Search

• Recurrent fire leads to degraded rainforest (DRf) and herbaceous-shrubby (HS). • Ksat and 6 years of rainfall-soil suction interactions are analyzed. • HS provide shallow soil saturation even during long dry periods. • Fire decreases Ksat in topsoil and it increases soil suction in depth at HS. • Post-fire soil changes tend to favor rapid suction loss in the unsatured zone. The role of fire in vegetation-soil–water interactions and its implications for soil stability and slope failures is poorly documented in humid tropical regions. This paper focuses on the relationships between vegetation change through recurrent fire and its effects on hydraulic conductivity and soil suction. Two monitoring sites were chosen on steep slopes in the mountainous domain of the Atlantic rainforest: the first is representative of degraded secondary rainforest (DRf) 25–30 years after slash and burn agriculture; the other represents herbaceous-shrubby vegetation (HS) resulting from wildfires in short-time intervals (<5 years). Two fires had previously occurred on the HS slope, one in December 2014 and the other in September 2019. Continuous records of rainfall and soil suction at depths of 10, 20, 50, 100, 150, and 220 cm provided a 6-year data collection from January 2015 to December 2020. Hydraulic conductivity (Ksat) field tests were conducted around the two monitoring sites before and after the September 2019 fire. The main results include: a) soil suction in the topsoil of both vegetation covers follow the rainfall inputs with high values of Ksat (DRf = 195 mm/h; HS = 203 mm/h); b) while quick rainfall-suction responses prevail within the DRf soil profile, soil suction at HS maintains a mean suction value around -27 kPa below 100 cm deep; c) field observations attest to the occurrence of hydrophobicity after the 2019 fire; d) Ksat tests just after this fire indicated a decreasing mean value from 203 mm/h to 46 mm/h; and e) by the end of the dry season after fire, there is a delayed increase in soil suction reaching -143 kPa at a depth of 100 cm and in smaller proportions at 220 cm deep. These results indicate that post-fire soil changes tend to favor the sudden loss of soil stability and slope failure during extreme rainfall events. [ABSTRACT FROM AUTHOR]

• The early attenuation of soil strength contributes to landslides caused by changes in pore water pressure. • Corrected the safety factor curve of cohesive soil slope superficial failure. • The potential sliding surface is closely related to the spatial variation of soil properties in the 'affected layer'. Slope failure is associated with changes in pore water pressure induced by rainfall, this paper further attempt to bridge knowledge gaps that exist in understanding the relationship between mechanism of rainfall-induced regional-scale widespread shallow landslides in cohesive soils and change in pore water pressure. We designed in situ slope experiments with pre-designed vertical profiles at the toe of the slope, and used pore water pressure, conductivity, and moisture content sensors to capture the changing characteristics of soil properties during slope failure. The experiment finds that failure occurred first where internal material was continuously taken out of the slope, even before the maximum static pore water pressure is reached. However, the slope remains stable when the pore water pressure near the failure surface reached the maximum static pore water pressure that could be provided by rainfall. Instead, slope failure during subsequent rainfall periods, even if the pore pressure is then lower. Meanwhile, the soluble minerals in the soil continuously dissolve and migrate, causing the electrical conductivity before slope failure is approximately 1.38 times that after failure, on average. Here, we estimate that the changes in soil properties caused by progressive water infiltration only may have decreased test slope stability by an average of approximately 33.0%. Therefore, we suggest that the early attenuation of soil strength caused by the gradual changes in soil properties makes a significant contribution to soil failure caused by pore water pressure. This was verified in the case of the 7.25 Tianshui group-occurring landslides. Finally, by using an automatic laser particle size analyzer, scanning electron microscope, X-ray diffraction, ion chromatography, and quadruple direct shear instrument to analogize the changes in soil properties exposed to different leaching environments on loess platform, we further show that the early attenuation soil strength is caused by deteriorate in soil properties in the processes of successive years of rainfall, where the content of cemented minerals tends to decrease, fine particles tend to be lost, and pore structure tends to take the form of single macro-pores, which are more likely distributed around mineral particles >10 μm. Our results provide a new perspective on the widespread shallow landslides caused by changes in pore water pressure in a region and their associated gradual deteriorations in soil properties. [ABSTRACT FROM AUTHOR]

[Display omitted] • The potential future evolution of LS in response to LUC changes in Romania was assessed. • The LS change was estimated by integrating LUC scenarios, predicted by the CLUEs model. • At the national level, an overall net slight decrease of LS is expected until 2075. • LUC transitions to forests have the largest contribution to the decrease of LS. • An appropriate land management may significantly contribute to reducing the LS level. Land-use/cover (LUC) change is a global change forcing with important impacts on landslides, which highlights the need to evaluate the potential future evolution of these hazards under future LUC scenarios. Accordingly, the current paper provides a first national-level exploration on the possible effects of LUC pattern change on landslide susceptibility (LS) in Romania, shedding light on the evolution of one of Europe's landslide hotspot countries as well as one of the territories significantly affected by recent LUC change, especially after the fall of the communist regime. Two countrywide future LS maps were modelled for 2075, by applying a previously developed national scale-adapted LS empirical procedure, integrating therein two existing long-term LUC pattern forecasts and assuming no change for the other landslide controlling factors. The estimated future LS maps were then compared to the current LS zonation using a pixel-based analysis to estimate the contribution of LUC class transitions to the LS variation in time. The quantitative examination of LS changes suggests an overall net slight decrease at the national level under both scenarios (on an average of 7.3% of the LUC change area), with more significant regional variations. The location and extent of the estimated potential LUC transitions reflect themselves into a clear influence on the future LS level manifesting itself, on average, over 7.1% of the country's area. The analysis demonstrates that the expected increase in the forest-covered area brings the most important contribution to the decrease of the LS level. An average of 44.2% of the total LS decrease area was mainly predicted by the transitions from pastures and natural grasslands/scrubs to forests, and 11.4% by that from heterogeneous agricultural areas to forests. Conversely, transitions to pastures and natural grasslands resulted in the most important contribution to the increase of the LS level (52.2%). Transitions among other agricultural lands resulted in slight susceptibility variations or in no change. Through the analysed LUC scenarios, differing in terms of the implementation of environmental management regulations inside protected areas, the study proves that a more appropriate land management could have an important influence on decreasing LS, a finding of particular relevance for encouraging and extending a conscious application of protective land measures, especially on slopes which are degraded or prone to instability, in a country otherwise characterised by an overall relative implementation of environmental policies. In addition, the analysis reveals that a significant proportion (24.2%) of the projected new built-up areas is expected to spread by 2075 over lands with moderate, high and very high LS, resulting in potentially new landslide exposure hotspots in the future in both rural and urban areas. The obtained results could be used in directing landslide risk reduction actions and decisions primarily towards the management of LUC and towards prioritizing areas for such measures, while, from a theoretical perspective, this approach could be extended to future investigations related to LUC change implications for landslide hazard and risk in Romania, but could also be followed in case of other national territories. [ABSTRACT FROM AUTHOR]

• First study in the Eastern Mediterranean reconstructing debris flows in a landslide body. • Shallow landslides and channel avulsions lead to dynamic spatial patterns. • The annual occurrence of events since 2014 was determined from tree-ring records. • Debris flow activity was compared with rain gauge data and climate reanalyses. • Interdecadal variability of extreme 3- and 5-day rainfalls affects debris flow dynamics. Chronological data on recent debris-flow activity in the Eastern Meditteranean are fragmentary, limiting a proper assessment of future geomorphic risk. This is especially true if these processes occur on collapsed slopes that predispose their occurrence. This paper reports on the long-term debris-flow activity reccuring periodically in the body of the 1913 Tsivlos landslide in Hellenides (Greece) using variety of methods. Analysis of aerial images confirmed a shift of active channels and debris-flow fans, mainly due to the recharge of new material in the landslide source zone, the contribution of partial shallow landslides, and frequent channel avulsions. Dendrogeomorphic reconstruction of 59 trees including Pinus nigra Arn. and Platanus orientalis L. pointed to the least annual occurrence of debris flows since 2014. Our data also specified the occurrence of at least one landslide-generated debris flow in 2018/2019 and one debris flow in 2019/2020 with an estimated maximum velocity of 6.3 m.s−1 and maximum discharge of 171.1 m3.s−1 in the transport zone. Our results suggest a link between increased debris-flow activity and increased occurrence of 3-day and 5-day extreme precipitation events, which were more pronounced in the 1950 s, 1990 s, and 2010 s. We conclude that debris-flow activity is likely to continue at this site and may continue to threaten infrastructure passing through the landslide body. Therefore, it is desirable to monitor the site and conduct ongoing field research to prevent future hazards from debris flows. [ABSTRACT FROM AUTHOR]

