAR) technique based on distributed scatterers (DSs) to the Radardat-2 SAR data collected from June 2014 to September 2015. In addition, the experimental results show that most areas of the landslide are stable, with an average deformation rate of less than 5.0 mm/year. The results demonstrate that the control measures of the WVDFCP not only reduced the damage caused by the later debris flows but also contributed to the consolidation of the loose sediments in the Wenjiagou landslide area. The time-series InSAR technique based on the DSs of high-resolution SAR images is an important tool for deformation monitoring of earthquake-induced landslides. [ABSTRACT FROM AUTHOR]

The Xinmo landslide occurred in the early morning of 24 June 2017 at about 5:38 am local time. This catastrophic event caused enormous casualties and huge economic losses in Xinmo Village, Mao County, Sichuan Province, China. In this study, Synthetic Aperture Radar (SAR) datasets acquired by X-band TerraSAR-X, Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) aboard the Advanced Land Observing Satellite-2 (ALOS-2), and C-band Sentinel-1 over the disaster area were collected and analyzed to characterize this landslide. The high-resolution TerraSAR-X intensity images were used to evaluate the landslide disaster and delineate the sliding area. Afterwards, two ALOS-2 PALSAR-2 image pairs and a stack of 45 Sentinel-1 images were processed to detect precursory movements of the landslide surface, using the conventional differential InSAR (DInSAR) method and advanced time series InSAR analysis. The unstable source area near the ridge was identified from the displacement rate map derived from Sentinel-1 datasets. The maximum displacement rate detected at the source area was −35mm/year along the radar line of sight (LOS) direction. The time series of LOS displacements over 2 years presents an easily discerned seasonal evolution pattern. In particular, a sudden acceleration of the displacement, dozens of days before the collapse was clearly captured by the Sentinel-1 observations, which might suggest that early warning of landslide disasters is possible given the availability of operational SAR data acquired in frequent repeat-pass mode, such as the Sentinel-1 twin-satellite constellation. [ABSTRACT FROM AUTHOR]

Post-event Interferometric Synthetic Aperture Radar (InSAR) analysis on a stack of 45 C-band SAR images acquired by the ESA Sentinel-1 satellites from 9 October 2014 to 19 June 2017 allowed the identification of a clear precursory deformation signal for the Maoxian landslide (Mao County, Sichuan Province, China). The landslide occurred in the early morning of 24 June 2017 and killed more than 100 people in the village of Xinmo. Sentinel-1 images have been processed through an advanced multi-interferogram analysis capable of maximising the density of measurement points, generating ground deformation maps and displacement time series for an area of 460 km straddling the Minjiang River and the Songping Gully. InSAR data clearly show the precursors of the slope failure in the source area of the Maoxian landslide, with a maximum displacement rate detected of 27 mm/year along the line of sight of the satellite. Deformation time series of measurement points identified within the main scarp of the landslide exhibit an acceleration starting from April 2017. A detailed time series analysis leads to the classification of different deformation behaviours. The Fukuzono method for forecasting the time of failure appear to be applicable to the displacement data exhibiting progressive acceleration. Results suggest that satellite radar data, systematically acquired over large areas with short revisiting time, could be used not only as a tool for mapping unstable areas, but also for landslide monitoring, at least for some typologies of sliding phenomena. [ABSTRACT FROM AUTHOR]

Ground-based synthetic aperture radar (GBSAR) is a powerful tool used in monitoring structures, such as bridges and dams. However, despite the extremely short range of GBSAR interferometry, the atmosphere effects cannot be neglected. The permanent scatterer technique is an effective operational tool that utilizes a long series of SAR data and detects information with high accuracy. An algorithm based on the permanent scatterer technique is developed in accordance with the phase model used in GBSAR interferometry. In this study, atmospheric correction is carried out on a real campaign (Geheyan Dam, China). The atmosphere effects created using this method, which utilizes SAR data, can be reduced effectively compared to when plumb line data are used. [ABSTRACT FROM AUTHOR]

We present the current status of seismic noise interferometry to reconstruct the seismic velocity and discuss the four phases from single-station data preparation to quality control of data processing procedures. Each phase of the processing procedure has been discussed in detail with salient examples using seismic data acquired in Changbaishan volcano region. In the end, we use continuous recordings in Jilin, China to track the temporal change of the seismic velocity variations with the method promoted in this paper. We filter the data between the frequency band 0.02 and 0.1 Hz, which the Rayleigh waves are most sensitive to the shear wave velocities in the crust and uppermost mantle. The long-term seismic variations present strong seasonal influence which may be caused by precipitation. We find clear evidence that the seismic velocity drops by up to ∼0.8% which may be caused by the dilatation of the volcanic edifice before the Mar. 11 2011 Japan earthquake. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for retrieving three-dimensional (3-D) displacement fields of mining areas from a single interferometric synthetic aperture radar (InSAR) pair. This method fully exploits the mechanism of mining subsidence, specifically the proportional relationship between the horizontal displacement and horizontal gradient of vertical displacements caused by underground mining. This method overcomes the limitations of conventional InSAR techniques that can only measure one-dimensional (1-D) deformation of mining area along the radar line-of-sight direction. The proposed method is first validated with simulated 3-D displacement fields, which are obtained by the FLAC $$^{\mathrm{3D}}$$ software. The root mean square errors of the 3-D displacements retrieved by the proposed method are 13.7, 27.6 and 3.6 mm for the West-East, North-South, and Up-Down components, respectively. We then apply the proposed method to estimate the 3-D displacements of the Qianyingzi and the Xuzhou coal mines in China, respectively, each along with two Advanced Land Observing Satellite (ALOS) Phased Array Type L-band Synthetic Aperture Radar images. Results show that the estimated 3-D displacement is highly consistent with that of the field surveying. This demonstrates that the proposed method is an effective approach for retrieving 3-D mining displacement fields and will play an important role in mining-related hazard prevention and environment assessment under limited InSAR acquisitions. [ABSTRACT FROM AUTHOR]