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On June 17, 2020, Aniangzhai landslide, an ancient landslide located in Danba County, southwest China, was reactivated by Meilonggou debris flow. The front edge of the slope collapsed, mobilizing a soil mass of about 2.35 × 106 m3. Evaluating the stability of the whole slope is of great importance to avoid further landslides and mitigate the damage for Aniangzhai villagers living on this slope. This paper focuses on the inaccessible upper slope of Aniangzhai landslide (no attention paid before) that exhibits a relative elevation difference of more than 1000 m. Multi-source remote sensing, including unmanned aerial vehicle (UAV) photogrammetry, light detection and ranging (LiDAR), and satellite-based interferometric synthetic aperture radar (InSAR) techniques, was used in this research to identify and evaluate this high mountain upper slope potential hazard in Aniangzhai landslide. Considering the huge height difference and the steep slope of Aniangzhai landslide, an iterative route planning method was proposed and adopted to obtain a 3D model with 0.02 m resolution and a DEM with 0.25 m resolution by using UAV and LiDAR close-in flight method, respectively. Meter-level huge cracks were clearly identified by the high-resolution UAV 3D model and LiDAR data, which confirm that the location of these cracks is related to the morphological structure of this ancient landslide. Time series InSAR analysis reveals the activity of this high-altitude area, with a maximum LOS displacement rate of 15 cm/a. The combination of the above remote sensing technologies confirms and reveals the high potential risk and the reactivated condition of the upper slope of Aniangzhai landslide. Through this finding, we show that the evolution of Aniangzhai landslide happened through four stages with a cascading effect. This paper proves the usefulness of an integrated method to successfully identify and evaluate the high-altitude upper slope potential hazard and compares the technical features of them, providing a reference for future works that aimed at mitigating the potential damage of the upper slope. [ABSTRACT FROM AUTHOR]

The reactivation of ancient landslides, a persistent issue that hinders urban development and threatens human safety, is the central focus of this paper. Specifically, this paper offers a detailed description and analysis of an ancient landslide that reactivated on February 26, 2021, in Guoye town, Zhouqu County, Gansu Province, China, and has remained slow-moving since then. With a volume of approximately 21.2 million m3 of rock and soil masses involved, this landslide poses a significant risk to the safety of 1119 individuals from 282 households in Moli village and Guoye village. A combination of field investigations, remote sensing interpretation, in situ monitoring, and interferometric synthetic aperture radar (InSAR) was used to investigate the landslide characteristics and reactivation mechanisms. The results revealed that the presence of sliding-prone rock formations and tectonic movement were the primary contributors to the formation of the Moli landslide. Furthermore, the accumulation of bedrock blocks in the quarry and collapsed rock masses caused by fault activity at the rear parts, along with the additional load from buildings on the middle and rear sections, increased the sliding force. Simultaneously, the erosion of the Dashuiba River resulted in a reduction in the anti-slip force, thereby directly facilitating landslide reactivation. The notable increase in annual rainfall in recent years has played a crucial role in ancient landslide reactivation by elevating the groundwater level and softening the shear strength of the sliding zone soil. The findings of this study contribute to an enhanced understanding of the reactivation mechanisms in giant, ancient landslides situated within areas characterized by highly complex geological conditions. [ABSTRACT FROM AUTHOR]

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]

Slow-moving landslide-prone areas (SLAs) are unstable objects on the terrestrial surface that can collapse rapidly when provoked by earthquakes, leading to infrastructure damage. It is critical to identify SLAs prior to earthquake events and assess their hazard-causing probabilities when triggered. An assessment approach of earthquake-triggered geohazards is proposed in this paper by combining interferometric synthetic aperture radar (InSAR) derived SLAs and geological and geomorphological factors. Taking the Ms6.8 Luding earthquake, which occurred in the Sichuan Province of southwestern China on September 5, 2022, as an example, 1320 scenes of Sentinel-1 SAR data in western Sichuan were processed using the small baseline subset (SBAS) InSAR technique before the earthquake. After the earthquake, hazard probability assessment was performed in real-time by filtering the SLAs using a spatial analysis technique with geological and geomorphological factors, e.g., real-time peak ground acceleration (PGA), slope, distance to fault (DTF), and distance to the river (DTR) data. The results show that 11 SLAs were classified into high-risk zones. As verified by the Luding co-seismic landslide dataset from visual interpretation of optical remote sensing images, 142 coseismic landslides were triggered by the earthquake in these high-risk regions. In these areas, an ancient landslide, with high pre-earthquake displacement rates (−50 mm/year) on the scarp was reactivated under the Luding earthquake forces. This method can provide a scientific tool for disaster mitigation and rapid response emergency management. [ABSTRACT FROM AUTHOR]

An updated and complete landslide inventory is the starting point for an appropriate hazard assessment. This paper presents an improvement for landslide mapping by integrating data from two well-consolidated techniques: Differential Synthetic Aperture Radar (DInSAR) and Landscape Analysis through the normalised channel steepness index (ksn). The southwestern sector of the Sierra Nevada mountain range (Southern Spain) was selected as the case study. We first propose the double normalised steepness (ksnn) index, derived from the ksn index, to remove the active tectonics signal. The obtained ksnn anomalies (or knickzones) along rivers and the unstable ground areas from the DInSAR analysis rapidly highlighted the slopes of interest. Thus, we provided a new inventory of 28 landslides that implies an increase in the area affected by landslides compared with the previous mapping: 33.5% in the present study vs. 14.5% in the Spanish Land Movements Database. The two main typologies of identified landslides are Deep-Seated Gravitational Slope Deformations (DGSDs) and rockslides, with the prevalence of large DGSDs in Sierra Nevada being first revealed in this work. We also demonstrate that the combination of DInSAR and Landscape Analysis could overcome the limitations of each method for landslide detection. They also supported us in dealing with difficulties in recognising this type of landslides due to their poorly defined boundaries, a homogeneous lithology and the imprint of glacial and periglacial processes. Finally, a preliminary hazard perspective of these landslides was outlined. [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]

