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Slow-moving landslides can be found worldwide, exhibiting gradual movement over years to decades, with velocities ranging from millimeters to meters per year. However, slow-moving landslides can undergo transformation into rapid and catastrophic events, leading to severe damage to human society. Given the presence of >2500 pre-existing slow-moving landslides identified and cataloged using LiDAR bare ground data in Taiwan, it is crucial to efficiently assess their activity prior to the typhoon and heavy rainfall seasons. Therefore, a key research objective is to enhance the ability to detect landslide velocities and movements over large areas spanning tens of thousands of square kilometers. This study aims to establish a workflow that employs the multitemporal interferometric synthetic aperture radar (MTInSAR) technique for the detection and monitoring of multiple slow-moving landslides across wide regions. Specifically, we propose an optimized analysis package called "multi-snap2stamps," based on the existing snap2stamps method, to generate interferograms for multiple regions simultaneously. Focusing on the analysis of nine pre-existing slow-moving landslides, with velocities <1.6 m/year (classified as very slow or extremely slow landslides according to established criteria), distributed across Taiwan with diverse terrain and geological conditions, this study investigates the characteristics of these deep-seated landslides using the proposed MTInSAR analysis workflow in both spatial and temporal domains. The results reveal that two slow-moving landslide sites exhibit significant seasonal signals in the time series, while seven sites do not display such signals. Additionally, the MTInSAR time series effectively captures accelerated movement in the Shiding-T001 landslide, which corresponds well with in situ inclinometer monitoring data. This study demonstrates the effective analysis of velocity distribution and movement characteristics of slow-moving landslides using the proposed MTInSAR workflow. Furthermore, it highlights the potential of this workflow for improving landslide motion detection over vast areas of interest in the future. • Simultaneous generation of SAR interferograms from multiple regions of landslides. • Optimizing an MTInSAR workflow for analysis of multiple slow-moving landslides. • Detecting accelerated movements of slow-moving landslides by time series analysis. • Implication of seasonal fluctuation signals from the MTInSAR time series. [ABSTRACT FROM AUTHOR]

Several remote sensing techniques, namely traditional aerial photographs, an unmanned aircraft system (UAS), and airborne lidar, were used in this study to decipher the morphological features of obscure landslides in volcanic regions and how the observed features may be used for understanding landslide occurrence and potential hazard. A morphological reconstruction method was proposed to assess landslide morphology based on the dome-shaped topography of the volcanic edifice and the nature of its morphological evolution. Two large-scale landslides in the Tatun volcano group in northern Taiwan were targeted to more accurately characterize the landslide morphology through airborne lidar and UAS-derived digital terrain models and images. With the proposed reconstruction method, the depleted volume of the two landslides was estimated to be at least 820±20x106 m³. Normal faulting in the region likely played a role in triggering the two landslides, because there are extensive geological and historical records of an active normal fault in this region. The subsequent geomorphological evolution of the two landslides is thus inferred to account for the observed morphological and tectonic features that are indicative of resulting in large and life-threatening landslides, as characterized using the recent remote sensing techniques. [ABSTRACT FROM AUTHOR]

Abstract: The 1999 Chi-Chi earthquake triggered the catastrophic Tsaoling landslide in central Taiwan. We mapped the landslide area and estimated the landslide volume, using high-resolution digital elevation model from airborne LiDAR (Light Detection and Ranging), satellite images, aerial photographs and topographic maps. The comparison between cut and fill volumes, about 0.126 and 0.150 km3, respectively, suggests a volume increase of 19% due to decompaction during landsliding. In April 2002, the cut and fill volumes were about 0.137 and 0.116 km3, respectively. These estimates suggest that 2.5 years after the event, the volume of landslide debris removed by river erosion was nearly 0.045 km3. Such a large value highlights the importance of landslide processes for erosion and long-term denudation in the Taiwan mountain belt. To cite this article: R.-F. Chen et al., C. R. Geoscience 337 (2005). [Copyright &y& Elsevier]

A slow-moving landslide on the Huafan University campus, which is located on a dip slope in northern Taiwan, has been observed since 1990. However, reliable monitoring data are difficult to acquire after 2018 due to the lack of continuous maintenance of the field measurement equipment. In this study, the multitemporal interferometry (MTI) technique is applied with Sentinel-1 SAR images to monitor the slow-moving landslide from 2014–2019. The slow-moving areas detected by persistent scatterer (PS) pixels are consistent with the range of previous studies, which are based on in situ monitoring data and field surveys. According to the time series of the PS pixels, a long period gravity-induced deformation of the slow-moving landslide can be clearly observed. Moreover, a short period seasonal surface fluctuation of the slow-moving landslide, which has seldom been discussed before, can also be detected in this study. The seasonal surface fluctuation is in-phase with precipitation, which is inferred to be related to the geological and hydrological conditions of the study area. The MTI technique can compensate for the lack of surface displacement data, in this case, the Huafan University campus, and provide information for evaluating and monitoring slow-moving landslides for possible landslide early warning in the future. [ABSTRACT FROM AUTHOR]