Abstract Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques have repeatedly proved to be an effective tool for built environments monitoring in areas affected by geological hazards. This paper describes how the Coherent Pixel Technique (CPT) approach has been successfully applied to assess the response of an unstable slope to the different phases of remedial works following a landslide event. The CPT technique was performed on 59 COSMO-SkyMed images obtained between May 2011 and August 2016 and centred on the Quercianella settlement (a small hamlet of Livorno municipality, Tuscany, Italy), where the reactivation of a dormant shallow slide had occurred in March 2011 and, hereafter, a geotechnical intervention, designed with the aim of mitigating the risks, has been conducted from August 2013, lasting thirteen months. The time series of CPT results show a deformation pattern with sudden accelerations (up to 21 mm in few months) corresponding to the beginning of the interventions, during which the area has been excavated to install a drainage well, followed by mild decelerations resulting from the stabilization of the area after the conclusion of the works. In particular, the integration of ground-based subsurface monitoring (inclinometers and piezometers) and DInSAR superficial data has provided consistent results for landslide characterization and helped defining the state of activity and the areal distribution of the sliding surface. Moreover, the performance of remedial works in the landslide-affected area has been observed, showing stabilization in the upper part of the hamlet and the ongoing movement in the lower part. The combined monitoring system also led the geotechnical company in charge of remedial works to design further stabilization works in order to preserve buildings and roads in the moving area. Therefore, the integration of remote sensing techniques and in situ instruments represents a timely and cost-efficient solution for intervention works monitoring, opening new perspectives on designing engineering solutions for the stabilization of unstable slopes. Highlights • DInSAR and conventional monitoring techniques were applied in Livorno, Italy. • Such integration supported the design of remedial works of the landslide. • The performances of the drainage well were observed by DInSAR and inclinometers. • The monitoring system led the company in charge to plan further stabilization works. [ABSTRACT FROM AUTHOR]

• An approach is proposed to assess extreme rainfall-triggered landslides. • 3D unsaturated flow is coupled with the infinite slope method. • Extreme precipitation events are investigated using soil depth models. • 1-year spin up for moisture conditions has little impact on the safety factor. • Simple soil depth models are viable options for landslide susceptibility studies. The susceptibility to shallow landslides is affected by several factors. Rainfall intensity, soil thickness distribution, and antecedent moisture conditions are components that influence the spatio-temporal prediction of landslides at the watershed scale. Yet, the combined impact of these factors on the susceptibility to landslides has been overlooked. The purpose of this paper is to investigate landslides triggered by extreme precipitation in the Tijuca Massif, Rio de Janeiro, southeastern Brazil. Our approach couples a 3D variably saturated flow solver with the infinite slope stability method to calculate the statistical distributions of the safety factor and the pore pressure at the soil–bedrock interface. Numerical simulations were performed for 6 scenarios considering 1-year spin-up time for soil moisture and different spatially distributed soil depths. The results show that during extreme precipitation events, soil depth and initial moisture conditions may not have much influence on the safety factor, as the intensity and duration of rainfall will be the triggering agents. Comparison of simulated unstable zones and field data from mapped landslide scars further supported this conclusion. We conclude that simple soil depth models are feasible options for regional studies of landslide susceptibility. Our findings are relevant to understanding shallow landslides induced by extreme rainfall in Rio de Janeiro and other regions with similar geological and climate settings. [ABSTRACT FROM AUTHOR]

Landslides are natural phenomena that can cause great loss of life and damage to property. A landslide susceptibility map is a useful tool to help with land management in landslide-prone areas. A support vector machine (SVM) is a machine learning algorithm that uses a small number of samples for prediction and has been widely used in recent years. This paper presents a review of landslide susceptibility mapping using SVM. It presents the basic concept of SVM and its application in landslide susceptibility assessment and mapping. Then it compares the SVM method with four other methods (analytic hierarchy process, logistic regression, artificial neural networks and random forests) used in landslide susceptibility mapping. The application of SVM in landslide susceptibility assessment and mapping is discussed and suggestions for future research are presented. Compared with some of the methods commonly used in landslide susceptibility assessment and mapping, SVM has its strengths and weaknesses owing to its unique theoretical basis. The combination of SVM and other techniques may yield better performance in landslide susceptibility assessment and mapping. A high-quality informative database is essential and classification of landslide types prior to landslide susceptibility assessment is important to help improve model performance. [ABSTRACT FROM AUTHOR]

This paper presents GIS-based new ensemble data mining techniques that involve an adaptive neuro-fuzzy inference system (ANGIS) with genetic algorithm, differential evolution, and particle swarm optimization for landslide spatial modelling. This research was tested in Hanyuan County, which is a landslide-prone area in Sichuan Province, China. Different continuous and categorical landslide conditioning factors according to a literature review and data availability were selected, and their maps were digitized in a GIS environment. These layers are the slope angle, slope aspect, altitude, plan curvature, profile curvature, topographic wetness index, distance to faults, distance to rivers, distance to roads, lithology, normalized difference vegetation index and land use. According to historical information of individual landslide events, interpretation of the aerial photographs, and field surveys supported by the Sichuan Land Resources Bureau of China, 225 landslides were identified in the study area. The landslide locations were divided into two subsets, namely, training and validating (70/30), based on a random selection scheme. In this research, a probability certainty factor (PCF) model was used for the evaluation of the relationship between the landslides and conditioning factors. In the next step, three data mining techniques combined with the ANFIS model, including ANFIS-genetic algorithm (ANFIS-GA), ANFIS-differential evolution (ANFIS-DE), and ANFIS-particle swarm optimization (ANFIS-PSO), were used for the landslide spatial modelling and its zonation. Finally, the landslide susceptibility maps produced by the mentioned models were evaluated by the ROC curve. The results showed that the area under the curve (AUC) of all of the models was > 0.75. At the same time, the highest AUC value was for the ANFIS-DE model (0.844), followed by ANGIS-GA (0.821), and ANFIS-PSO (0.780). In general, the proposed ensemble data mining techniques can be applied for land use planning and management of landslide susceptibility and hazard in the study area and in other areas. [ABSTRACT FROM AUTHOR]

The slopes of Mount Elgon, a complex volcano at the border between Uganda and Kenya, are frequently affected by landslides with disastrous effects on the livelihood of its population. Since local people greatly depend on the land for crop production, this paper examines if and how fast physico-chemical characteristics in landslide scars recover. A chronosequence of 18 landslides covering a period of 103 years was sampled in order to explore differences between topsoil inside and outside landslide scars. For each landslide, two topsoil samples were taken within the landslide and two in nearby undisturbed soils to compare their physico-chemical characteristics. Samples inside the landslides were located at the transition zone between the depletion and accumulation zone, which is situated at the contact line between the plan concave and plan convex section of the landslide. No differences were found for available phosphorus, Ca 2+ , Mg 2+ content or for the fine earth texture. Recent landslides had however lower content of soil organic carbon ( OC) and K + , and higher content of rock fragments and Na + than the adjacent soils. Soil OC content increased significantly with age and reached levels of the corresponding undisturbed soils after ca. 60 years. Older landslides had even higher OC contents than soils adjacent to the landslide. Hence landslide scars act as local carbon sink. We suggest that the occurrence of rock fragments in the topsoil is a useful indicator for mapping past landslides. Moreover, the difference in soil OC content between landslide scars and adjacent soil could be used for estimating the age of landslides in data-poor regions. [ABSTRACT FROM AUTHOR]