Interferometric synthetic aperture radar (InSAR) has gained considerable attention as a landslide monitoring strategy owing to its high accuracy, large coverage, and relatively low associated costs. A crucial drawback of InSAR, however, has limited its further incorporation: one-dimensional estimations along the sensor's line-of-sight (LOS). This leads to an ambiguity in results and a less intuitive understanding of landslide kinematics. A frequently exercised approach to address this issue has been taking inspiration from the topography to establish compatibility assumptions between velocity components, yet little insight exists on the performance of these methods. The objective of this paper is to investigate the performance of four renowned topography-based methods—Surface Parallel Flow Model (SPFM), SPFM coupled with least-squares method (SPF-LSM), Aspect Parallel Flow Model (APFM), and Steepest Terrain Following Model (STFM)—in evaluating the magnitude and geometry of total velocity vectors. To this end, the analysis is performed on 202 Radarsat-2 and 243 Sentinel-1 scenes acquired over a section of the Thompson River valley, a critical railway corridor in Western Canada traversing 14 landslides. The results indicate that the APFM provides estimations with the lowest magnitude error (15–19 mm/yr or 18.75–23.75% of in situ measurements) compared to the other approaches. SPFM and SPF-LSM are highly sensitive to LOS variance and tend to bias the interpreted vectors toward the north orientation. However, APFM and STFM reflect more realistic aspect angles, with the former inclined to steeper travel angles and the latter suffering from erratic upward travel angles due to local topographies. [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]

On June 25, 2020, Jinweng Co in Yiga, Tibet, experienced an outburst flood that resulted in catastrophic damage to farmland and roads. The complex causal factors for glacial lake outburst flooding (GLOF) are not fully understood. This paper provides a systematic analysis of the contributing factors leading to the GLOF disaster in terms of meteorological triggering, glacial activity, lake expansion, landslide, and glacial collapse. The analysis is based on multi-source remote sensing approaches. Pixel offset tracking of Sentinel-1 images shows changes in the glacier flow velocity from 2017 to 2020. Sentinel-2 and Landsat-8 images and inventory data have revealed the expansion of the lake since 1998. The satellite precipitation measurements revealed that the highest daily rainfall in recent years occurred approximately 4 days before the GLOF. Time series synthetic aperture radar (SAR) backscattering images and interferograms suggest that a landslide had occurred from the western lateral moraine into the lake. Additionally, SAR images suggest possible ice collapse from the glacier tongue into the lake. The causal mechanism for the June 2020 GLOF event was likely the dam failure triggered by heavy rainfall and combined with landslides and ice collapses. Our research can provide a reference to identify and mitigate glacial lake outburst disasters in mountainous regions based on satellite optical and radar images. [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 paper presents a multi-source approach tailored for the analysis of ground movements affecting the village of Barberà de la Conca (Tarragona, Catalonia, Spain), where cracks on the ground and damage of different severity to structures and infrastructure was recorded. For this purpose, monitoring of ground displacements performed by topographic survey, geotechnical monitoring and remote sensing techniques (ground-based synthetic aperture radar, GBSAR) are combined with multi-temporal damage surveys and monitoring of cracks (crackmeters) to get an insight into the kinematics of the urban slope. The obtained results highlight the correspondence between the monitoring data and the effects on the exposed facilities induced by ground displacements, which seem to occur predominantly in the horizontal plane with diverging directions (northward and southward) from the main ground fracture crossing the centre of the village. The case study stands as a further contribution to fostering this kind of integrated approaches that via cross-validations can improve data reliability as well as enrich datasets for slope instability recognition and analysis, which are crucial to plan risk mitigation works. [ABSTRACT FROM AUTHOR]

Statistical analyses have been often used for landslide susceptibility zoning at small to medium scale when relevant base and thematic maps are available. Since the beginning of the last decade, images remotely acquired by spaceborne Synthetic Aperture Radar (SAR) and processed via Differential SAR Interferometry (DInSAR) proved extremely useful for non-invasive and non-destructive monitoring of displacements of the topographic surface. The present paper proposes an original procedure for the definition of the state of activity of slow-moving landslides via the combined use of multivariate statistical analyses and DInSAR data. The procedure is based on the following essential elements: distinction between terrain units used for computational purposes and the final zoning units; independent statistical and DInSAR analyses and activity models leading to first-level state of activity zoning maps; a consistency model between statistical and DInSAR analyses; two confidence and combination models leading, respectively, to second- or third-level state of activity zoning maps. The application in a test area including 19 municipalities in southern Italy, where slow-moving landslides are widespread and accurately mapped by using geomorphological criteria, allowed the generation of the three above-mentioned levels of zoning maps. The results were successfully crosschecked by exploiting a different DInSAR dataset and the results of previous works based on the use of slow-moving landslide-induced damage to facilities surveys. [ABSTRACT FROM AUTHOR]

