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Interferometric Synthetic Aperture Radar (InSAR) technology is capable of detecting large areas of potentially unstable slopes. However, traditional time-series InSAR methods yield fewer valid measurement points (MPs) in alpine canyon regions. Distributed Scatterer (DS) Interferometry (DSI) technology serves as a potent tool for monitoring surface deformation in complex land cover areas; nonetheless, it grapples with high computational demands and low efficiency when interpreting deformation across extended time series. This study proposes an image compression–based DSI (ICDSI) method, which, building upon the DSI method, utilizes principal component analysis (PCA) to compress multi-temporal SAR images in the time dimension. It develops a module for compressing long-time sequence SAR images, acquires the compressed image (referred to as a virtual image), and integrates the developed image compression module into the DSI data processing flow to facilitate the inversion of long-time sequence InSAR land surface deformation information. To validate and assess the credibility of the ICDSI method, we processed a total of 78 ascending and 81 descending scenes of Sentinel-1A images spanning the period 2019–2021 using Small Baseline Subset (SBAS), DSI, and the ICDSI method proposed in this paper. Subsequently, these methods were applied to detect landscape displacements on both coasts of the Jinsha River Basin. The investigation reveals that the ICDSI method outperforms SBAS and DSI significantly in monitoring landslide displacements, enabling the detection of more measurement points (MPs) while utilizing less raw data. The accomplishments of this research program carry crucial theoretical implications and practical application value for the detection of surface deformation using long-time series InSAR. [ABSTRACT FROM AUTHOR]

The Jianshanying landslide in Guizhou province, China, is a typical mining-induced landslide with its complex formation in karst mountainous area. However, the spatiotemporal deformation characteristics and failure mechanism are still unknown. In this paper, the surface deformation time series from 2017 to 2020 is firstly estimated by combining multi-temporal synthetic aperture radar (SAR) interferometry and improved offset-tracking methods to overcome the difficulties caused by the large gradient surface deformation and surface material changes. Then, the spatiotemporal characteristics of Jianshanying landslide is analyzed in terms of line-of-sight (LOS) deformation with stacking InSAR method and two-dimensional (2D) deformation with improved SAR offset-tracking method. And the different deformation features between sliding body and surrounding areas are uncovered. Accordingly, we point out the "three-section" surface deformation model. We further analyze the deformation time series by considering the joint effects of rainfall and underground mining. Finally, we conceptualize the landslide failure mode for the Jianshanying landslide, which can be extended to the similar landslide in karst mountainous areas of southwestern China. [ABSTRACT FROM AUTHOR]

The impoundment of reservoirs in canyons can aggravate the destruction of bank slopes. The Xingguang village landslide is located on the Xiluodu Reservoir in the lower reaches of the Jinsha River. It has deformed continuously since impoundment of the reservoir in 2012, and it seriously threatens the operational safety of the Xiluodu hydropower station. Its temporal and spatial deformation characteristics and its deformation mechanism have not been systematically monitored and explained. In this paper, the movement directions were identified based on the time-series cumulative displacement maps and the landslide is further partitioned into different sections by combining geomorphological data, stratigraphic occurrence, and lithological characteristics. The horizontal and vertical displacement characteristics of the two sections of the Xingguang village landslide were obtained by ascending and descending track interferometric synthetic aperture radar (InSAR) observation results and two-dimensional decomposition functions, and the results were further verified by a field survey and unmanned aerial vehicle (UAV) photography. The results show that the lithologic combination of alternating soft and hard anticline strata and the high steep bank slope cut by the Jinsha River are the internal factors responsible for the development of the Xingguang village landslide. The softening of the strata caused by water storage and the pressure difference caused by water level fluctuations reduce the slope stability. This study provides a new technical path to obtain the direction of landslide movement through time-series cumulative displacement maps and stratigraphic information and then identifies rock toppling in a remote way, which is of great significance for the prevention and control of rocky slope failures in canyon reservoir areas. [ABSTRACT FROM AUTHOR]

When an active landslide is first identified in an artificial reservoir, a comprehensive study has to be quickly conducted to analyse the possible hazard that it may represent to such a critical infrastructure. This paper presents the case of the El Arrecife Landslide, located in a slope of the Rules Reservoir (Southern Spain), as an example of geological and motion data integration for elaborating a preliminary hazard assessment. For this purpose, a field survey was carried out to define the kinematics of the landslide: translational in favour of a specific foliation set, and rotational at the foot of the landslide. A possible failure surface has been proposed, as well as an estimation of the volume of the landslide: 14.7 million m3. At the same time, remote sensing and geophysical techniques were applied to obtain historical displacement rates. A mean subsidence rate of the landslide around 2 cm/year was obtained by means of synthetic aperture radar interferometry (InSAR) and ground-penetrating radar (GPR) data, during the last 5 and 22 years, respectively. The structure-from-motion (SfM) technique provided a rate up to 26 cm/year during the last 14 years of a slag heap located within the foot of the landslide, due to compaction of the anthropical deposits. All of this collected information will be valuable to optimise the planning of future monitoring surveys (i.e. differential global positioning systems, inclinometers, ground drilling, and InSAR) that should be applied in order to prevent further damage on the reservoir and related infrastructures. [ABSTRACT FROM AUTHOR]

