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We propose a simple method to estimate the surface displacement of earth slides. It is based on the assumptions that earth slides move by sliding along a discrete basal-slip surface and extensional structures, which commonly characterize their depletion zone, completely accommodate the occurred displacement. The proposed method is based on the reconstruction of the cross-sectional geometry of structures crossed by an arbitrary chosen longitudinal profile, aligned with the direction of the movement. Structure geometry reconstruction is completed using high-precision GPS survey and the reconstructed geometry is then used as basis to measure horizontal and vertical components of the displacement accommodated by each single extensional structure. Total horizontal and vertical earth-slide displacements are calculated as the sum of displacements accumulated at each single structure. We test the method at the Summonte earth slide in southern Italy using real-time kinematic GPS field mapping. Results from our estimation were validated considering a single displacement vector derived from the direct and indirect measurement of the position of an isolated tree located below the extensional zone of the slide. [ABSTRACT FROM AUTHOR]

The main aim of this study is the description and the analysis of the monitoring strategies implemented within local landslide early warning systems (Lo-LEWS) operational all around the world. Relevant information on 29 Lo-LEWS have been retrieved from peer-reviewed articles published in scientific journals and proceedings of technical conferences, books, reports, and institutional web pages. The first part of the paper describes the characteristics of these early warning systems considering their different components. The main characteristics of each system are summarized using tables with the aim of providing easily accessible information for technicians, experts, and stakeholders involved in the design and operation of Lo-LEWSs. The second part of the paper describes the monitoring networks adopted within the considered systems. Monitoring strategies are classified in terms of monitored activities and methods detailing the parameters and instruments adopted. The latter are classified as a function of the type of landslide being monitored. The discussion focuses on issues relevant for early warning, including appropriateness of the measurements, redundancy of monitoring methods, data analysis, and performance. Moreover, a description of the most used monitoring parameters and instruments for issuing warnings is presented. [ABSTRACT FROM AUTHOR]

Recent investigations have sought to understand the spatial-temporal distribution of landslides in Teziutlán, Puebla, a municipality historically affected by landslides. The latest initiative, under the umbrella of the ICL-IPL Project “Landslide disaster risk communication in mountain areas,” was the publication of a book of Atlas type comprising a collection of 142 maps and their corresponding explanatory texts that included a context analysis of landslide disaster risk drivers at various scales, from regional to local. This paper aims to recognise and address the necessity to further enhance the guiding principle of the Sendai Framework for Disaster Risk Reduction to focus on the understanding of disaster risk drivers at local level, for the determination of measures to reduce disaster risk. We present an initial contribution to promote landslide disaster risk awareness in the urban area of Teziutlán by providing to the community direct access to maps of landslide disaster risk at local scale; this is a first step towards the establishment of a robust strategy to communicate landslide risk in the long term. Effective implementation calls for decreasing vulnerability and exposure. Beyond contexts of vulnerability reflected by social, economic, cultural, political, and institutional conditions, it may be difficult to picture the spatial interactions of exposure of communities, assets, and the environment because the means of analysing spatial relationships between society and nature are not commonly available in mountain areas. Therefore, for people to better understand risk, maps of landslide susceptibility and risk exposure present a good way for the inhabitants to familiarise themselves with the spatial context of the dynamics in which they are immersed. [ABSTRACT FROM AUTHOR]

The primary objective of the current study is to better understand landslide hazards in reservoir areas and the mechanism of reservoir landslides using different methods. To achieve this main objective the Xiangjiaba Reservoir area, Southwest China is taken as a case study. First, landslide mapping and spatial analysis in the Xiangjiaba Reservoir area were conducted by air photo interpretation (API), followed by field checks. Second, landslide susceptibility mapping was done using the information value method and a logistic regression model. Through remote sensing interpretation coupled with field investigations, 62 landslides, 38 rockfall deposits, and 10 bedrock deformed bodies along the banks of the Xiangjiaba Reservoir area which have effects on the reservoir and resettlements were considered, with a total volume of 32,228 x 104 m³, 19,916 x 104 m³, 1,072 x 104 m³, respectively. Geological characteristics of the reservoir slopes and spatial prediction indicate that after filling the reservoir to a normal level of 380 m, 23 landslides among the total identified landslides are stable, six landslides have been mitigated, and all of the rest are unstable. Thirty-two rockfall deposits are still in a stable state, and the rest are unstable. By overlaying the existing landslide and the susceptibility map, it is found that 0.36% of the existing landslides are in areas of very low susceptibility, 1.77% are in areas of low susceptibility, 4.14% are in areas of moderate susceptibility, 6.04% are in areas of high susceptibility, and 13.37% are in areas of very high susceptibility. [ABSTRACT FROM AUTHOR]