In this paper, a systematic procedure to assess the feasibility of Advanced Differential Interferometric SAR (A-DInSAR) technique for landslide monitoring using SAR images acquired by Sentinel-1 sensors is presented. The methodology is named "Assessment of the advanced differentiaL interferometric synthetic aperture radar technique Feasibility for large scale lAndslide monitoring – ALFA" and it is structured in two main phases, which includes pre-processing and post-processing elaborations. The methodology was developed and tested in the Alpine sector of the Piedmont region in Italy, which represents a landslide prone area. In particular, ALFA represents a methodology based on previous algorithms available in the literature to assess the a-prior feasibility assessment and post-processing analysis of A-DInSAR data for landslide, which introduces three novel aspects such as (1) a systematic scheme suitable within regional practices; (2) the use of Sentinel-1 data and the development of (3) an index to take into account of the kind of distribution of the measuring points along the landslide. The approach was applied over an area extended about 5300 km2 affected by 5703 landslides mapped in the database of the Piedmont Region (Landslides information system in Piedmont—SIFRAP). Sentinel-1 images covering the period 2014–2018 were analysed. The results show the potential of the Sentinel-1 data for large-scale landslide monitoring. The developed methodology presents reliable tools that could be useful as feasibility for the use of Sentinel-1 data for landslide monitoring at regional and national scale. [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]

As a member of the International Consortium on Landslides, the University of Alberta is actively working to improve technologies for monitoring natural hazards. Though ground-based, interferometric, synthetic aperture radar (GB-InSAR) has been successfully implemented for near real-time monitoring of natural and man-made slopes, it has seen limited use in Canada outside of the mining industry. This lack of adoption in the rural areas of Canada is due to difficulties associated with providing continuous power to remote sites, other logistical challenges, and concerns with the impact of snow cover on the data collected. This paper presents the results of a project to install a GB-InSAR system to monitor a 2 to 3 million m3 bedrock landslide with a measured average rate of displacement of ~ 10 mm/year. The site is characterized by long periods of deep snow cover, cold temperatures, no connection to the electrical grid, and a location within a steep valley that limits hours of daylight for solar power. Challenges with, and solutions developed for, the deployment of GB-InSAR equipment at this site are described, and the results of the monitoring program are validated with existing geotechnical instrumentation. [ABSTRACT FROM AUTHOR]

Rockfalls are a recurrent cause of disruption for transportation corridors running along the bottom of U-shaped alpine valleys. In some scenarios, risk may effectively be reduced only by implementing an early-warning system able to give notice of incipient failures on the slope. This paper describes a successful example of rockfall forecasting and risk management in proximity of the Gallivaggio sanctuary (San Giacomo Valley, Central Italian Alps). Since 2016, a Ground-Based Synthetic Aperture Radar continuously monitored a roughly 500-m high, sub-vertical granitic slope. Monitoring data evidenced the presence and continued movement of a ~ 5000 m3 highly unstable mass, having a projected fall trajectory directly threatening the sanctuary and the adjacent segment of a national road. Traffic and access to the sanctuary were regulated by a sequence of alert thresholds, and restrictive orders were issued according to the activity of the instability. The rock mass eventually fell, and the failure-time was accurately predicted several hours in advance. Despite damage to both the road and buildings, the timely evacuation of the area prevented any loss of life. The case study provides a reference framework to better manage rockfall risk in areas where the installation of adequate protective barriers is not technically feasible. [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]

Timely and effective post-disaster assessment is of significance for the design of rescue plan, taking disaster mitigation measures and disaster analysis. Field investigation and remote sensing methods are the common ways to perform post-disaster assessment, which are usually limited by dense cloud coverage, potential risk, and tough transportation etc. in the mountainous area. In this paper, we employ the 2017 catastrophic Xinmo landslide (Sichuan, China) to demonstrate the feasibility of using spaceborne synthetic aperture radar (SAR) data to perform timely and effective post-disaster assessment. With C-band Sentinel-1 data, we propose to combine interferometric coherence to recognize the stable area, which helps us successfully identify landslide source area and boundaries in a space-based remote sensing way. Complementarily, X-band TanDEM-X SAR data allow us to generate a precise pre-failure high-resolution digital elevation model (DEM), which provides us the ability to accurately estimate the depletion volume and accumulation volume of Xinmo landslide. The results prove that spaceborne SAR can provide a quick, valuable, and unique assistance for post-disaster assessment of landslides from a space remote sensing way. At some conditions (bad weather, clouds, etc.), it can provide reliable alternative. [ABSTRACT FROM AUTHOR]

Two successive landslides within a month started in October 11, 2018, and dammed twice the Jinsha River at the border between Sichuan Province and Tibet in China. Both events had potential to cause catastrophic flooding that would have disrupted lives of millions and induced significant economic losses. Fortunately, prompt action by local authorities supported by the deployment of a real-time landslide early warning system allowed for quick and safe construction of a spillway to drain the dammed lake. It averted the worst scenario without loss of life and property at least one order of magnitude less to what would have been observed without quick intervention. Particularly, the early warning system was able to predict the second large-scale slope failure 24 h in advance, along with minor rock falls during the spillway construction, avoiding false alerts. This paper presents the main characteristics of both slope collapses and damming processes, and introduces the successful landslide early warning system. Furthermore, we found that the slope endured cumulative creeping displacements of > 40 m in the past decade before the first event. Twenty-five meter displacement occurred in the year immediately before. The deformation was measured by the visual interpretation of multitemporal satellite images, which agrees with the interferometry synthetic aperture radar (InSAR) measurement. If these had been done before the emergency, economic losses could have been reduced further. Therefore, our findings strengthen the case for the deployment of systematic monitoring of potential landslide sites by integrating earth observation methods (i.e., multitemporal satellite or UAV images) and in situ monitoring system as a way to reduce risk. It is expected that this success story can be replicated worldwide, contributing to make our society more resilient to landslide events. [ABSTRACT FROM AUTHOR]