Early Warning Systems (EWS) are efficient tools for preventing and mitigating the risks associated to landslides occurrence. In this paper, an integrated methodology for landslides' analysis is presented and described. Such methodology is aimed at the creation of early warning systems and is based on the integration between a modern monitoring technique, such as the Ground-Based Interferometric Synthetic Aperture Radar (GBInSAR), along with advanced numerical modelling. The paper also shows the application of the proposed methodology to the case study of a rockslide in central Italy. The integration between monitoring data, thanks to a GBInSAR survey and advanced numerical simulations with the combined Finite-Discrete Elements Method (FDEM), allowed for the definition of a set of surface velocity thresholds to be adopted for the long-term monitoring of the landslide and for the creation of an effective EWS. [ABSTRACT FROM AUTHOR]

The Zongling landslide (Nayong, Guizhou, China) is dominated by a unique karst landscape area with many landslide masses. In this paper, an improved Interferometric Point Target Analysis (IPTA) method is proposed to identify and monitor the Zongling landslide. In this method, the Anderson-Darling test is applied to distributed scatterer (DS) selection, and DS and persistent scatterer (PS) are combined to improve the density of measurement points in vegetation area. Moreover, this method is also characterized by the appropriate combination of differential interferograms produced by a small baseline subsets and the employment of the phase triangulation algorithm to estimate the optimal phase. Combining 105 scenes of C-band Sentinel-1A ascending and descending data acquired during 2014–2018, the method is applied to retrieve time series displacement for the large-scale landslide in Zongling Town. Finally, three accelerating landslides are identified from our result, which is consistent with ALOS PALSAR differential interferometry synthetic aperture radar (DInSAR) results and field investigation. The influencing factors and deformation mechanism of the Zongling landslide are also analysed. Our monitoring results will help the local government to conduct regular inspections and strengthen disaster prevention in mountain areas. [ABSTRACT FROM AUTHOR]

The focus of this paper is on two large sequential landslides which formed a dam and the resulting lake that occurred along the Jinsha River on October 11 and November 3, 2018. About 24 and 9 × 106 m3 of material failed and rushed into the river, respectively. Both landslides totally blocked the river and induced hazard chains. Four multi-temporal unmanned aerial vehicle (UAV)-based high-resolution images and digital elevation models (DEMs) before and after the landslides were obtained and merged. The initial deformation of the two landslides can be clearly captured by optical remote-sensing images and interferometric synthetic aperture radar (InSAR) analysis. The depth-integrated continuum method was adopted to analyze the dynamic process of both landslides, using the same basal friction angle and cohesion. The computational results matched well with field measurements and observations. It is shown that the evaluation of potentially landslide-prone areas by the depth-integrated continuum method is feasible and is able to provide significant information before a possible event. [ABSTRACT FROM AUTHOR]

On February 14, 2010, a large landslide affected the urban centre of San Fratello town (Sicily Island, Southern Italy), causing severe damage to buildings, roadways, and infrastructure, as well as about 2000 evacuees. This large complex landslide, covering more than 1 km2 in extension, represents one of the major phenomena that ever occurred in Sicily. In order to manage the landslide risk, the civil protection system was activated as part of the initial response to the emergency (the “emergency phase”). This involved the Civil Protection Departments both at national (DPC) and regional (DRPC) levels, as well as scientific institutions (namely “Competence centres”, CdCs), local administration personnel, and technicians. On March 8, 2010, during the post-event recovery phase, a ground-based synthetic aperture radar (GB-InSAR) system was installed in order to monitor the ground surface deformation, assess the landslide residual risk, and analyse its displacement trend. Accurate field surveys and building inspections were also performed for a validation of the GB-InSAR data, in order to map the ground deformation, plan building evacuation-demolishment, as well as check the efficiency of the landslide mitigation works. This paper describes the outcomes of the 57 month monitoring campaign (March 2010–December 2014), reporting the use of GB-InSAR data for near real-time monitoring, mapping, and post-emergency/recovery management activities. The final aim was to provide the civil protection personnel with a reliable, rapid, and easy communication system of the monitoring results, designed to an enhance understanding of the landslide phenomena, and to support the decision-making process. [ABSTRACT FROM AUTHOR]