This study attempts to compare popular statistical methods (linear, logarithmic, quadratic, power and exponential functions) with machine learning methods (multi-layer perceptron (MLP), radial base function (RBF), adaptive neural-based fuzzy inference system (ANFIS) and support vector machine (SVM)) for simulating the volume of landslides based on their surface area (VL ~ AL) in the Kurdistan province, Iran. Performances of the models were validated using some commonly error functions including the Adjusted R 2 , F-test and AIC (Akaike Information Criteria). The results showed that the power model demonstrates the best performance compared to other statistical methods whereas the ANFIS model outperforms other machine learning approaches. Furthermore, the comparative results showed that machine learning methods indicate better performances than simple statistical methods for simulating the volume of landslides in the study area. In practice, the outputs of this research can help managers and investigators decrease the cost of field surveys and measurements of volumes of landslides in landslide hazard management projects. [ABSTRACT FROM AUTHOR]

Scientific literature is becoming daily more and more abundant. Scientific and professional journals as primary information sources are competing to each other to attract readership. Their position (ranking, visibility, attractiveness, prestige) in scientific community can be measured by using different journal bibliometric and scientometric parameters, journal impact factor being only one of them. Springer Nature publishes the journal Landslides: Journal of the International Consortium on Landslides since 2004. Being examined in the past by different authors from bibliometric and editorial point of view, this review on the journal's achievements confirmed the high ranking of this journal in the fields of geological and geotechnical engineering and engineering geology. Strong and weak points are discussed from the bibliometric point of view, stressing the need for higher internationality of co-authorship of published articles in order to be true international journal. Continuous publishing and the move to a monthly journal in 2018 will eventually increase journal's h-index and cited half-life of citations, but further editorial efforts should be directed to attract excellent review papers and focused technical notes to increase cites per paper. Until now, the journal Landslides is the foremost journal in the field of landslide disaster risk reduction, and the top young international journal in the field of geological engineering and engineering geology. [ABSTRACT FROM AUTHOR]

The ANNEX to the 2017 Ljubljana Declaration on Landslide Risk Reduction described in the 'Preface' section of this issue is the list of participants (by organizations) in the Fourth World Landslide Forum. In this article, emphasis is put on this list of organizations as they are expected to be the key components for the Fifth World Landslide Forum 2020 in Kyoto, Japan. The participants in the Fourth World Landslide Forum 2017 adopted the 2017 Ljubljana Declaration on Landslide Risk Reduction. They further endorsed the concept of the Kyoto 2020 Commitment for Global Promotion of Understanding and Reducing Landslide Disaster Risk. The commitment aims to establish a long-term, wider, and stronger network after WLF5 2020 among three membership categories, namely, the International Consortium on Landslides (ICL) full members/supporters/associates, ICL-supporting organizations (UN and international global organizations) and ICL-supporting governments, and ISDR-ICL Sendai Partnerships 2015-2025. This article introduces three categories of ICL memberships and calls for participation. [ABSTRACT FROM AUTHOR]

Despite continuing technological advancement in hazard and vulnerability assessment, risk modelling and hazard mitigation techniques, losses to disasters associated with natural hazards continue and in some cases are increasing across Europe and worldwide. This paper focuses on the need to bridge the gap between technical solutions and the sociopolitical contexts in which these are produced, to better understand and create more effective risk management regimes. We do so with application of the science-policy co-production frame to landslide risk management in Italy. The methodology deployed included a desk study informed by semi-structured interviews carried out with selected key stakeholders at national, regional and municipal level. We propose a normative and analytical framework for transferring co-production into natural hazard research by presenting a matrix identifying four contexts within which co-production may unfold. The matrix is based on two axes, which distinguish between innovation and its absence in science and policy domains. We examine several examples of co-production, such as the water-soil integrated approach to risk management or the implementation of hazard/risk assessment. The results highlight that the insulation of science from the institutional context within which knowledge is produced and used is a very problematic issue. This often hinders the implementation of desirable policies and undermines the effectiveness of interventions. Moreover, innovation in science and policy does not automatically result in successful solutions for landslide risk management. Finally, results confirm the utility of co-production but also highlight methodological challenges associated with the introduction of this new conceptual paradigm into the well-structured communities of scientists and policy-makers. [ABSTRACT FROM AUTHOR]