Large landslides and deep-seated gravitational slope deformations (DSGSD) represent an important geo-hazard in relation to the deformation of large structures and infrastructures and to the associated secondary landslides. DSGSD movements, although slow (from a few millimetres to several centimetres per year), can continue for very long periods, producing large cumulative displacements and undergoing partial or complete reactivation. Therefore, it is important to map the activity of such phenomena at a regional scale. Ground surface displacements at DSGSD typically range close to the detection limit of monitoring equipment but are suitable for synthetic aperture radar (SAR) interferometry. In this paper, permanent scatterers (PSInSAR™) and SqueeSAR™ techniques are used to analyse the activity of 133 DSGSD, in the Central Italian Alps. Statistical indicators for assigning a degree of activity to slope movements from displacement rates are discussed together with methods for analysing the movement and activity distribution within each landslide. In order to assess if a landslide is active or not, with a certain degree of reliability, three indicators are considered as optimal: the mean displacement rate, the activity index (ratio of active PS, displacement rate larger than standard deviation, overall PS) and the nearest neighbor ratio, which allows to describe the degree of clustering of the PS data. According to these criteria, 66% of the phenomena are classified as active in the monitored period 1992-2009. Finally, a new methodology for the use of SAR interferometry data to attain a classification of landslide kinematic behaviour is presented. This methodology is based on the interpretation of longitudinal ground surface displacement rate profiles in the light of numerical simulations of simplified failure geometries. The most common kinematic behaviour is rotational, amounting to 41 DSGSDs, corresponding to the 62.1% of the active phenomena. [ABSTRACT FROM AUTHOR]

The Thompson River valley, south of Ashcroft in British Columbia, Canada, has experienced several landslides since the mid-1800s. The national railways that run along the valley cross a number of these landslides. All the landslides occur in glacial deposits, typically sliding on weak clay layers. Some have failed rapidly to very rapidly and are currently inactive or showing deformation rates from a few millimeters to centimeters per year. An evaluation of satellite InSAR (Interferometric Synthetic Aperture Radar) using RADARSAT-2 images between September 2013 and November 2015 provides new insight into landslide displacements in the Thompson River valley. This information enhances the ongoing hazard management of unstable terrain. This paper presents the comparison of the InSAR measurements with other instrumentation (GPS and ShapeAccelArrays™ -SAA) installed at one moving landslide and then addresses the extent and magnitude of the slope movements observed. InSAR was found to provide similar displacement values to those measured otherwise. The stable location showed displacements of +/−1 mm with an average near zero during the whole monitoring period. Six areas of slope movement were identified within the study area, all within or adjacent to the footprints of past landslides. The average line of sight (LOS) displacement rates range between 11 and 39 mm/year. Most of the landslides exhibited seasonal variations in velocity that corresponds to changes in river elevation in the valley. [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]

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]

Landslides are the fourth most common natural disasters in the world, with Costa Rica and southern Mexico being the most affected regions of Central America (Froude and Petley, 2018). In this work, we propose a semi-automated method to detect earthquake-triggered landslides for rapid mapping after a disaster event using open Sentinel-1 data. We used high-resolution TerraSAR-X data and very high-resolution Spot-7 images to compare and evaluate the accuracy of landslide distribution maps generated from the semi-automated method, applied to the M 7.1 earthquake on June 23, 2017, in Oaxaca, Mexico. The outcomes showed better accuracy in descending orbits due to 'windward-leeward' physiographic conditions, with a 50.56% quality percentage. This shows a reasonably good capacity to detect co-seismic landslides. However, the breaching factor was also high because several features, such as bare soils and agricultural areas, were incorrectly identified as co-seismic landslides. Finally, this semi-automated method establishes a basis for future improvements in methodologies applied to construct rapid mapping inventories using medium SAR scales. [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]

Interferometric Synthetic Aperture Radar (InSAR) has been increasingly used in landslide detection over wide areas. However, atmospheric delays, phase unwrapping errors, and noise, which behave like deformation signals in InSAR deformation results, pose a challenge for semi-automatic and automatic landslide detection. C-index can assistant in landslide interpretation by assessing the rationality of InSAR deformation and filtering out non-real landslide deformation signals. Yet, few studies have analyzed its applicability in identifying landslide from InSAR results. In this study, we develop a method that uses C-index to assist in landslide detection using InSAR. We validate our method in a selected region of the Jinsha River basin, China. We first using multi-temporal InSAR (MT-InSAR) to obtain the deformation rate of the study area. Sixty-nine and 47 suspicious slope deformation areas are extracted from the ascending and descending deformation results, respectively. Next, C-index is used to automatically exclude 28 and 12 false deformation areas from the ascending and descending InSAR results, respectively. Remarkably, all the excluded false deformation areas do not correspond to landslides, suggesting the reliability of the proposed method. Finally, by visually interpreting the optical images of the remaining deformation results, we successfully detect 54 landslides. Among these, 9 landslides can be detected by both the ascending and descending Sentinel-1 data, and 15 landslides are located on the riverbanks, posing a potential risk of river blockage in the event of failure. The presented landslide detection method effectively filters out false deformation areas, ultimately enhancing the efficiency and accuracy of landslide detection over wide areas using InSAR. [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]

Ground-based synthetic aperture radar (GB-SAR) has been widely used in the safety monitoring of slopes, dams, and buildings due to its high precision, large coverage area, and fast image acquisition. The real-time processing of high frequency and continuous deformation monitoring data is particularly important for early warning of landslides and high-risk buildings. Yet very limited studies have been conducted on the real-time processing method of GB-SAR monitoring data. In this study, a novel real-time processing method of GB-SAR monitoring data is proposed by using the Kalman filter based on the permanent scatterer (PS) network. The proposed method starts from the radiation characteristic and the phase composition of the GB-SAR monitoring data and instantaneously processes the acquired radar image by using the dynamic Kalman filter based on PSs and PS network. Then, a real-time processing Kalman mathematical model can be established, the model parameters are initialized, and the recursive Kalman filter to solve the timely deformation monitoring. By continuously updating the image data, the real-time and high-efficient calculation of PS deformation parameters can be achieved, which realizes the high accuracy and continuous deformation monitoring. The proposed novel method fills the gap in the real-time processing techniques of GB-SAR monitoring data and solves key problems of PS network updating, phase unwrapping, atmospheric phase correction, deformation calculation, etc. [ABSTRACT FROM AUTHOR]