• Both models have applicability in prediction of group-occurring shallow landslides. • Combining Scoops3D and TRIGRS shows more effective landslide prediction result. • TRIGRS has the problem of over-prediction in the simulation of unstable area. • Fitting curve of rainfall threshold supports landslide warning in basin lacking data. The stability evaluation of rainfall-induced landslides using a physical determination model supports disaster prevention, but it is mostly applied to the area with few landslides, and there is a lack of quantitative study on rainfall and landslide stability. This paper combined the Scoops3D model with the TRIGRS model (3D) to predict the shallow landslide spatiotemporal distribution and compared the simulation results with those of the TRIGRS model alone (1D), aiming to obtain more accurate assessment results. At the same time, the relationship between landslide stability and accumulative rainfall was quantitatively fitted to improve the real-time landslide prediction system. We applied the 1D and 3D models to the July 21, 2013 group-occurring landslide event (976 shallow landslides) in the Niangniangba basin, China. The required geotechnical parameters of both models were acquired by field and laboratory tests. We calculated the pressure head over time using the TRIGRS model based on practical rainfall data and predicted the shallow landslide stability using the Scoops3D model according to the resulting piezometric surface. We compared the landslide stability spatial distributions of the two models under initial and saturated conditions with the landslide catalogue. The success rate of landslides predicted by 3D model is 4.20% higher than 1D model. A composite index to quantitatively evaluate both models' performances indicates over-prediction by the 1D model in the stable region, while the 3D model more effectively predicts shallow landslides with a smaller unstable region. The relationship between instability proportion and accumulative rainfall in the 1D and 3D model can be represented by y = 24.57 x 0.18 and y = 11.59 x 0.33 , respectively. The 3D model shows more conservative result, and the rainfall threshold analysis proposed in this paper can provide reference for the time of most landslides in the case of insufficient data, which is an important indicator for disaster early warning and prediction. [ABSTRACT FROM AUTHOR]

The use of satellite Synthetic Aperture Radar Interferometry (InSAR) for monitoring ground instability due to landslide events, although advantageous over large spatial scales, still poses challenges related to the recurrently complex kinematics of the phenomena or to the unfavorable settings of the examined areas with respect to steep topography and vegetated land cover. This paper presents results obtained by using Multi-temporal InSAR techniques with high resolution TerraSARX (TSX) data for monitoring the Carlantino landslide, located in the Daunian Subapennine (Apulia region, southern Italy) on a slope overlooking a water reservoir, and subjected to several investigations and consolidation works. The targets detected by using Persistent Scatterer Interferometry (PSI) correspond to urban structures or peri-urban walls and guard rails, while the landslide body is almost completely devoid of stable targets, due to the widespread vegetation and variable land cover. To allow stability monitoring, a network of six Corner Reflectors (CR) was designed and deployed over the landslide test site. The TSX images were analyzed by using both the PSI processing and a procedure, based on the double difference analysis of InSAR phase values on the CR pixels. Despite residual noise and the loss of 2 CRs due to vandalism, the processing allowed verifying the stability of the upper and central part of the landslide body, and relating indirectly the movements at the toe of the landslide to the water level fluctuations of the reservoir. Finally, this experiment suggests some recommendations and guidelines in planning CR deployment in complex landslide sites. [ABSTRACT FROM AUTHOR]

The weathering processes produce important chemical and physical transformations in rock masses producing a decay of their strength and then stability. In this study different methodologies were employed to define the physical-mechanical properties and the minero-petrographical changes at each grade of weathering, useful to determine a geological model of the weathered granitoids involved in mass movements. The paper focuses on a multidisciplinary research on the weathering profiles of the Paleozoic granitoid rocks surrounding the village of Fabrizia located in the Serre Massif (southern Calabria, Italy). Fabrizia lies on an old erosion surface composed of basement rocks made up of weathered granitoids, belonging to the Serre Massif granitoid complex, and overlain by thin eluvial-colluvial deposits. The tectonic uplift of the area combined with Mediterranean climatic conditions, both active at least since the Quaternary, are the main causes of the deep weathering of the plutonic rocks. The weathered profiles of the granitoid complex have been studied through field observations, borehole explorations with geotechnical tests and seismic surveys coupled to minero-petrographical analysis and laboratory tests. Weathered profiles are mainly composed by rock masses varying from completely weathered and residual soil (classes V–VI) to moderately weathered rocks (class III), characterized by a progressive increase of geotechnical properties ( e.g. , seismic wave velocity, rock quality designation, internal friction angle, uniaxial compressive strength) with a decrease of weathering. The weathered rocks display a wide variety of mass movement. Landslide types are rockfalls for the fresher rocks (class III); translational slides occur between different weathering degrees (classes IV and V) and rotational slides dominate at the top of the slopes and generally involve the weathering grades from class IV to classes V–VI. The shallow horizons are composed of thin eluvial-colluvial deposits and more weathered granitoids (classes V–VI) that may generate dangerous debris flows or debris avalanches during intense and prolonged rainfall. The landslide surface is usually at a depth lower than 2 m in the debris flow type, while deeper landslides (depth > 2 m) are rotational and translational types with sliding surfaces occurring mainly in the transition between the classes IV and V. The field survey coupled to geotechnical, geophysical and minero-petrographical data allowed the recognition of the different weathered horizons and relative geotechnical properties useful to the reconstruction of the reliable geological model. The model represents an important support for the study of the landslide processes and for a sustainable management of the territory. The used approach provided results to set a general reference framework for establishing more precise correlations between mass movement phenomena and weathering processes. [ABSTRACT FROM AUTHOR]

• Freeze-thaw induced landslides (FTILs) on grasslands were systematically examined. • Soil characteristics and topography were intrinsic factors controlling FTILs. • Increased rainfall and thickening active layer were direct drivers of FTILs. • Combining multiple monitoring methods is the trend for early warning of FTILs. Landslides induced by freeze–thaw processes on grasslands are one of the major geohazards, and their scale and frequency are increasing as the global warms. Freeze-thaw induced landslides degrade surface vegetation and soil properties, reduce biodiversity, intensify landscape fragmentation, and lead to losses in economy, human and animal lives. Despite substantial progress in research on landslides, there has been little study focused on how ground freeze–thaw events affect landslides. By critically analyzing previous studies, this paper proposes a conceptual framework for the forms and types, development, dominant factors, monitoring techniques, and impact mechanisms of freeze–thaw induced landslides. Landslides are controlled by soil characteristics and topographic slope, which are major intrinsic determinants. Increased rainfall, rising temperatures, and thickening active layer due to climate change are all direct drivers of freeze–thaw induced landslides. Vegetation conditions, animal behavior interference, and wind erosion all affect the occurrence and development process of landslides by modifying vegetation cover, soil physical and chemical properties, and structure. Currently, landslide monitoring techniques have evolved rapidly with improved efficiency and accuracy, but with only few applications for freeze–thaw induced landslides. There are a variety of prediction models for landslides, but few consider freeze–thaw effects and lack field validation. The new perspective on the occurring types and dominant factors enhances theoretical understanding of the formation mechanisms, which helps further monitor and analysis of freeze–thaw induced landslides. Future studies should concentrate on the coupling mechanism of multiple factors and the development of an accurate prediction system, which will greatly benefit the understanding and early detection of freeze–thaw induced landslides. [ABSTRACT FROM AUTHOR]