In this paper, the updating of the landslide inventory of Tuscany region is presented. To achieve this goal, satellite SAR data processed with persistent scatter interferometry (PSI) technique have been used. The updating leads to a consistent reduction of unclassified landslides and to an increasing of active landslides. After the updating, we explored the characteristics of the new inventory, analysing landslide distribution and geomorphological features. Several maps have been elaborated, as sliding index or landslide density map; we also propose a density-area map to highlight areas with different landslide densities and sizes. A frequency-area analysis has been performed, highlighting a classical negative power-law distribution. We also explored landslide frequency for lithology, soil use and several morphological attributes (elevation, slope gradient, slope curvature), considering both all landslides and classified landslide types (flows, falls and slides). [ABSTRACT FROM AUTHOR]

The spatial resolution of digital elevation models (DEMs) is an important factor for reliable landslide studies. Multi-interferometric techniques such as persistent scatterer interferometric synthetic aperture radar (PSInSAR) are used to evaluate the landslide state of activity and its ground deformation velocity, which is commonly measured along the satellite line of sight (LOS). In order to compare velocities measured by different satellites in different periods, their values can be projected along the steepest slope direction, which is the most probable direction of real movement. In order to achieve this result, DEM-derived products are needed. In this paper, the effectiveness of different DEM resolutions was evaluated in order to project ground deformation velocities measured by means of PSInSAR technique in two different case studies in the Messina Province (Sicily, southern Italy): San Fratello and Giampilieri. Three DEMs were used: (i) a 20-m resolution DEM of the Italian Military Geographic Institute (IGM), (ii) a 2-m resolution DEM derived from airborne laser scanning (ALS) light detection and ranging (LiDAR) data for the San Fratello 2010 landslide, and (iii) a 1-m resolution DEM derived from ALS LiDAR data for the area of Giampilieri. The evaluation of the applied method effectiveness was performed by comparing the DEMs elevation with those of each single permanent scatterer (PS) and projecting the measured velocities along the steepest slope direction. Results highlight that the higher DEM resolution is more suitable for this type of analysis; in particular, the PS located nearby the watershed divides is affected by geometrical problems when their velocities are projected along the steepest slope. [ABSTRACT FROM AUTHOR]

Large rocky landslides induced by underground mining are the primary type of geological disaster in the karst mountains of southwestern China. In this study, by integrating field surface surveys, interferometric synthetic aperture radar (InSAR) monitoring, and discrete element simulations, we analyzed the deformation evolution of steep cliffs with karst structural planes under mining disturbance. Based on the stress transfer, deformation response, and instability precursors, a landslide instability model was developed. The results revealed that the instability boundaries and the instability mode were controlled by the large structural plane at the top of the mountain. Underground mining accelerated the uneven subsidence of the overlying strata, which led to expansion and penetration of the karst fissure structural planes and fracturing of the rock base, which are the main reason for the instability of the mountain. Underground mining caused internal stress fluctuation of the overlying strata, and the mountain experienced four stages during this process, i.e., development of karst fissure structural planes, fissures expansion and rock base fracturing, further fissures expansion and rock base crashing, and fissures penetration and shear failure. The mining-induced failure of mountain with large karst structural planes can be described as tensile shear-fracturing crashing failure. The InSAR monitoring results revealed that accelerated deformation occurred in the source area starting 20 days before the Baiyan landslide. In addition, 25 potential deformation landslides were identified in Zhijin County, Guizhou Province. Hence, InSAR technology can be used for early-stage detection and warning of similar landslides. [ABSTRACT FROM AUTHOR]

Persistent scatterer interferometry (PSI) is capable of millimetric measurements of ground deformation phenomena occurring at radar signal reflectors (persistent scatterers, PS) that are phase coherent over a period of time. However, there are also limitations to PSI; significant phase decorrelation can occur between subsequent interferometric radar (InSAR) acquisitions in vegetated and low-density PS areas. Here, artificial amplitude- and phase-stable radar scatterers may have to be introduced. I2GPS was a Galileo project (02/2010-09/2011) that aimed to develop a novel device consisting of a compact active transponder (CAT) with an integrated global positioning system (GPS) antenna to ensure millimetric co-registration and a coherent cross-reference. The advantages are: (1) all advantages of CATs such as small size, light weight, unobtrusiveness and usability with multiple satellites and tracks; (2) absolute calibration for PSI data; (3) high sampling rate of GPS enables detection of abrupt ground motion in 3D; and (4) vertical components of the local velocity field can be derived from single-track InSAR line-of-sight displacements. A field trial was set to test the approach at a potential landslide site in Potoška planina, Slovenia to evaluate the applicability for operational monitoring of natural hazards. Preliminary results from the trial highlight some of the key considerations for operational deployments in the field. Ground motion measurements also allowed an assessment of landslide hazard at the site and demonstrated the synergies between InSAR and GPS measurements for landslide applications. InSAR and GPS measurements were compared to assess the consistency between the methods from the slope mass movement detection aspect. [ABSTRACT FROM AUTHOR]