Slope instability arisen along with dam construction is a common problem of great concern in reservoir areas. Thus, displacement monitoring of active slopes is of great importance for the safety of dam operation. The unstable Guobu slope is located only about 1.5 km away from Laxiwa hydropower station in upstream Yellow River. In this study, Synthetic Aperture Radar (SAR) datasets acquired by C-band Environmental Satellite (ENVISAT) Advanced Synthetic Aperture Radar (ASAR), L-band Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar 2 (PALSAR-2), and X-band TerraSAR-X covering different evolution stages of Guobu slope were collected to investigate the displacement history so as to facilitate understanding of its deformation and failure mechanisms. The displacements occurred during the past decade were quantitatively identified for the first time by SAR pixel offset tracking analyses. The results show that before the reservoir impoundment, the maximum accumulative displacements on the slope were more than 7 m from 2003 to 2008, while the post-impoundment displacements also exceeded 7 m in just 1 year from September 2009 to September 2010. Furthermore, this slope is still in active deformation up to now. Nevertheless, the displacement rates seem decreased recently according to the interferometric results of TerraSAR-X data pairs from September 2015 to March 2016. [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]

The redaction of landslide inventory is a fundamental task for risk management and territorial planning activities. The availability of synthetic aperture radar imagery, especially after the launch of Sentinel-1 mission, enables to systematically update landslide inventories covering wide areas in a reduced time frame and at different scales of analysis. In this work, SAR data processed from the fully automatic P-SBAS pipeline have been adopted to update the Italian national landslide database. Specifically, a matrix has been introduced by comparing past landslide state of activity obtained with Envisat data (2003–2010) and that computed with Sentinel-1 (2014–2018). The state of activity was defined by obtaining the projected velocity along the slope dip direction. The analysis involved about 56,000 landslides which showed at least one Sentinel-1 measurement point, of which 74% were classified as dormant, having annual average velocity < 7 mm/year (considering a value of two times the standard deviation) and 26% as active (mean velocity > 7 mm/year). Furthermore, a landslide reliability matrix was introduced on the landslide inventory updated with S1 data, using the measurement point (MP) density within each landslide and the standard deviation of the mean Vslope value of each landslide. In this case, the analysis revealed that more than 80% of landslides has values of reliability from average to very high. Finally, the 2D horizontal and vertical components were computed to characterize magnitude and direction of every type of landslides included in this work, showing that spreadings, deep-seated gravitation slope deformations, and slow flows showed a main horizontal movement, while complex and translational/rotational slides had more heterogeneity in terms of deformation direction. Hence, the work demonstrated that the application of fast and automatically nationwide Sentinel-1 MTInSAR (multi-temporal interferometry SAR) may provide a fundamental aid for landslide inventory update. [ABSTRACT FROM AUTHOR]

Spaceborne interferometric synthetic aperture radar has been proven to be able to monitor slow deforming landslides with mm-precision. Continental- and nationwide-scale Sentinel-1 PSI (persistent scatterer interferometry) datasets with millions of deformation time series are publicly available, e.g., via the European Ground Motion Service or the Ground Motion Service Germany. This creates the possibility for an increased routine use of PSI for landslide applications. However, the use of PSI datasets is often done by visual inspection. The huge amount of measurements makes visual inspection, subjective, time-consuming, and error prone due to outliers. This study demonstrates how spatial and temporal patterns of the PSI velocity and time series can be detected in a semi-automatic way to improve objective information extraction. Therefore, two landslides, namely, Trittenheim and Piesport landslides, in Germany are analyzed using Sentinel-1 PSI datasets from the Ground Motion Service Germany. The post-processing technique semi-automatically detects spatial clusters of deforming PS with a maximum LoS velocity of 18 and 7 mm/a in Trittenheim and Piesport landslides, respectively. Furthermore, a correlation and time-lag between the surface deformation and a potential triggering factor is found. Results show that an increase in climatic water balance accelerates landslide deformation at the investigated locations. Results are verified by a second independent Sentinel-1 PSI dataset from the Ground Motion Service Germany. [ABSTRACT FROM AUTHOR]

Fifty-five descending images from the ENVISAT satellite were processed using the small baseline subset (SBAS) method to derive the spatial and temporal ground deformation of the Bailong River Basin between 2003 and 2010. The basin is one of the most severely landslide- and debris flow-affected areas of China. As a result, 104 sites with high deformation areas were identified. Interferometric Synthetic Aperture Radar (InSAR) analysis was combined with landslide inventory data and field surveys, and anomalous areas were classified into three main types: landslide; debris; and subsidence. Displacement rates up to 35 mm/yr were evaluated away from the sensor along a line-of-sight (LOS) direction. The results gained should allow a more accurate prediction and monitoring of landslides, debris, and subsidence; further, they demonstrate the capability of the SBAS method to analyze any displacement effect and identify dangerous and uninhabitable areas in the basin. The small baseline subset method can thus contribute to the prediction and prevention of geohazards in the area. [ABSTRACT FROM AUTHOR]