• The Random Naïve Bayes (RNB) was developed to evaluate the flood susceptibility. • A repeatedly random sampling method was adopted to select negative samples for RNB. • The RNB-based most accurate classifier can achieve better classification performance. • The framework can generate stable flood susceptibility maps. • RNB is a feasible approach for natural susceptibility assessment study. Random Naïve Bayes (RNB) is a machine learning method that uses the Random Forest (RF) structure to optimize Naïve Bayes (NB). It is interesting to see whether RNB could optimize NB and achieve satisfied assessment results like RF in the flood susceptibility assessment study. RNB has rarely been used in study of using machine learning methods to spatially analyze natural disasters, and thus it was selected as the analysis method. Based on the data feasibility, 12 spatial factors that affect the occurrence and spatial distribution of floods were selected. To avoid the influence of subjective equal-interval classification method, natural breaks and quantile method were used to discretize factors with continuous values, respectively. Here, a recently proposed repeatedly random sampling method was adopted to select negative samples for RNB to generate a most accurate classifier (MAC) that was employed to compute the probability of flood occurrence in the study area. Consequently, this paper adopted the integrated framework of GIS and RNB to spatially assess the flood susceptibility using the Wanan County in China as an instance. The results demonstrated that when integrated with the repeatedly random sampling method, the MAC-based flood susceptibility maps corresponding to different factor discretization methods were similar, meaning this framework can effectively avoid the effects caused by different factor discretization methods. Also, to testify the classification performance of RNB, RF and NB were chosen to compare the classification performance with it. The results indicated the classification performance in the order of RF > RNB > NB. This means RNB is able to achieve better classification performance than NB, but it exists limitations when compared with traditional strong classifiers like RF. The findings of this paper proved that RNB is a feasible approach for natural hazard susceptibility assessment. [ABSTRACT FROM AUTHOR]

[Display omitted] • DoD models allowed to determine that landslides remaining in contact with stream channels remain active all the time. • Colluvia are removed from the toe and foot of a landslide in periods between floods, which makes these landforms active by setting them in motion at the bottom first, which propagates to the top. • Colluvia are activated within the entire landslide during both major and minor floods starting from the bottom and propagating to the top or through movement propagating in both said directions: top-to-bottom and bottom-to-top. The paper deals with the problem of the impact of river erosion on the activity level and type of colluvial movement within landslides in two study regions (Foothills and Beskidy Mts.) in the Polish Outer Carpathians. The principal goal of the study was to investigate how landslides that remain in contact with river channels function and to identify primary colluvial movement types depending on hydrometeorological conditions. Five landslides were studied, with three of them found in the Rożnowskie Foothills and two in the Beskid Niski Mts. The research was performed using terrestrial laser scanning (TLS) in the period April 2014 to November 2017. Ten measurement series were acquired during the study period. A total of 9 DEM of Difference representations (DoDs) were produced that showed both quantitative and spatial changes in the studied landslides. It was determined, based on the DoDs produced, that landslides adjacent to river channels remained continuously active due to the influence of continuously occurring fluvial erosion, although the level of activity varied, as it depended on hydrometeorological conditions. Colluvial material was set in motion within the entire landslide during floods. The recording of spatial and quantitative changes in the body of each landslide allowed to identify two key types of colluvial movement occurring during floods: (i) movement starting at the bottom and subsequently activating parts at the top (landslides: Sękówka, Boczkówka, Żabno), (ii) motion propagating in top-to-bottom and in bottom-to-top directions (landslides: Bodaki, Leszczyny). Then again, in periods between floods, colluvial material was continuously removed from the toe of each landslide, which occurred in all the studied landslides. Colluvial material became activated during these periods through movement starting at the bottom and propagating to the top. The amount of colluvium removed by streams varied depending on hydrometeorological conditions. The colluvial material carried away from the studied landslides by streams during floods comprised 60% to 90% of the volume of material removed during the entire examined period. [ABSTRACT FROM AUTHOR]

Landslides are an important means of conveying sediment from slopes to channels in steepland environments, but landsliding is a discontinuous process. This means that any single assessment in time of their contribution to the sediment cascade is of limited value. To better understand landscape dynamics and the contribution of landslides to slope–channel coupling over time, this paper quantifies connectivity over a time span of 65 years in small, steep headwater catchments in the southern Ruahine Range, New Zealand. Temporal variability in landsliding and slope–channel coupling was assessed using six sets of aerial photography flown between 1946 and 2011, from which over 6900 landslides were mapped in ArcGIS, of which up to 78% connected with the stream network. Estimates of the volume of material delivered by landslide erosion to headwater channels were based on ground survey measurements of selected landslide scars and suggest that between 1946 and 2011 over 5 million m 3 of sediment was delivered from slopes to channels in the 221 km 2 study area. Forest cover is not sufficient to prevent this erosion. These catchment systems are particularly vulnerable to high magnitude storm events, which significantly elevate landslide intensity and enhance sediment delivery, as occurred in the mid-1970s. The legacy of these events remains in these headwater channels, with ongoing consequences for stream and hazard management in and adjacent to the ranges. [ABSTRACT FROM AUTHOR]

The paper proposes a methodology, in two successive steps, to zone the susceptibility to shallow landslides in fine grained soils by means of statistical methods. The first step of the methodology, aiming at defining, calibrating and validating the statistical analysis, ends with a landslide susceptibility computational map; the second step of the methodology is employed to produce a susceptibility map for zoning purposes. This structured methodology arises from the need to distinguish, at any given scale of analysis, between the spatial discretization needed to perform the statistical computations (terrain computational units) and terrain units useful for zoning purposes (terrain zoning units). The applicability of the proposed methodology is tested, at two different scales (1:25,000 and 1:5000), in two areas of southern Italy, the test area for the larger scale being a portion of the test area used for the analysis at the smaller scale. This allows for the generalization of the obtained results through the comparison, for the same phenomena in the same geo-environmental context, of the predisposing factors at two scales of analysis. In both analyses, the relevant variables for the susceptibility assessment are: elevation zone, slope gradient, slope curvature and geology; in the analysis at large scale also the weathered rock thickness, available only at this scale, assumes a relevant role. In both cases, the aggregation of multiple terrain computational units (TCU) into a larger terrain zoning unit (TZU) works best when focal statistic techniques are used with a characteristic dimension of the area of influence equal to 16 TCUs. [ABSTRACT FROM AUTHOR]

Abstract: An 8 Richter Scale (RS) earthquake struck West Sumatra on Wednesday, 30 September 2009, at 17.16pm which led to huge number of landslides. Hence a comprehensive landslide susceptibility mapping (LSM) should be produced in order to reduce the damages to people and infrastructures. In the international landslide literature, various statistical methods such as frequency ratio (FR) and logistic regression (LR) have been widely used individually for LSM, but they have some weaknesses. FR which is able to perform bivariate statistical analysis (BSA) assesses the influence of classes of each conditioning factor on landslide occurrence. However, the correlation between the factors is mostly neglected. On the other hand, LR is able to analyze the relationship among the factors while it is not capable to evaluate the classes of each landslide conditioning factor. This paper aims to propose an ensemble method of FR and LR in order to overcome their weak points. For LSM, a landslide inventory map with a total of 87 landslide locations was extracted from various sources. Then the landslide inventory was randomly divided into two datasets 70% for training the models and the remaining 30% was used for validation purpose. The landslide conditioning factors consist of: altitude, curvature, river, SPI, rainfall, soil type, soil texture, land use/cover (LULC), peak ground acceleration (PGA), geology, slope, aspect, lineament and topographic wetness index (TWI). Four PGA of 7.5, 8, 8.6 and 9 were acquired and PGA 8 which was related to the 2009 earthquake was used to generate the model. Finally, the produced landslide susceptibility maps were validated using an area under the (ROC) curve method. For the model which was derived by PGA 8, the validation results showed 84% and 78% success and prediction rates respectively. Furthermore, the prediction rates for the models made by PGA 7.2, 8.6 and 9 are 79%, 78% and 81% respectively. The result proved the reasonable efficiency of the proposed method for earthquake induced landslide susceptibility mapping. Also the proposed ensemble method can be used in other hazard studies as it is capable to produce rapid and accurate assessment for disaster management and decision making. [Copyright &y& Elsevier]