This work provides a multi-temporal and spatial investigation of landslide effects in the San Fratello area (Messina province within the Sicily region, Italy), by means of C-band and X-band Persistent Scatterer Interferometry (PSI) data, integrated with in situ field checks and a crack pattern survey. The Sicily region is extensively affected by hydrogeological hazards since several landslides regularly involved local areas across time. In particular, intense and catastrophic landslide phenomena have recently occurred in the San Fratello area; the last event took place in February 2010, causing large economic damage. Thus, the need for an accurate ground motions and impacts mapping and monitoring turns out to be significantly effective, in order to better identify active unstable areas and to help proper risk-mitigation measures planning. The combined use of historical and recent C-band satellites and current X-band Synthetic Aperture Radar sensors of a new generation permits spatially and temporally detection of landslide-induced motions on a local scale and to properly provide a complete multi-temporal evaluation of their effects on the area of interest. PSI ground motion rates are cross-compared with local failures and damage of involved buildings, recently recognized by in situ observations. As a result, the analysis of landslide-induced movements over almost 20 years and the validation of radar data with manufactured crack patterns, permits one to finally achieve a complete and reliable assessment in the San Fratello test site. [ABSTRACT FROM AUTHOR]

Landslide and especially rockfall hazard widely occurs along cut slopes in mountainous regions. The risk assessment of mass movements is still one of most challenging problems in slope engineering geology. We propose a routine method to assess rock slide and rockfall risk of cut slopes essentially based on slope properties and rock mass structure. The method is a lean low-cost path to a risk estimate. Rock block size is simplified into two classes, {small} with a volume less than 1.0 m and {large}, greater than 1.0 m. Studies indicate that for a slope with n small-medium rock blocks, the possibility of rockfalls can be estimated by 1 − (1 − P), in which P is the likelihood of one {small} rock block fall. The possibility of other types of mass movement can be determined by the first-order second-moment (FOSM) method. Based on this, an exponent equation was adopted to evaluate the consequence and the risk. The methodology is demonstrated by a case study from the mountains of Mentougou district, Beijing, China. Based on the investigations of geological conditions (i.e., lithology, weathering and rock mass structure) and some historical mass movement data of the cut slopes, a zonation map for rockfall and rock slide risk along a 17-km section of a road is presented. The result is supported by mass movement event observations in the recent 2 years. [ABSTRACT FROM AUTHOR]

Logistic regression studies which assess landslide susceptibility are widely available in the literature. However, a global review of these studies to synthesise and compare the results does not exist. There are currently no guidelines for the selection of covariates to be used in logistic regression analysis, and as such, the covariates selected vary widely between studies. An inventory of significant covariates associated with landsliding produced from the full set of such studies globally would be a useful aid to the selection of covariates in future logistic regression studies. Thus, studies using logistic regression for landslide susceptibility estimation published in the literature were collated, and a database was created of the significant factors affecting the generation of landslides. The database records the paper the data were taken from, the year of publication, the approximate longitude and latitude of the study area, the trigger method (where appropriate) and the most dominant type of landslides occurring in the study area. The significant and non-significant (at the 95 % confidence level) covariates were recorded, as well as their coefficient, statistical significance and unit of measurement. The most common statistically significant covariate used in landslide logistic regression was slope, followed by aspect. The significant covariates related to landsliding varied for earthquake-induced landslides compared to rainfall-induced landslides, and between landslide type. More importantly, the full range of covariates used was identified along with their frequencies of inclusion. The analysis showed that there needs to be more clarity and consistency in the methodology for selecting covariates for logistic regression analysis and in the metrics included when presenting the results. Several recommendations for future studies were given. [ABSTRACT FROM AUTHOR]