Slow-moving landslides move downslope at velocities that range from mm year−1 to m year−1. Such deformations can be measured using satellite-based synthetic aperture radar interferometry (InSAR). We developed a new method to systematically detect and quantify accelerations and decelerations of slowly deforming areas using InSAR displacement time series. The displacement time series are filtered using an outlier detector and subsequently piecewise linear functions are fitted to identify changes in the displacement rate (i.e., accelerations or decelerations). Grouped accelerations and decelerations are inventoried as indicators of potential unstable areas. We tested and refined our new method using a high-quality dataset from the Mud Creek landslide, CA, USA. Our method detects accelerations and decelerations that coincide with those previously detected by manual examination. Second, we tested our method in the region around the Mazar dam and reservoir in Southeast Ecuador, where the time series data were of considerably lower quality. We detected accelerations and decelerations occurring during the entire study period near and upslope of the reservoir. Application of our method results in a wealth of information on the dynamics of the surface displacement of hillslopes and provides an objective way to identify changes in displacement rates. The displacement rates, their spatial variation, and the timing of accelerations and decelerations can be used to study the physical behavior of a slow-moving slope or for regional hazard assessment by linking the timing of changes in displacement rates to landslide causal and triggering factors. [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]

According to local villagers, the main Beiguo landslide on the Heyang Loess Tableland in China occurred several decades ago (the specific time is unknown). After the initial occurrence of the main landslide, there was no major activity for several decades until December 17–22, 2017 (2 months after the rainy season), when the main landslide was completely reactivated. One of the interesting findings of our field survey is that there are two erosion gullies and numerous loess caves (groups) developed at the top of the Beiguo landslide, which are generally considered to be the dominant channels by which rainwater or surface runoff enters the deep underground space. In order to better understand the process and triggering factors of the main landslide's reactivation, a multidisciplinary investigation including satellite remote sensing, interferometric synthetic aperture radar (InSAR), an unmanned aerial vehicle (UAV) survey, a terrestrial laser scanning (TLS) survey, an electrical resistivity tomography (ERT) survey, laboratory experiments, real-time monitoring using an inclinometer, and field investigations of the Beiguo landslide was conducted. We believe that the reactivation of the main Beiguo landslide may have been occurring for more than 10 years, or perhaps even longer. Since 2011, there have been several signs of local activity in the main landslide body, and the last accelerated stage of the entire deformation process occurred in 2017. The development and existence of loess caves directly destroyed the stability of the slope, and the rainfall and surface runoff quickly entered the interior of the main landslide. The influence of the loess caves on the landslide's reactivation was long-term and continuous. The results of this study suggest that the several days of abundant and continuous rainfall in the rainy season in 2017 were the last direct trigger of the final reactivation of the main landslide. The secondary landslide significantly changed the original slope, including the aspect of the slope profile's morphology, the slope gradient, relief, erosion, and accumulation, which accelerated the evolution of the tableland landform. This study enhances our understanding of the reactivation behavior of loess landslides, and also provides important support for the monitoring and prevention of reactivated landslides in the future. [ABSTRACT FROM AUTHOR]

Information about the long-term spatiotemporal evolution of landslides can improve our understanding of the landslide development process and can help prevent landslide disasters. However, few studies have been devoted to the pre- and post-failure spatiotemporal evolution process and pattern of landslides. Therefore, we studied the pre- and post-failure geomorphic changes and spatiotemporal evolution of the 2019 Jiangou landslide based on field investigations, interferometric synthetic aperture radar (InSAR), unmanned aerial vehicle (UAV) observations, and remote sensing techniques. The results show that the volume of the deposition of the Jiangou landslide is less than the depletion volume, which means the remaining landslide materials were washed away when the dammed lake collapsed. Moreover, the InSAR technique has an advantage in terms of the retrieval of pre- and post-failure creep deformation. Our analysis suggests that the Jiangou landslide has experienced long-term creep. Potential landslide risks still exist after the previous failure event. Furthermore, we found that the pre- and post-failure spatiotemporal deformation processes and evolutionary patterns of the landslide are different. The pre-failure evolutionary pattern of the landslide is a progressive failure mode, while the post-failure evolutionary pattern is a retrogressive failure mode. This evolution provides a reference for local governments to further monitor or take effective prevention measures against future landslide failures. [ABSTRACT FROM AUTHOR]

Interferometric Synthetic Aperture Radar (InSAR) enables detailed investigation of surface landslide movements, but it cannot provide information about subsurface structures. In this work, InSAR measurements were integrated with seismic noise in situ measurements to analyse both the surface and subsurface characteristics of a complex slow-moving landslide exhibiting multiple failure surfaces. The landslide body involves a town of around 6000 inhabitants, Villa de la Independencia (Bolivia), where extensive damages to buildings have been observed. To investigate the spatial-temporal characteristics of the landslide motion, Sentinel-1 displacement time series from October 2014 to December 2019 were produced. A new geometric inversion method is proposed to determine the best-fit sliding direction and inclination of the landslide. Our results indicate that the landslide is featured by a compound movement where three different blocks slide. This is further evidenced by seismic noise measurements which identified that the different dynamic characteristics of the three sub-blocks were possibly due to the different properties of shallow and deep slip surfaces. Determination of the slip surface depths allows for estimating the overall landslide volume (9.18 · 107 m3). Furthermore, Sentinel-1 time series show that the landslide movements manifest substantial accelerations in early 2018 and 2019, coinciding with increased precipitations in the late rainy season which are identified as the most likely triggers of the observed accelerations. This study showcases the potential of integrating InSAR and seismic noise techniques to understand the landslide mechanism from ground to subsurface. [ABSTRACT FROM AUTHOR]