Abstract: Landslides are one of the most widespread natural hazards that cause damage to both property and life every year, and therefore, the spatial distribution of the landslide susceptibility is necessary for planning future developmental activities. In this paper the artificial neural network (ANN) technique is tested for developing a landslide susceptibility map in Turbolo River catchment, North Calabria, South Italy. Landslides were mapped through air-photo interpretation and field surveys, by identifying both the landslide depletion zones (DZs) and accumulation zones (AZs); and relevant geo-environmental thematic layers pertaining to landslide predisposing factors were generated using air-photo interpretation, field surveys and Geographic Information System (GIS) tools. Ten predisposing factors were related to the occurrence of landslide: lithology, faults, land use, drainage network, and a series of topographic factors: elevation, slope, aspect, plan curvature, topographic wetness index (TWI) and stream power index (SPI). In order to evaluate and validate landslide susceptibility, the DZs were divided in two groups using a random partition strategy. The first group (training set) was used to prepare the susceptibility map, employing a back-propagation learning algorithm in the Idrisi Taiga software. The second group (testing set) was used to validate the landslide susceptibility model, using the confusion matrix and the receiver operating characteristic (ROC) curve. The susceptibility map was classified into five susceptibility classes: very low, low, moderate, high, and very high. About 46% of the study area falls in high to very high susceptible classes and most of the DZs mapped (87.3%) occur in the same classes. The validation results showed satisfactory agreement between the susceptibility map and the DZs locations; over 85% of the DZs of the validation set are correctly classified falling in high and very high susceptibility areas. Also, the ROC curve had shown an area under curve (AUC) value of 0.90 which demonstrates the robustness and good reliability of the landslide susceptibility model. According to these results, we conclude that the map produced by the artificial neural network is reliable and the methodology applied in the study produced high performance, and satisfactory results, which may be useful for land planning policy. [Copyright &y& Elsevier]

Abstract: A method based on dendrochronology was developed to analyse the spatial and temporal variability of landslide activity as an alternative and complement to methods such as field monitoring of landslide relief, aerial-photography, and remote sensing. The method involves a feature of wood anatomy, tree-ring eccentricity, which is used in the dating procedure. The degree of eccentricity is used as an indicator of the intensity of the mechanical stress affecting a tree stem in a certain year. The objective was to develop a mathematical indicator of tree-ring eccentricity for dating the recent dynamics of landslides. A method presented in the paper is also designed for practical application in detecting initial landslide activity and allowing the determination of triggering factors. The index developed is dimensionless and for this reason is independent of the absolute ring variations of the single trees analysed. Using reference results (from stable slopes) as thresholds in dating an objective method for detecting landslide activity was developed. The method was used in the Carpathian and Sudeten Mountains on three landslides with different sizes and geological settings. It was found that the values of eccentricity index in trees growing on stable slopes rarely exceed at ±100%, while in trees growing on landslides they can reach hundreds to thousands per cent. A spatial analysis of the eccentricity values conducted for a single landslide has revealed that the method developed allows one to identify areas of landslide activation and to observe the down- or upslope propagation of instability. A comparison of the results obtained regarding the precipitation record has shown that, by using the method that has been developed, it is possible to detect past mass-movement episodes caused by heavy, long-term rainfall as well as by single, short-lasting but torrential downpours. [Copyright &y& Elsevier]

• Earthquake–Induced Landslides in the Abruzzo region combining several factors. • Methodological tool for land planning and loss-reduction measures. • Catalogue–independent method for landslide susceptibility. • Object–image based and cluster analyses. • Statistical evaluation for a repeatable methodology and comparable results. Landslides are widespread natural phenomena that play an important role in landscape evolution and are responsible for several casualties and damages. Slope instability is linked to the combination of geological, geomorphological, and climatic factors with various triggering mechanisms; among these, seismic shaking can induce relevant changes in the landscape, leading to coseismic and post-seismic phenomena such as landslide events. The Abruzzo Region (Central Italy) is severely affected by Earthquake-Induced Landslides (EILs), linked to the geomorphological dynamics and the severe seismicity of the area. The distribution, mechanisms, and typology of landslides are strictly related to the different physiographic and geological-structural settings. This paper focuses on the realisation of an EILs susceptibility map, following a heuristic approach combined with a statistical analysis, integrated using GIS technology. This approach led to the identification of nine instability factors. These factors were analysed for the construction of thematic maps. Hence, each factor was assigned proper expert-based ranks and weights based on the critical evaluation of literature data as well as on available landslide inventories and combined in a preliminary map wherein high/low numerical values correspond to a high/low propensity of the slope to fail; furthermore, a statistical analysis of these values was performed to derive suitable susceptibility classes. Results presented herein highlight the robustness of the approach; remarkably, the applied methodology is suitable even in areas where a detailed landslide catalogue is lacking, when the same classification and weighting of available parameters is performed. The statistical analyses and the adoption of an absolute scale ranging from minimum to maximum potential values, finally, ensures the comparability of results among different study areas. Finally, this work represents a scientific and multidisciplinary tool for better defining situations that could lead to hazards (such as landslides) following an earthquake to develop sustainable territorial planning, emergency management, and loss-reduction measures. [ABSTRACT FROM AUTHOR]

Abstract: Various impacts of landslides have increased in past decades due to the rapid growth of urbanization in the developing world. Landslide effects have damaged many aspects of human life and the natural environment, and many difficulties remain for accurate assessments and evaluations. Many investigations by landslide researchers have attempted to achieve a comprehensive view of landslide consequences, however, the lack of further systematic studies have resulted in a limited view. Hence, this study considers an alternative classification theory concerning significant concepts of landslide hazard and risk through the presentation of numerous case studies. This classification method categorizes landslide impacts into two main groups as general and particular, and discusses them in an environmental and socio-economic framework. The findings illustrate that the rate of physical or socio-economic losses critically impact populated regions and civilization centers. This paper attempts to describe a systematic organizational approach in framing landslide impacts in order to more reliably describe and integrate analysis and mitigation measures. [Copyright &y& Elsevier]

Abstract: Vegetation is widely used for controlling shallow landslides. The mechanisms by which roots increase apparent soil cohesion is well documented and many values of root additional cohesion are available in the literature for different plant species. However, less information is given about the spatial variation of soil reinforcement by roots at a slope scale and its influence on slope stability, in particular in forest areas. The goal of this paper is to describe the spatial variability of root additional cohesion on two monospecific 17-y-old stands of Robinia pseudoacacia and Platycladus orientalis grown on slopes in the semiarid Loess Plateau of China, and to analyze numerically the effect of this variability on slopes stability. For this purpose, vertical trenches were dug at different distance and directions around trees situated at three different slope locations, i.e. up-, mid- and down-slope. Grids with a 10×10cm mesh were placed on vertical walls. Roots were counted within each grid cell and split according to their diameter class. Root area ratio (RAR) was estimated and compared among different positions around the trees and at three different locations along the slope. Roots tensile strength was determined with laboratory mechanical tests. RAR and root tensile strength were used as inputs in six different root reinforcement models to calculate root additional cohesion. A 2D finite element model of slope stability was developed and used to calculate the increase in factor of safety (FoS) due to root additional cohesion on rectilinear and terraced slopes. Results showed that both root tensile strength and Young''s modulus of R. pseudoacacia was about two times higher than tensile strength of P. orientalis. RAR distribution had a strong relationship with local soil moisture content measured in July during the raining season, and was significantly different with regards to tree location on the slope. The six theoretical models used to estimate the root additional cohesion gave different vertical profiles of root reinforcement distribution according to the underlying hypothesis on how forces are transferred to the roots. Theoretical analyses of slope stability showed that terraced slopes were 20% more stable than rectilinear slopes, disregarding the differences in hydrological regimes between these two terrain morphologies. Numerical sensitivity analyses also showed that the FoS reached an asymptotic value when increasing root additional cohesion. Actual additional cohesions of the two studied sites corresponded to FoS that were already close to this asymptotic values. Consequently variations of these actual root cohesions would not much affect slope stability. However it was showed that more attention should be given to the reinforcement of the bottom part of the actual slopes, where roots have a larger positive impact on the FoS. [Copyright &y& Elsevier]

Abstract: This paper presents a detailed geomorphological overview of the landforms and processes characterizing the Dessie basin, a small graben located on the western Afar Margin (Ethiopia), which is a physiographic province characterized by small, closed basins and mountain ranges produced by regional extension. Large-scale geomorphological survey and mapping of the basin allowed to point out the noteworthy morphodynamic role of the present-day slope processes, including numerous landslides of different typology and size. These processes heavily interact with the built-up area of Dessie town, one of the most important cities of Ethiopia with ca. 200,000 inhabitants, which occupies a large part of the basin floor. The potential incidence of landslides of different typology in the basin and their possible impact on the urban settlement are put in relation with the distribution of the different landform units which make up the basin surface. [Copyright &y& Elsevier]

