Rotational–translational landslides in the neogene basins at the northeast margin of the Tibetan Plateau

 

青藏高原东北缘新近纪盆地的旋转-平推式滑坡

 

Engineering Geology, Volume 244, 3 October 2018, Pages 107-115

 

Peng Xin, Zhen Liu, Shu-ren Wu, Changyu Liang, Cheng Lin

 

摘要：Rotational–translational landslides are common in Neogene basins throughout the world and are of high risk to the public. To understand the mechanism of rotational–translational failure, the spatial distribution and deformation of rotational–translational landslides in the northeast of the Tibetan Plateau are investigated in this study. The spatial distribution of these landslides is dependent on the regional tectonics and geomorphology, crustal stresses, and lithological properties. The rotational–translational landslides are concentrated in the Neogene mudstone basins, and the intensities of these landslides are observed to gradually decrease from the hinterland of the plateau to the marginal basins. The bedding-parallel shear zones within the location of the rotational–translational landslides are present in the overconsolidated Neogene mudstones with high clay content. Nearly horizontal tectonic stresses and erosion cause the formation of horizontal shear stresses in the sliding masses. In this stress environment, materials with low internal friction angle (<10°) are observed to develop in the shear zones. A weak layer with high clay content and low calcium content are observed in all the bedding-parallel shear zones of rotational-translational landslides. Further, illite–montmorillonite and illite are the main clay minerals of all the shear zones with no montmorillonite. Horizontal shearing is further accelerated by increasing the pore-water pressure and creep.

 

A data-based landslide susceptibility map of Africa  

 

基于数据的非洲滑坡易发性分布图

 

Earth-Science Reviews, Volume 185, October 2018, Pages 102-121

 

Jente Broeckx, Matthias Vanmaercke, Rica Duchateau, Jean Poesen

 

摘要：Our understanding of the spatial patterns of landslides in Africa is limited with available landslide studies typically focusing on only one or a few study areas. Moreover, Africa is clearly underrepresented in terms of available landslide inventories. This study aims to produce a first continent-wide landslide susceptibility map for Africa, calibrated with a well-distributed landslide dataset. We reviewed the literature on landslides in Africa and compiled all available landslide inventories (ca. 10,800 landslides), supplemented by additional landslide mapping using Google Earth imagery in underrepresented regions (ca. 7250 landslides). This resulted in a dataset of approximately 18,050 landslides. Various environmental variables were investigated for their significance in explaining the observed spatial patterns of landslides. To account for potential mapping biases in the dataset, we used Monte Carlo simulations that selected different subsets of mapped landslides to test the significance of the considered environmental variables. Based on these analyses, we constructed two landslide susceptibility maps for Africa: one for all landslide types and one excluding the known rockfalls. In both maps, topography is by far the most significant variable. We evaluated the performance of the fitted multiple logistic regression models using independent subsets of landslides, selected from the total dataset. Overall, both maps perform very well in predicting intra-continental patterns of landslides in Africa and explain about 80% of the observed variance in landslide occurrence. To further test the robustness and sensitivity to mapping biases, we also modelled landslide susceptibility while excluding regions with arid climates, as landslides in these environments are expected to be better preserved over time and therefore likely relatively overrepresented. Despite this potential bias, the effect on the landslide susceptibility model is limited. Based on the constructed database and our analyses we further discuss potential research gaps for landslide prediction in Africa and at continental scales. For example, analysis of the African countries' mean landslide susceptibility shows a lack of landslide research in various countries prone to landsliding (e.g.: Guinea, Gabon, Lesotho, Madagascar). Apart from the intrinsic value of this landslide susceptibility map as a natural hazard risk management tool, the map and compiled database are highly promising for other applications. For example, we explored the potential significance of landslides as a geomorphic process by confronting our landslide susceptibility map with an available database of measured catchment sediment yield for 500 rivers in Africa. Overall, a significant positive, but relatively weak relation between landslide susceptibility and sediment yield is observed.