Landslide hazard mapping is essential for disaster reduction and mitigation. The hazard map produced by the spatiotemporal probability analysis is usually static with false-negative and false-positive errors due to limited data resolution. Here we propose a new method to obtain dynamic landslide hazard maps over the Wushan section of the Three Gorges Reservoir Area by introducing the ground deformation measured by the spaceborne Copernicus Sentinel-1 synthetic aperture radar (SAR) imagery collected from 9/30/2016 to 9/13/2017. We first determine the spatial probability of landslide occurrence predicted by the support vector machine algorithm. We also conducted the statistical analysis on the temporal probability of landslide occurrence under various rainfall conditions (0, 0–50, 50–100, and > 100 mm for the antecedent 5-day total). We initialize a preliminary landslide hazard map by combining the spatial and temporal landslide probabilities. Meanwhile, the ground deformation velocities during the representative dry and wet seasons can be extracted from multi-temporal interferometric SAR (MT-InSAR). Thereafter, the landslide hazard map can be finalized by an empirical assessment matrix considering both the preliminary landslide hazard map and deformation velocities. Our results demonstrate that false-negative and false-positive errors in the landslide hazard map can be effectively reduced with the assistance of the deformation information. Our proposed method can be used to assess the dynamic landslide hazard at higher accuracy. [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]

The objective of this work is to document the deformation pattern of the deep-seated La Clapière landslide for the period 2007-2010 from the combination of L-band synthetic aperture radar (SAR) interferograms, ground-based total station measurements and identification of the slope geomorphological structures. The interferograms are calculated for pairs of ALOS/PALSAR images at a time interval of 46 days. The displacement field derived from the interferograms reveals a non-uniform displacement gradient from the top (subsidence) to the bottom (accumulation). Vertical velocities are calculated from the unwrapped phase values and are in good agreement with ground-based measurements. The results demonstrate the potential of L-band ALOS/PALSAR imagery for the monitoring of active landslides characterized by complex kinematic patterns and by important changes in the soil surface backscattering in time. [ABSTRACT FROM AUTHOR]

A landslide map is the most basic element for any landslide assessment, especially for giant landslides. However, due to remoteness and hazards, it is difficult to know the characteristics of these landslides after great earthquakes. In this study, the Coregistered Single look Slant range Complex(CoSSC) synthetic aperture radar (SAR) data from TerraSAR-X and its twin satellite TanDEM-X are employed to estimate a high-accuracy digital elevation model (DEM) for the giant landslide in Wenjiagou on Feb. 1, 2013, which was one of the biggest landslides triggered by the 2008 Wenchuan great earthquake. Then, compared to the DEM from SRTM, the elevation change can be estimated, and the characteristics of the Wenjiagou landslide, such as the source and deposit area, are highlighted. Based on the estimation of elevation change, the initial and deposit volumes are estimated as 5.09 × 10 m and 4.47 × 10 m respectively which are in agreement with previous field investigations by other researchers. And the results also show that using bistatic space-borne SAR data is an effective means for timely assessment of the giant landslide. [ABSTRACT FROM AUTHOR]

We provide a step-by-step analysis and discussion of the 'PSI-based matrix approach', a methodology employing ground deformation velocities derived through Persistent Scatterer Interferometry (PSI) for the assessment of the state of activity and intensity of extremely to very slow landslides. Two matrices based on PSI data are designed respectively for landslides already mapped in preexisting inventories and for newly identified phenomena. Conversely, a unique intensity scale is proposed indiscriminately for both. Major influencing factors of the approach are brought to light by the application in the 14 km area of Verbicaro, in Northern Calabria (Italy). These include lack of PSI data within the landslide boundaries, temporal coverage of the available estimates, and need of field checks as well as the operative procedures to set the activity and intensity thresholds. For the area of Verbicaro, we exploit 1992-2011 PSI data from ERS1/2 and RADARSAT1/2 satellites, projecting them along the maximum slope directions. An activity threshold of ±5 mm/year is determined by applying the average projection factor of local slopes to the PSI data precision. The intensity threshold between extremely and very slow phenomena (16 mm/year) is reduced by ~20 % to account for temporal and spatial averages being applied to attribute representative velocities to each landslide. The methodology allows assessing the state of activity and the intensity for 13 of the 24 landslides premapped in the 2007 inventory and for two newly identified phenomena. Current limitations due to characteristics and spatial coverage of PSI data are critically tackled within the discussion, jointly with respective implications. [ABSTRACT FROM AUTHOR]