Abstract: Landslides are common in the Polish part of the Flysch Carpathians. They are controlled mostly by lithology and tectonics of the bedrock and by climate. They are a major factor of slope transformation. Rock cliffs within deep landslides are overgrown with lichen thalli of the Rhizocarpon genus, so these cliffs may be dated using lichenometry. This paper presents the basics of lichenometry as well as its applications in geomorphological research in Poland and worldwide. Also presented are results of lichenometric dating of landslide–rockfall walls in the western part of the Polish Flysch Carpathians. The study helps to identify landslide episodes from historical times. The results obtained indicate that on the slopes studied there coexist several generations of landslide–rockfall forms of various age, including recent and active ones. [Copyright &y& Elsevier]

Abstract: Shallow landslides involving loss of blanket peat are relatively uncommon but can nevertheless be environmentally and geomorphologically significant. This paper describes a cluster of 40 shallow landslides, including significant peat failures, which occurred within 2.5 km2 on Dooncarton Mountain (Republic of Ireland) in the evening of 19 September 2003 during an exceptional rainfall event. It examines two hypotheses: (i) that the combination of topography and local soil catena characteristics were the primary site factors that led to the occurrence of most of the failures, and (ii) that anthropogenic disturbance to the slopes in the form of boundary ditches or peat-cutting activities may have contributed to three of the largest peat failures. All of the landslides were mapped and sampled within 4 months of the event. Physical, hydrological and geotechnical properties of the slope materials were determined from samples obtained from nine representative failures. Possible controls on the stability of the slopes were investigated by modelling seven of the landslides and a series of hypothetical slopes using standard limit equilibrium methods. The humified blanket peat was underlain by a dominantly sandy mineral material, including a buried soil horizon, derived from weathering of the mainly schist bedrock. Direct shear tests established the respective shear strengths to be ϕ′=50°, c′=0 (buried soil) and ϕ′=21–25°, c′=8–11 kPa (basal peat), although back-analyses suggested that the average peat cohesion was lower than this on the failed slopes. Analyses of separate slope segments of the landslides showed that the main slope convexity, where the peat cover gives way to thin peaty soil, defined the zone of minimum stability. Failure of the slope segment immediately above the convexity was controlled by the depth of peat and the hydrostatic or possibly artesian water pressures within the slopes. Thus catena characteristics coupled with local topography (gradient and peat depth) were important determinants of slope instability. Two of the failed slopes were crossed by boundary ditches but, contrary to accounts from elsewhere, stability analyses suggested that these ditches did not contribute significantly to the landslides. Stability analysis of a slope affected by peat extraction also suggested no direct causal association, but the hydrological conditions developed in the vertical tine cuts did probably contribute to a large peat slide. At other locations, therefore, similar anthropogenic factors should be incorporated in landslide hazard assessments. [Copyright &y& Elsevier]

Abstract: In the present paper, the preliminary results of a study concerning the fan dynamics in the valley of the Mucone River (Sila Massif, southern Italy) are presented. In the study area highly weathered Palaeozoic crystalline rocks crop out, ranging from residual soils to moderately weathered rocks. Because of the rugged topography and the abundance of weathered deposits, mass movements affect the great majority of the catchments. The most common instability phenomena are represented by rotational and translational slides, with subordinate rockfalls on steep to near vertical slopes. Debris-flow and debris-avalanche scars occur at the upper-middle reaches of many catchments. They are caused by mobilization of colluvial and weathered materials during large storms and are usually channelized in the main canyon of the basin. At the catchment mouth, deposition of debris-flow material occurs, contributing to the building up of fans. In order to assess the fan morphodynamics and the slope evolution in the temporal range 1955–1996, multi-year air-photo interpretation and field surveys concerning morphodynamic processes and vegetation cover features were carried out. Field observations allowed discriminating the type of fan deposits (debris-flow or water-flow dominated, mixed deposits) and the successional stages of vegetation. Results showed that fans were concerned by different activity and dissection modality, in addition to diverse evolution patterns in vegetation communities, according to the fan aspect. At the basin scale, from 1955 to 1996 changes in land use and in the disturbance regime involved a considerable expansion of natural vegetation cover at the expense of cultivated lands. Such occurrences very likely played a major role in determining a remarkable attenuation in slope instability at the basin scale and a progressive trend toward inactivity of the fans. [Copyright &y& Elsevier]

Abstract: This study examines mass movement associated with land use change, particularly deforestation, from multiple perspectives. The significance of such understanding is related to the degree of impact landsliding may cause on human settlements and economic activities, and on forest ecosystems. In this paper, the distribution of hillslope instability in the Sierra Norte, Puebla, Mexico is addressed by means of a diachronic analysis, which involves the development of vegetation indexes, as well as vegetation fragmentation derived from Landsat-5 (TM) and Landsat-7 (ETM+) satellite images from 1989 and 1999, respectively. The time period was chosen to compare vegetation cover conditions prior and after the extreme October 1999 rainfall event that triggered hundreds of slope failures in the study area. Results suggested there was a significant vegetation reduction from 1989 to 1999, which was strongly expressed by an increase of 809 km2 of bare surfaces. Additionally, areas with highest vegetation density (91–100%) decreased considerably, from 1245 to 363 km2, resulting in a net vegetation reduction of 70%. Furthermore, it was possible to highlight that landslide concentration was much higher on surfaces that were bare and had low vegetation density (0–50%), representing 85% of hillslope instability, than on surfaces having a greater density of vegetation cover. Land use change and land degradation are precursors to environmental hazards, such as mass movement events, that pose serious threats to regional population distributions and economic vitality. [Copyright &y& Elsevier]

Land degradation is a crucial issue in mountainous areas and is manifested in a variety of processes. For its assessment, application of existing models is not straightforward. In addition, data availability might be a problem. In this paper, a procedure for land degradation assessment is described, which follows a four-step approach: (1) detection, inventory and mapping of land degradation features, (2) assessing the magnitude of soil loss, (3) study of causal factors, and (4) hazard assessment by applying decision trees. This approach is applied to a case study in the Middle Mountain region of Nepal. The study shows that individual mass movement features such as debris slides and slumps can be easily mapped by photo interpretation techniques. Application of soil loss estimation models helps get insight on the magnitude of soil losses. In the study area, soil losses are higher in rainfed crops on sloping terraces (highest soil loss is 32 tons/ha/year) and minimal under dense forest and in irrigated rice fields (less than 1 ton/ha/year). However, there is high frequency of slope failures in the form of slumps in the rice fields. Debris slides are more common on south-facing slopes under rainfed agriculture or in degraded forest. Field evidences and analysis of causal factors for land degradation helps in building decision trees, the use of which for modelling land degradation has the advantage that attributes can be ranked and tested according to their importance. In addition, decision trees are simple to construct, easy to implement and very flexible in adaptations. [Copyright &y& Elsevier]

The paper deals with the relationship between the temporal occurrence of landslides and climatic changes in the Italian Dolomites since the Late glacial. After an introduction on the state of the art, with particular reference to the Alpine region, the results of recent investigations in the two study sites are illustrated. At Cortina d''Ampezzo, several landslides were dated mainly by the radiocarbon method. The most ancient landslide event there involved large rock slides, which affected the dolomitic slopes following the withdrawal of glaciers after the Last Glacial Maximum (LGM), and also slides and flows mainly occurring in pelitic materials of the valley floors (from 13,000 to 10,000 cal BP). A later series of flows occurred between 5500 and 2500 cal BP. In the Upper Badia Valley (Alta Badia), the most ancient events go back to 10,000 and 9000 cal BP, and correspond with earth flows that followed vast rotational slides affecting the bedrock up to a depth of about 50 m. More recent earth flows, involving more modest amounts of material, took place between 6500 and 2300 cal BP.By analysing the dates from the two study areas, it was possible to correlate the recorded increase of landslide activity with the climatic changes occurring at the boundary between the Late glacial and the Holocene and between the Atlantic and the Subboreal, and to compare the results with those derived from other European regions. The types and causes of landslides taking place in these two periods were substantially different, reflecting the different morphoclimatic conditions that existed in the two areas when these mass movements were triggered. Finally, notwithstanding the importance of non-climatic causes, such as geological–structural factors and possible human influences, it is concluded that many of the dated landslides can be considered as indicators of climatic change. [Copyright &y& Elsevier]