 

Presenting logistic regression-based landslide susceptibility results  

 

基于逻辑回归的滑坡易发性原因研究

 

Engineering Geology, Volume 244, 3 October 2018, Pages 14-24

 

Luigi Lombardo, P. Martin Mai

 

摘要：A new work-flow is proposed to unify the way the community shares Logistic Regression results for landslide susceptibility purposes. Although Logistic Regression models and methods have been widely used in geomorphology for several decades, no standards for presenting results in a consistent way have been adopted; most papers report parameters with different units and interpretations, therefore limiting potential meta-analytic applications. We first summarize the major differences in the geomorphological literature and then investigate each one proposing current best practices and few methodological developments. The latter is mainly represented by a widely used approach in statistics for simultaneous parameter estimation and variable selection in generalized linear models, namely the Least Absolute Shrinkage Selection Operator (LASSO). The North-easternmost sector of Sicily (Italy) is chosen as a straightforward example with well exposed debris flows induced by extreme rainfall.

 

Satellite SAR interferometry for the improved assessment of the state of activity of landslides: A case study from the Cordilleras of Peru  

 

改进滑坡活动评估的卫星SAR干涉法：秘鲁科迪勒拉山系实例研究

 

Remote Sensing of Environment, Volume 217, November 2018, Pages 111-125

 

Tazio Strozzi, Jan Klimeš, Holger Frey, Rafael Caduff, Alejo Cochachin Rapre

 

摘要：In Peru landslides have been causing damages and casualties annually due to the high mountain relief and distinct seasonal precipitation distribution. Satellite Synthetic Aperture Radar (SAR) interferometry represents one possibility for mapping surface deformation at fine spatial resolution over large areas in order to characterize aspects of terrain motion and potentially hazardous processes. We present land surface motion maps derived from satellite SAR interferometry (InSAR) for a part of the Santa River Basin between the Cordilleras Blanca and Negra around the city of Carhuaz in Peru. Using both Persistent Scatterer Interferometry (PSI) and differential SAR Interferograms (DInSAR) from ALOS-1 PALSAR-1, ENVISAT ASAR, ALOS-2 PALSAR-2 and Sentinel-1 we mapped 42 landslides extending over 17,190,141 m2 within three classes of activity (i.e. 0–2 cm/a, 2–10 cm/a and >10 cm/a). A geomorphological inventory of landslides was prepared from optical satellite imagery and field experience and compared to the InSAR-based slope-instability inventory. The two approaches provide slightly different information about landslide spatial and temporal activity patterns, but altogether they can be combined for the assessment of the state of activity of landslides and possibly the development of hazard maps, which are not systematically available in this region. We conclude that ALOS PALSAR (1 and 2) and Sentinel-1 data have a high potential to derive high-quality surface deformation information of landslides in many mountainous regions worldwide due to their global and frequent acquisition strategies.

 

Mapping an earthquake-induced landslide based on UAV imagery; case study of the 2015 Okeanos landslide, Lefkada, Greece  

 

基于UAV图像的地震滑坡制图：希腊Lefkada2015年Okeanos滑坡实例研究

 

Engineering Geology, Volume 245, 1 November 2018, Pages 141-152

 

Sotiris Valkaniotis, George Papathanassiou, Athanassios Ganas

 

摘要：On November 17, 2015 07:10 UTC an earthquake of Mw 6.5 induced slope failures mainly at the western part of the island of Lefkada, Ionian Sea, Greece. The most characteristic one is the Okeanos site deep-seated landslide (near village Athani) that affected the man-made environment; part of the site, including a dirt road, moved downwards along the coastal cliff and a luxury hotel suffered heavy damage. The goal of this study is to map in detail the Okeanos landslide and to provide relevant quantitative data i.e. structural data and volume of both the accumulated and removed material. In order to achieve this, a comparison between pre-earthquake and post-earthquake point clouds generated from aerial imagery and UAV-acquired photos took place. Using Structure from Motion, the steep coastal cliff site was surveyed in detail, even in areas that are difficult to approach. Results from this study show that the total landslide area covers a surface of ~36,000 m2, while a removed volume of ~93.000 m3 of landslide material was evaluated using change detection techniques. In addition, fieldwork and survey data revealed that the sliding surface was a pre-existing fault surface upon which the geological material moved downwards the coastal cliff. The sliding surface dips west and is exposed along a 115 m long and 25–30 m high section scarp. As a conclusion, this study underlines the importance of a thorough geological study in order to identify landslide prone areas prior to any building activity, and shows that a UAV survey is capable to provide adequate information during a post-earthquake field survey for co-seismic landslide mapping and modeling.