A natural hillslope developing into a landslide shows ground cracks and topographic deformation. Geomorphological and subsurface investigations using appropriate methodology are essential to understand the failure mechanisms and stability of a hillslope. Huafan University campus located on a dip slope in northern Taiwan is facing a potential landslide hazard. Slope movement was detected through the development of ground cracks and persistent deformation of campus buildings and facilities. To monitor the sliding behavior of the dip slope, a nail network consisting of 144 ground monitoring points was set in 2001, and its coordinates were measured using conventional traverse surveying twice a year until 2017. The 17-year surficial surveying results were presented as a time series of displacements with constraints of geometry and distribution of ground cracks and underground observations. The long-term surveying results reveal multiple potential sliding blocks within the Huafan University campus. A model of landslide movement with a listric sliding surface is proposed. Additionally, from the velocity field derived from the monitoring points, the horizontal strain rates of the slope are estimated. The pattern of strain rates indicates that a plausible fault passing through the campus may have affected the movement of the dip slope. The long-term surface monitoring of a potential landslide slope in this study provides a reliable and economical way to understand the mechanism of movement behavior of the slope and evaluate slope stability. • 17-year surficial monitoring distinguishes movement behavior of different parts of dip-slope landslides. • A model of movement process of landslides having listric sliding surface(s) is proposed to reveal intermittent movements. • A strain pattern obtained of the slope surface evidences a tectonic fault passing through the landslide block. • Economic and reliable study procedures are applicable to unstable slopes for research and disaster prevention. [ABSTRACT FROM AUTHOR]

Catastrophic landslides often cause serious disasters, and such incidents are often the focus of our attention. The well-known Tasoling Landslides occurred repeatedly, which were triggered by earthquakes, typhoons, and torrential rains in 1862, 1898, 1941, 1942, 1951, 1979, and 1999. Among these, the landslides in 1862, 1941, and 1999 were triggered by earthquakes. The Tsaoling area geologically belongs to a dip-slope terrain in interbedded Pliocene sandstone, mudstone, and shales. The volume of the rock debris accumulated from previous landslide events was about 0.026 - 0.126 km3, which formed a landslide dam with a height of 70-170 m and blocked the Qingshui river. The sudden failures of these landslide dams often resulted in additional catastrophes in the downstream areas, three of which occurred years after the landslide event. With the progress of surveying technology, high-resolution DEMs data could be used for important topics, such as landslides and geomorphic change. In this study, we presented multi-temporal remote sensing datasets for geomorphic changes in the Tsaoling landslide area before and after the Chichi earthquake and provided an effective DEM analysis technique to better estimate volume changes and surface movements. We found that multi-temporal data comparison could show the geomorphic changes of the Tsaoling landslide area directly at different times by using aerial photogrammetry and LiDAR DEM analysis. The observed results of geomorphic changes in the shorter period of 1- 3 years from 2011 to 2012, 2012 to 2016, 2016 to 2017 and over a long period time of about 9 years from 2002 to 2011, including the location of the landslide accumulation area, the change of cliff retreat, and the volume change of the debris after the landslide event. By means of terrain profile comparison, elevation change calculation and Particle image velocimetry (PIV) analysis from image and DEM data during 2016-2017, we found some surface displacement located in the lower half of the Tsaoling landslide area and distributed in the Chinshui shale area. Within the range of about 80 hectares, there was a clear trend of surface displacement, indicating that this range of the Tsaoling area may have slipped, which was similar to the scale as the 1942 landslide event. This study shows that the integrated use of aerial photogrammetry and LiDAR DEM data analysis method with multi-temporal topographic data collection and field surveys in the landslide area, and could resolve the surface changes and possible impacts of this large landslide and river geomorphological changes in the future. [ABSTRACT FROM AUTHOR]

Dip-slope mapping is a fundamental task for landslide investigation and mitigation. However, most dip-slope mapping methods involve visual interpretations and manual processes that are inevitably subjective and time consuming. The advent of high-resolution digital elevation models (DEM) and increases in computing power have provided opportunities to improve the dip-slope mapping process. This study proposes a polygon auto-tracing method for generating dip-slope maps based on airborne Light Detection and Ranging (LiDAR) data and a customized spatial analysis toolset developed in Python. This method requires the input of strata boundaries produced for sedimentary terrain based on 2 m resolution LiDAR DEMs. The method begins by deriving the raster layer of the dip direction of the bedding, and it then executes a series of raster calculations among the three raster layers slope, aspect, and dip direction to extract the dip-slope raster cells. Using the clustering pattern of the dip-slope raster cells, we implement the Point-Density analysis tool to determine the dip-slope areas. The ArcGIS ModelBuilder platform is used to lay out an automated workflow for the proposed polygon auto-tracing method using the customized toolset. For demonstration purposes, we successfully mapped 298 dip slopes in the study area, which frequently experiences dip-slope landslides and is located in the sedimentary terrain of northern Taiwan. The dip-slope mapping results were compared and validated against two government-funded visually interpreted dip-slope maps. Our dip-slope mapping results were also used in a daylight analysis along major freeways to identify potential locations of daylighted dip slopes. [ABSTRACT FROM AUTHOR]