• The induced factors of the Baige landslide are comprehensively investigated. • The Baige landslide is caused by deep-seated gravitational slope deformation. • River downcutting is a prerequisite for the evolution of the Baige landslide. • Earthquake contributes to accelerating the development of the Baige landslide. On October 11 and November 3, 2018, two successive landslides happened at the same location near Baige Village in Tibet of China and dammed the Jinsha River twice. The induced factors and formation mechanism of the Baige landslide are still being questioned. In this paper, high-resolution topographic data, multi-temporal remote sensing images (including the unmanned aerial vehicle (UAV) 3D image, remote sensing, and Geographical Information Systems (GIS) techniques), rainfall data, seismic records, comprehensive field investigations, and numerical simulations are used to identify the main characteristics, the induced factors, and the formation mechanism of the event. The results show that deep-seated gravitational slope deformations play an important role in the evolution process of the Baige landslide; river downcutting is a prerequisite for the progressive evolution of the gravitational slope deformation behavior of the Baige landslide, whereas earthquake plays a catalytic role in the development of the gravitational slope deformation of the Baige landslide. The Baige landslide would be a typical case study for understanding the formation mechanism of large-scale landslides along the Jinsha River. [ABSTRACT FROM AUTHOR]

[Display omitted] • Mapping and monitoring of slow-moving landslides. • Remote Sensing, statistical and ground-based measurements have been combined. • Integration of Machine Learning and InSAR techniques for landslide risk assessment. This paper describes a novel methodology where Machine Learning Algorithms (MLAs) have been integrated to assess the landslide risk for slow moving mass movements, processes whose intermittent activity makes challenging any risk analysis worldwide. MLAs has been trained on datasets including Interferometric Synthetic Aperture Radar (InSAR) and additional remote sensing datasets such as aerial stereo photographs and LiDAR and tested in the Termini-Nerano landslides system (southern Apennines, Italy). The availability of such a wealth of materials allows also an unprecedented spatio-temporal reconstruction of the volume and the kinematic of the landslides system through which we could generate and validate the hazard map. Our analysis identifies fifteen slow-moving phenomena, traceable since 1955, whose total area amounts to 4.1 × 105 m2 and volume to ~1.4 × 106 m3. InSAR results prove that seven out of the fifteen slow-moving landslides are currently active and characterized by seasonal velocity patterns. These new insights on the dynamic of the landslides system have been selected as the main independent variables to train three MLAs (Artificial Neural Network, Generalized Boosting Model and Maximum Entropy) and derive the landslide hazard for the area. Finally, official population and buildings census data have been used to assess the landslide risk whose highest values are located in the crown area, south of Termini village, and nearby Nerano. This new methodology provides a different landslide risk scenario compared to the existing official documents for the study area and overall new insights on how to develop landslide risk management strategies worldwide based on a better understanding of slope processes thanks to the latest satellite technologies available. [ABSTRACT FROM AUTHOR]

• Accuracy, mean value and standard deviation reflect well the LSP uncertainties. • LSP uncertainties decline with the rise of attribute interval numbers (AINs) of factors. • LSP under an AIN of 20 and random forest has the lowest uncertainties. • LSP under an AIN of 4 and grey relational degree model has the highest uncertainties. • Advanced machine learning has higher LSP accuracy than heuristic and statistical models. This paper aims to explore the influences of different attribute interval numbers (AINs) in the frequency ratio (FR) analysis of continuous environmental factors and the influences of different data-based models on the uncertainties of landslide susceptibility prediction (LSP). Taking Ningdu County of China as study area, 446 landslides and nine environmental factors are first acquired. Then the FR values of environmental factors under 6 different AINs (4, 6, 8, 12, 16 and 20) and 6 different data-based models (FR model, grey relational degree (GRD), logistic regression (LR), multilayer perceptron (MLP), C5.0 decision tree (C5.0 DT) and random forest (RF)) are set to 36 different conditions. Finally, the LSP results with uncertainties under all conditions are discussed. Results show that: 1) For a certain model, the LSP accuracy gradually increases with the AINs increasing from 4 to 8, and then the increase rate decreases until the accuracy is stable with the AINs increasing from 8 to 20; 2) For a certain AIN, the LSP accuracy of RF is higher than that of C5.0 DT, followed by the MLP, LR, FR and GRD; 3) The LSP accuracy is highest under an AIN of 20 and RF and is satisfied under an AIN of 8 and RF, while is the lowest under an AIN of 4 and GRD; 4) The landslide susceptibility indexes (LSIs) under AINs of 4, 6 and 12 are significantly different from the other AINs, and the LSIs calculated by the C5.0 DT and RF are significantly different compared to the other models; 5) The mean values and standard deviations of LSIs calculated by the MLP, C5.0 DT and RF models are relatively smaller and larger, respectively, than those of the other models, indicating that the LSIs calculated by these models are more consistent with the actual landslide distribution features. [ABSTRACT FROM AUTHOR]

• Multidisciplinary approach for complex landslide study. • Geomorphologic and DEM analyses reveals western and eastern part of landslide. • ERT analysis show internal structure of eastern part of landslide. • Variable colluvium activity within the landslide. • New insight in the stages of landslide development using multidisciplinary approach. Landslides are a major threat to the environment, infrastructure and human activities, especially in mountainous and hilly areas. It is therefore important to accurately identify the mass movements triggering these mechanisms. This paper presents the impacts of lithotectonic conditions on the formation of mass movements on the example of the landslide that is located in the northern part of the Polish Outer Carpathians. In the area of the research, the ratio of the total area of landslides to the surface of the area reaches even 20%. The interpretation of a high resolution Digital Elevation Model (DEM), Electrical Resistivity Tomography (ERT) and fieldwork results allowed for the reconstruction of the landslide movements and dividing them into two areas; the western one, dominated by rotational movement, and the eastern one, featuring rotational and translational movement. It was found that the eastern part is more active now as it probably was also in the past, which might have resulted from the lithotectonic conditioned or from the impact of the flowing waters of the Dunajec River. Moreover, in the eastern part of the landslides, a small-sized ridge (55 m × 25 m) was identified, which shows greater stability in comparison with the colluvium that surrounds it. In order to explain the lower rate of movement of this landform, a morphometric analysis and research using ERT were performed. The geophysical measurements showed that the ridge comprised rock formations of greater resistivity than its surroundings. It is most likely that the only preserved sandstone packet, constituting the original secondary escarpment, became separated from the bedrock due to rotational movement. The presented studies indicate that the landslide was created due to geological and atmospheric conditions. A clear revival of landslide movements took place after significant precipitation events that last occurred in the years 2010 and 2015. The bedrock substrate due to its lithology and tectonics, facilitates these movements. It was found that the landslide studied is a complex entity, characteristic of the Polish Outer Carpathians, that has undergone multiple stages of development. The landslide is active or periodically active and, therefore, must be excluded from the planned development as well as from other forms of human activity. [ABSTRACT FROM AUTHOR]