Landslides, as a representative geohazard in fault zones, threaten the safety of buildings and infrastructure. Landslide movements are often subject to multiple loads in urbanized hillslopes from both natural and human activity. Synthetic aperture radar interferometry (InSAR) has been used to measure landslide movements. Used independently, InSAR can measure only surface deformation, and the points are sparse. Numerical modeling can simulate the full-scale movements, but it requires a prior knowledge of soil properties that are often not available in practice. To address these limitations, we proposed to couple InSAR and numerical modeling for characterizing landslide movements under multiple loads. We used 60 ascending and 56 descending Sentinel-1 images to measure surface movements in urbanized Daguan County Town. Of 31 landslides in the inventory map, 24 were successfully identified. The InSAR results assisted in determining the optimal soil properties through back-analysis. We used geological, geotechnical, and meteorological data to set three boundary conditions, that is, body loads, precipitation-induced hydraulic conditions, and construction-induced forces. Landslide mobility was demonstrated more distinctly using the coupled analysis. The numerical results revealed that body loads dominated the cumulative downslope movements by squeezing water and air from voids, and precipitation caused seasonal movements with the direction perpendicular to the slope surface. Construction works caused permanent changes (accelerating and decelerating) in time-series trends. Coupling InSAR and numerical modeling can facilitate analysis of the effects of complex loads and potentially predict future deformation. The method developed can be extended to study other urbanized landslide areas for early warning and risk mitigation. [ABSTRACT FROM AUTHOR]

Loess landslides are a severe engineering geological problem on the Loess Plateau of China. This study relies on interferometric synthetic aperture radar (InSAR) and unmanned aerial vehicle (UAV) photogrammetry techniques to characterise a large-scale loess landslide deformation process in Northwest China. First, a total of 85 Sentinel-1 SAR images acquired from March 2015 to March 2019 were used to detect the spatial displacement and characterise the pattern of deformation from presliding to postsliding. Second, three UAV flight surveys were conducted to reconstruct landslide morphology, identify scarps, cracks and fissures; and generate elevation differences. By comparing these two technologies, we found that InSAR has more advantages in the retrieval of creeping deformation, while UAV data is valuable for detecting large sudden slides. Dynamic deformation zonation maps were generated based on comprehensive analysis, and the deformation pattern of the large loess landslide was deduced. The Hongheyan landslide was induced by heavy rainfall and then gradually became suspended owing to the topography effect. Recently, the western part of the slope showed a clear accelerating trend. This evolution provides comprehensive kinematic information for local governments to make further intensive observations or take effective precautions. [ABSTRACT FROM AUTHOR]

New radar satellites provide global coverage and the possibility of long-term, regular frequency (days-weeks) surface displacement measurements through the application of high precision multi-temporal InSAR (Synthetic Aperture Radar Interferometry) techniques. This represents an excellent opportunity to investigate and improve our understanding of the behavior of extremely slow landslides, as well as of the long- to short-term controls of their activity. In urban settings, such landslides deserve special attention, as their cumulative movements can cause significant socio-economic damage. Here, we re-examine the case of a long-lived, deep-seated landslide in the Apennine Mountains (Italy) which was urbanized between the late 1970s and early 2000s. The case provides a rare opportunity to highlight the benefits of the integrated analysis of long-term (several years) borehole inclinometer measurements with 15 years of multi-temporal InSAR displacement data. We present evidence of the landslide composite nature and asymmetry, and draw attention to the recent period of accelerated movement that coincided with the foot failure event. This helps constraining the interpretation of the borehole and InSAR data and demonstrating the predominantly rotational landslide mechanism. We show how a detailed analysis of sparse inclinometer and more spatially continuous InSAR measurements, when combined with local rainfall records, can reveal long- to short-term patterns of temporal variability in landslide motions and allow anticipating the consequences of future landslide activity. [ABSTRACT FROM AUTHOR]

Ridge-top rockslides frequently cause huge property losses and casualties due to the difficulties involved in detecting their precursors by means of manual surveys. Their early identification and the surrounding area's evaluation in terms of potential danger are essential for preventing disasters. The recent large rockslide which occurred at Su Village, which is in possession of data related to pre-failure images, real-time video, and post-failure boreholes, is helpful for providing new insights into the processes associated with these events. Due to a strong sustained rainfall, a large volume of granite blocks rapidly descended from the upper part of the hillside, causing 27 deaths and destroying more than 20 houses. It is found that the early identification of the hazard associated with such rockfalls can be made by the analysis of remote sensing images and Persistent Scatterer Interferometry (PSI) analysis of Synthetic Aperture Radar (SAR) data. The depth-integrated continuum method, including taking the entrainment effect into account, was adopted to analyze the dynamic processes and to identify the areas at risk. The computational results show that the evaluated runout distance and extent match well with the field investigation results. The parameter sensitivity surrounding cohesion, coefficients of lateral earth pressure, and volume amplification were analyzed. It is demonstrated that the cohesion plays a significant role in the dynamic processes and the deposited area. However, the effects from the earth pressure coefficient and volume bulking are comparatively weaker. [ABSTRACT FROM AUTHOR]

Accurate measurement of the small pre-failure deformation plays a crucial role in landslide early warning systems. Recently, terrestrial laser scanning (TLS) has been applied to detect the small pre-failure deformation, while the processing of TLS point clouds is still a non-trivial issue, especially for long-range TLS. Therefore, we propose an efficient method to detect the small pre-failure deformation of slow-moving landslides by the use of long-range TLS. To precisely align the point clouds of different epochs, a hybrid-weighted iterative closest point (HWICP) algorithm is proposed after the coarse registration, where the influences of several factors (i.e., deformed areas, point density variations, and observation errors) on the inconsistency of the point correspondence are quantitatively estimated. An adaptive local cloud-to-mesh method (ALC2M) is then proposed for the deformation calculation in the complex topography by defining a local reference frame and removing poor matches between ground points of the two epochs. To validate the performance of the proposed method, the Dashu landslide of the Three Gorges Reservoir Region was selected as a case study. The TLS-derived deformation showed that the landslide was stable in most areas over the study period, except for two abnormal deformation zones with maximum deformations of ~ 6 cm and ~ 3 cm, which agreed well with the ground-based synthetic aperture radar interferometry (GB-InSAR) measurements. A statistical analysis of the stable areas around the landslide illustrated a low uncertainty for the TLS-derived deformation of 6.3 mm. Therefore, the use of the long-range TLS was an efficient way to monitor slow-moving landslides. Moreover, extensive comparative experiments about the co-registration and deformation calculation were conducted, and the results showed that HWICP and ALC2M achieved superior performances. [ABSTRACT FROM AUTHOR]