 

Residual mechanisms and kinematics of the relict Lemeglio coastal landslide (Liguria, northwestern Italy)  

 

意大利北部Liguria地区残遗Lemeglio海岸滑坡的残余机理与运动学

 

Geomorphology, Volume 320, 1 November 2018, Pages 64-81

 

A. Cevasco, F. Termini, R. Valentino, C. Meisina, P. De Vita

 

摘要：The Lemeglio landslide is a deep-seated coastal landslide of the Liguria region (northeastern Italy) involving heterogeneous rock-masses formed by Miocene turbidide series, whose prevalent lithology varies from sandstones to mudrocks. It has been recognized since the end of the nineteenth century and characterized by a relict state of activity. Besides the general state of slope stability given by the current morpho-climatic conditions, different from those that determined its original paroxysmal evolution, a residual slow kinematics of the accumulation zone still exists, posing a threat to buildings and infrastructures located across the landslide foot. Consequently, the Lemeglio landslide represents a relevant case of study for advancing knowledge on residual kinematics, mechanisms and hazard inherited by a relict slope mass-movement phenomenon.The study is based on results of several drilling campaigns and geotechnical investigations carried out mainly by the Regione Liguria in the unstable landslide accumulation zone. Moreover, in this area ground deformations were assessed by inclinometer measurements and ADInSAR data covering two partially overlapping time spans, from June 2009 to July 2011 and from January 2004 to June 2014, respectively. By these data, joined with field geological and geomorphological surveys, an integrated and consistent landslide model was reconstructed, which was used for Limit Equilibrium (LEM) and Finite Elements Modelling (FEM) analyses. Among principal outcomes is the recognition, by field observations, stratigraphic and inclinometer data as well as slope stability modelling, of a basal sheared and softened band, made chiefly of remoulded mudrocks, which constrains the current landslide failure surface. Such basal band can be considered an inherited landslide structure, formed during the original paroxysmal stage of the Lemeglio landslide, which controls the current residual kinematics of the landslide deposits throughout the foot, depending also on the coastal marine erosion acting along the landslide toe.

 

Landslide state of activity maps by combining multi-temporal A-DInSAR (LAMBDA)  

 

基于多时A-DInSAR (LAMBDA)的滑坡活动图

 

Remote Sensing of Environment, Volume 217, November 2018, Pages 172-190

 

Roberta Bonì, Massimiliano Bordoni, Alessio Colombo, Luca Lanteri, Claudia Meisina

 

摘要：In this paper, a new methodology was developed to automatically update Landslide state of Activity Maps by combining multi-temporal A-DInSAR data (LAMBDA). LAMBDA procedure was tested using ERS-1/2 (1992–2000), Radarsat-1/2 (2003–2009) and COSMO-SkyMed data (2011–2014) over an area of 2199 km2 located in Alps context of Piedmont region (north-western Italy). For the first time, a multidimensional landslide activity matrix was implemented to update the landslide state of activity during the monitored time span. For the definition of the state of activity, the representative velocity of each landslide was divided by the standard deviation of the velocities along the slope of the whole dataset. Thus, a common stability threshold of ±1 was introduced for multi-sensors A-DInSAR data, allowing to distinguish a phenomenon with stable targets (PS-DS) or unstable PS-DS. By combining activity classes estimated during different time spans allows to determine if a phenomenon is active, reactivated, or dormant. Furthermore, an innovative confidence degree assessment was carried out to verify the reliability of the procedure, by considering the measuring points distribution and the variability of the movements for each landslide. The results were validated using the landslide inventory of the study area and in-situ monitoring systems for representative case studies. Thanks to this approach an updated state of activity until 2014 was assigned to 507 landslides out the 1657 which were previously mapped in the study area.