• Landslide susceptibility mapping models in a loess area were evaluated. • ADTree, ADTree with AdaBoost, and ADTree with Bagging were applied. • The impact of each factor on the landslide occurrence was detailed analyzed. • Ensemble models enhance the accuracy of solely applied ADTree model. • ADTree with AdaBoost shows the best result in landslide prediction. Landslides are a common type of natural disaster that brings great threats to the human lives and economic development around the world, especially in the Chinese Loess Plateau. Longxian County (Shaanxi Province, China), a landslide-prone area located in the southwest part of the Loess Plateau, was selected as the study area. The main purpose of this paper is to map landslide susceptibility using Alternating decision tree (ADTree) as well as GIS-based new ensemble techniques involving ADTree with bootstrap aggregation (Bagging) and ADTree with adaptive boosting (AdaBoost). Initially, a landslide inventory map was prepared with 171 determined historical landslides events in the study area, 120 landslides (70%) were randomly selected for training dataset and the remaining 51 landslides (30%) were used for validation dataset. Subsequently, eleven landslide conditioning factors were considered in the landslide susceptibility mapping. Then, an optimization operation on selection of landslide conditioning factors was performed using correlation attribute evaluation method and Spearman's rank correlation coefficient. Afterwards, landslide susceptibility maps were generated with the three models. Finally, receiver operating characteristic (ROC) curve, area under the ROC curve (AUC) and statistical measures were applied to evaluate and validate the performance of the models. The results show success rates of the ADTree model, the ADTree with Bagging (ADTree-Bagging) model and the ADTree with AdaBoost (ADTree-AdaBoost) model were 0.872, 0.917, and 0.984, respectively, while prediction rates of the three models were 0.696, 0.752 and 0.787, respectively. In sum, the two ensemble models proposed prohibited better performance than the ADTree model did, and the ADTree-AdaBoost model was selected as the best model in the study. Hence, ensemble techniques can provide new and promising methods for spatial prediction and zonation of landslide susceptibility. [ABSTRACT FROM AUTHOR]

• Considering the change in pore-water pressure due to rainfall and earthquake. • Good performance with real landslide events in Atsuma. • Cumulative rainfall strongly affect the area of susceptibility class. • Peak ground acceleration strongly affect the area of susceptibility class. • Excess pore-water pressure is the main reason for slope instability. Increased pore-water pressure due to rainfall infiltration and cyclic loading is a major cause of slope instability. Many studies have been carried out to assess rainfall-induced landslide spatial probability based on physical models, combining hydrological models to analyze changes in pore-water pressure on slopes due to rainfall. However, the generation of pore-water pressure due to seismic loading is often disregarded during assessments of earthquake-induced landslide susceptibility. Hence, in this paper, we propose a model to assess landslide spatial probability that takes into account increased pore-water pressure during both rainfall and earthquakes. The procedure for the proposed method includes two main steps. In step 1, we analyze the change in the groundwater table due to rainfall infiltration and subsurface flow during rainfall. In step 2, the slope safety factor is calculated using an infinite slope model, considering the generation of excess pore-water pressure under cyclic loading during earthquakes. Landslide spatial probability is established based on the slope factor of safety. We validated the proposed model by analyzing rainfall-earthquake-induced landslide events occurring on September 6, 2018 in Atsuma town, Japan. According to our results, the area under the receiver operating characteristic curve of the Atsuma landslide data is 82.4% and the true-positive rate of unstable slope classification is 98.1%. The proposed model was then applied to Mt. Umyeon, Korea, to assess the spatial probability of rainfall-earthquake-induced landslide. Our model classifies the likelihood of landslide occurrence according to four susceptibility levels: high, moderate, low and very low. We also compared our results to those of previous models and show that the proposed approach may provide reasonably accurate predictions of landslide spatial probability during rainfall and earthquake events. [ABSTRACT FROM AUTHOR]

Landslides as major geo-hazards in Sweden adversely impact on nearby environments and socio-economics. In this paper, a landslide susceptibility map using a proposed subdivision approach for a large area in southwest Sweden has been produced. The map has been generated by means of an artificial neural network (ANN) model developed using fourteen causative factors extracted from topographic and geomorphologic, geological, land use, hydrology and hydrogeology characteristics. The landslide inventory map includes 242 events identified from different validated resources and interpreted aerial photographs. The weights of the causative factors employed were analyzed and verified using accepted mathematical criteria, sensitivity analysis, previous studies, and actual landslides. The high accuracy achieved using the ANN model demonstrates a consistent criterion for future landslide susceptibility zonation. Comparisons with earlier susceptibility assessments in the area show the model to be a cost-effective and potentially vital tool for urban planners in developing cities and municipalities. • An ANN model for landslide susceptibility was developed and optimized. • A novel subdivision approach for landslide hazard assessment was introduced. • Detailed discussion comparing with previous studies and projects. • A cost-effective high-resolution map for decision makers and planners was generated. [ABSTRACT FROM AUTHOR]

The absence data (samples) for landslide susceptibility mapping using data-driven methods are not available directly and often approximated by locations where no landslides have occurred. The existing methods for generating absence data cannot quantify the reliability of candidate absence data and thus such data reduce the quality of prediction. In this paper, a new approach to absence data generation, referred to as similarity based sampling, was proposed for landslide susceptibility mapping using data-driven methods. First, the reliability of candidate absence data is quantified based on the dissimilarity in environmental conditions (covariate conditions) between the absence data and the presence data (which are the landslide occurrences). The absence data whose reliability value is higher than a given threshold were selected to be used. The proposed approach was validated through its application to three data-driven methods (i.e. logistic regression, support vector machine and random forest) for landslide susceptibility mapping. A case study was conducted in the Youfang catchment in southern Gansu Province of China. Ten groups of absence data were generated each corresponding to one of the ten different thresholds of reliability ranging from 0.0 to 0.9. The results show that the prediction accuracy of the data-driven methods rose when the threshold increased from 0.0 to 0.5, but the accuracy decreases as the threshold continues to increase after 0.5, that is, from 0.5 to 0.9. The best performance was obtained when the threshold was 0.5. The proposed method was compared with existing methods for absence data generation (i.e. buffer controlled and target space exteriorization). These results show that the similarity-based approach has a better performance than these existing methods for landslide susceptibility mapping using data-driven methods. • Similarity Based Sampling is proposed to generate absence data. • Landslide susceptibility mapping using statistic method • Prediction efficiency index was used to evaluate the accuracy of model. [ABSTRACT FROM AUTHOR]

Alluvial fans occur in all climatic and tectonic environments. However, most descriptions of fan features and sediments have focused on arid and semiarid regions. This paper describes the sediments and soil ages on 63 alluvial fans in a subhumid climate (mean annual precipitation of 45–52 cm). SSURGO soil data were merged with geologic and topographic data in the ArcMap© GIS platform to develop a series of maps showing variations across fan surfaces in sediment textures and surface stability ages. Particle size data (percent cobble and percent total gravel) from the upper 150 cm of sediments cluster into six textural groups that are aligned along a trend of decreasing gravel percentage (decreasing stream capacity) and decreasing cobble percentage (decreasing stream competency). The groups of higher cobble and gravel percentages extend from fan apex to toe in both the shallow (<50 cm depth) and deeper (>100 cm depth) layers with groups of lower cobble and gravel percentage occurring along fan margins in the shallow (<50 cm depth) layer. The thickness of B and Bt horizons from representative soil profiles were used to calculate proportional soil ages based on 10Be residence times in loessial Bt horizons and correlation of gravelly fan soils to similar gravelly soils on nearby Pinedale outwash. This approach identified six stability episodes since the end of the Bull Lake beginning at ~100 ka, ~38 ka, ~27 ka, ~16 ka, ~10 ka, and <2 ka. The proportional soil ages correlate closely with fan chronologies constrained by TL and OSL ages in nearby areas. Soil ages and sediment textural groups differed between fan populations along the mountain front with active faulting and those along the stable mountain front. Fan stability surfaces older than 16 ka are preserved only at fault termini. Holocene faulting resulted in fans with (1) coarser sediments, (2) younger sediments, (3) progressive onlap of younger sediments, (4) the absence of relic fan surfaces, landslides and colluvium at the mountain front, and (5) the onlap of alluvial fans onto the floodplain of the axial stream. Sediment pulses related to individual fault events could not be definitively identified because of concurrent climatic changes. The study demonstrates that both climatic and tectonic conditions influence sediment textures and fan surfaces ages. • Sediments cluster into six groups reflecting progressive changes in stream power • The same high capacity/high competency textural groups dominate all fan sediments • Six fan-surface stability episodes since Bull Lake (100, 38, 27, 16, 10, and < 2 ka) • Relict fans >38 ka only occur at fault termini; elsewhere fan surfaces are <16 ka • Identified fan-stability episodes are regional and correspond to climate changes [ABSTRACT FROM AUTHOR]