Landslides are one of the most relevant geohazards worldwide, causing direct and indirect costs and fatalities. Italy is one of the countries most affected by mass movements, and the Molise region, southern Italy, is known to be susceptible to erosional processes and landslides. In January 2003, a landslide in the municipality of Agnone, in the Colle Lapponi-Piano Ovetta (CL-PO) territory, occurred causing substantial damage to both structures and civil infrastructure. To investigate the evolution of the landslide-affected catchment over approximately one century, different data were taken into account: (i) literature information at the beginning of the twentieth century; (ii) historical sets of aerial optical photographs to analyse the geomorphological evolution from 1945 to 2003; (iii) SAR (Synthetic Aperture Radar) data from the ERS1/2, ENVISAT and COSMO-SkyMed satellites to monitor the displacement from 1992 to 2015; (iv) traditional measurements carried out through geological and geomorphological surveys, inclinometers and GPS campaigns to characterize the geological setting of the area; and (v) recent optical photographs of the catchment area to determine the enlargement of the landslide. Using the structure from motion technique, a 3D reconstruction of each set of historical aerial photographs was made to investigate the geomorphological evolution and to trace the boundary of the mass movements. As a result, the combination of multitemporal and multitechnique analysis of the evolution of the CL-PO landslide enabled an assessment of the landslide expansion, which resulted in a maximum length of up to approximately 1500 m. A complete investigation of the past and present deformational sequences of the area was performed to potentially plan further mitigation and prevention strategies to avoid possible reactivations. [ABSTRACT FROM AUTHOR]

The Bàlitx area is located on the steep coastal side of the Tramuntana Range (Majorca), a mountainous region which was declared a World Heritage Site by UNESCO in 2011 in the cultural landscape category. The Bàlitx site was occupied by farming areas with dry stone constructions and water storing systems of both Roman and Islamic origin. The coastal landscape is characterised by a large fault escarpment of up to 260 m in height. Lateral spreading processes are favoured by local stratigraphy and tectonics in an energetic coastal dynamics scenario. Block spreading morphologies are identified along the escarpment, with large, rocky blocks of volumes up to 60 × 103 m3 moving very slowly until their collapse. Consequently, a thick and highly karstified breccia deposit is accumulated at the base of the scarp. The lowest, oldest breccia outcrop has been dated (Th/U), and an age of 82.5 ± 5.6 kyr was obtained, reflecting the time span this process has been active. Additionally, numerous geomorphological slope features are identified in the area: landslides, rockfalls, and, more specifically, long and deep cracks in the hanging wall block of the fault, which also reveal active lateral spreading processes. Coastal dynamics have been investigated by interpreting offshore geophysical studies, bathymetry data and borehole information to determine the role of wave energy in the stability of the slope. Additionally, 14 SAR images from the ALOS PALSAR satellite have been exploited for the present work, covering a period spanning from 2007 to 2010, an anomalous rainy period in the region. Images were processed using the Persistent Scattered Interferometry (PSI) technique. PSInSAR results reveal that the rate of movement for the Bàlitx lateral spreading is extremely low (− 5.2 mm/year on average), but major activity has been detected in the NE sector, where velocity rates can reach values of up to − 16 mm/year Coastal dynamics in the area can explain this, as a small island generates wave refraction and reflection determining more intense erosive processes in the NE part, which lead to a greater destabilising effect on the slopes. A simple vulnerability approach has been developed to take the elements of cultural heritage into account. Vulnerability increases from SW to NE, in accordance with landslide activity. The Bàlitx case study could provide a testimony to the effects of mass movements and coastal dynamics in an exceptional example of Mediterranean agricultural landscape. [ABSTRACT FROM AUTHOR]

In this manuscript, an integrated strategy that exploits both phase and amplitude features of satellite SAR (synthetic aperture radar) images and ground data is proposed for deriving the deformation field induced by a complex landslide that affected part of the village of Ponzano (Abruzzi Region, Central Italy). The February 12, 2017, landslide was triggered by the combined effects of intense rainfalls and snowmelt that saturated the slope. The SqueeSAR algorithm was applied to two C-band SAR datasets, composed by Radarsat-2 and Sentinel-1 images, spanning a nine-year time interval before the landslide occurrence. Moreover, the amplitude information carried by two TerraSAR-X images, acquired immediately before and after the event, was exploited to derive the total displacement generated by the landslide movement by means of the RMT (rapid motion tracking) algorithm. The obtained results allow describing the landslide behavior before and after its failure. In particular, the back-monitoring analysis shows that the landslide was already slowly moving, with deformation rates increasing from the Radarsat-2 to the Sentinel-1 monitored periods, 10 years before its complete mobilization. The landslide failure of February 2017 produced maximum displacements of about 10 m in some sectors of the affected area. The registered deformation rates and the localization of the maximum displacements areas were confirmed by field data, collected during a field campaign and a helicopter recognizance of the damaged areas, both performed after the event. [ABSTRACT FROM AUTHOR]