Abstract: The Chi-Chi earthquake occurred in the western foothills of central Taiwan, which triggered coseismic and catastrophic Chiufengershan dip-slope landslides, Tsaoling rockslides and surface stripping of the Jiujiufeng area. After a few days of the Chi-Chi event, the Hongtsaiping area in central Taiwan was reported to have several meters of slide in a small scale area. The reported landslides are dissimilar to the catastrophic events. To better understand the characteristics of such non-catastrophic and unobvious landslide, we try to characterize in detail the sliding directions, their magnitudes and region of the landslide. We analyzed three orthorectified aerial photographs of the Hongtsaiping area, which were taken in 1998/06/13, 1999/11/18 and 2002/10/26, using the Particle Image Velocimetry (PIV) technique. Through the method we correlated the image pixels of the two aerial photographs in order to derive the displacement vector field. The results of the PIV analysis have helped us not only find the areas where sliding had happened, but also evaluate the azimuth and magnitudes of the sliding event. The PIV analysis in the Hongtsaiping area covers a dimension of about 3228×2448 pixels in an area of about 1.2 km2. Our results show that the maximum horizontal displacement of the landslide is about 24 m towards NW in the study area. This unobvious but wide-coverage landslide may need further investigation in mechanisms combining with available or new geological data. [Copyright &y& Elsevier]

Abstract: The Jiufengershan rock and soil avalanche is one of the largest landslides triggered by the Chi-Chi earthquake Taiwan 1999. The landslide destabilized the western limb of the Taanshan syncline along a weak stratigraphic layer. It involved a flatiron remnant, which was almost entirely mobilized during the earthquake. The avalanche was slowed down by NS trending ridges located downstream along the Jiutsaihu creek. The landslide affected a 60 m thick and 1.5 km long sedimentary pile composed of shales and sandstones, which dip ∼22°SE toward a transverse valley. The triggering mechanism and the sliding process were analyzed by means of geological and morphological data from aerial photographs and observed in the field. A high-resolution airborne Light Detection and Ranging (LiDAR) image taken 2.5 years after the landslide allows the identification of morphological structures along the sliding surface and the landslide accumulation. The sliding surface shows several deformation structures such as fault scarps and folds. These structures are interpreted in terms of basal shear stresses created during the avalanche. Three major joint sets were identified at the sliding surface. The isopach map of the landslide was calculated from the comparison between elevation models before and after the earthquake. The coseismic volume of mobilized material and landslide deposit data are 42×106 m3 and 50×106 m3, respectively. The geometry of the landslide accumulation in the field has an irregular star shape. The morphology of the deposit area shows a sequence of smooth reliefs and depressions that contrast with the neighboring ridges. [Copyright &y& Elsevier]

Earthquakes can generate seismic disturbances that propagate vast distances and trigger landslides that can achieve high-speeds. It remains difficult to identify the co-seismic ground motion of these landslides and their triggering earthquakes. In this paper, we report on the analysis of co-seismic ground motions generated by the initiating fracture and deposition impact of the Tsaoling landslide. The landslide, with a source volume of 125 × 10 6 m 3 , was triggered by the 1999 Chi-Chi earthquake in Taiwan. The ground motion was recorded by a strong ground motion station, CHY080, near the scar area. The polarization of the seismic waves indicates that the peak acceleration was parallel to the dip direction. Modified ensemble empirical mode decomposition (EEMD), with additional clustering analysis, was applied to decompose the seismic signals. Two instances were found in the seismic records of a series of peculiar wave packets, with the first being associated with the landslide initiation and the second the landslide impact on the deposit valley. To confirm the first landslide breakage, the decomposed signals were compared with the predictions of the analytic elastic wave model and Newmark analysis. The landslide impact was verified with a computational fluid dynamic simulation. Comparison between the EEMD decomposed signals, elastic wave theory, Newmark rigid body analysis, and numerical simulation demonstrates the claimed landslide motion. [ABSTRACT FROM AUTHOR]

Abstract: In the village of Tsaoling (in Yunlin County, Taiwan), a major landslide was triggered by the Chi-Chi earthquake in 1999 with more than 125×106 m3 of rock displaced. The kinematic behaviour of this landslide is simulated using a 2D discrete element model (PFC2D code). Our numerical model is composed of discs bonded together. The initial boundary conditions are applied along the ball-wall contacts by using derived velocities integrated from the strong motion data with a duration of 160 s including the peak acceleration near Tsaoling. The constraints are mainly issued from the final geometry of the landslide including its capacity to cross the river valley and reach a significant elevation on the opposite mountain flank. They also result from a variety of geological and hydrological observations, including the local levels of material disruption and the location of survivors. Our modelling thus indicates that a low-friction coefficient (about 0.15) and a medium strength are required to account for the actual landslide characteristics. A self-lubrication mechanism probably accounts for the low residual friction. Our model also suggests that the maximum velocity of sliding reached 50 m/s, a result that cannot be checked in the absence of actual measurements. In addition to friction, the strength of sliding block is of special importance because it controlled the possibility for the upper layer fragments to roll and get buried, and hence the probability of survival. [Copyright &y& Elsevier]