The San Vicente volcano in central El Salvador has a recurring and destructive pattern of landslides and debris flows occurring on the northern slopes of the volcano, and in recent memory, there have been at least seven major destructive debris flows. There has been no known attempt to study the inherent stability of these slopes and determine the factors that might lead to slope instability. Past events on the volcano were used to perform a 2D slope stability back analysis and to estimate the unknown model parameters. This analysis confirmed that the surface materials of the volcano are highly permeable and have very low shear strength. Additionally, the analysis provided insight into the groundwater table behavior during a rainstorm. Slope geometry, rainfall totals and initial groundwater table location were found to have the greatest effect on stability. A methodology is outlined for creating a stability chart to be used during rainfall events for monitoring slope stability. This chart could be used by local authorities in the event of a known extreme rainfall event to help make evacuation decisions. Finally, recommendations are given to improve the methodology for future application in other areas as well as in central El Salvador. [ABSTRACT FROM AUTHOR]

The wired and wireless monitoring system installed in the Rebaixader catchment detected six debris flows and 11 debris floods between 2009 and 2012. Apart from results directly related to the processes, many experiences associated with monitoring were collected. Debris flows and debris floods showed clear differences in both the recorded data and field observations. The distinction was especially visible in the stage measurements and the ground vibration registered by the most downstream geophone. At this geophone, a positive relation between the maximum ground vibration and the volume was also observed. The triggering of most events was associated with short, high-intensity rainstorms in summer, but some were also generated in spring, when the melting of snow cover and frozen soil played an additional role. A positive correlation between the volume and both the amount and the intensity of the triggering rainfall was observed. Regarding technical aspects, a switch between a 'no-event' mode with a low sample rate and an 'event' mode with a fast sampling was particularly useful at the station that register the passing of a flow. In addition, the stations, which most recently were installed at Rebaixader, apply wireless devices because wireless techniques include multiple advantages against standard wired systems. Although recorded data or even video images provide detailed information on the debris-flow behavior, we strongly recommend periodic field surveys along the entire torrent to verify and improve the interpretation obtained from the monitoring system. [ABSTRACT FROM AUTHOR]

Throughout the history, many lives have been lost due to landslides. Understanding the process of human flight during landslide events is important in assessing the risks posed by future landslides. This study proposes a model for simulating human flight from a quick shallow landslide along a road, quantifies the flight success rate, and identifies the crucial variables that impact flight efficiency. A questionnaire survey was undertaken along a stretch of highway near Yingxiu, China to collect information regarding human responses and behavior in the face of landslide events. The factors influencing human flight are classified into factors related to the evacuees, the landslide intensity, and the flight path. Subsequently, a flight model is proposed to simulate the movements of people randomly located along a road threatened by landslides. Various components of 'available time' and 'demand time' for escaping from the landslide affected area are treated as random variables. Based on this model, probability analysis is conducted to estimate the flight success rates of the people at risk when fleeing from landslides of various intensities. Sensitivity analysis shows that the pre-failure time and the response time are the most important factors in the flight process. Finally, comparison between the flight success rates from two existing methods and those from the new model is made. [ABSTRACT FROM AUTHOR]

Disruption of segments of roads can have a significant impact on the vulnerability of the entire network. Natural disasters are frequent causes of disruptions of this kind. This article focuses on determining the risk of road disruptions due to landslides. Our approach is based on methodology widely used in the field of epidemiology. We had available data on the location of the landslides, the road network and a list of the disrupted road segments. With the use of a 2 × 2 table, we determined the relationship between landslide data and road segment disruptions and derived the risk coefficient based on the number of landslides in the vicinity of the road and its length. The result is a disruption risk map with risk coefficients ranging from 0 to 47.94. In order to distinguish the most risky segments, we calculated a threshold of 12.40 with the use of a risk breakdown in a group of segments without damage. Nineteen percentage (402 km) of the road network in the Zlín region (Czech Republic), where the methodology was applied, is located beyond this threshold. The benefits of this approach stem from its speed and potential to define the most risky areas on which a detailed geomorphologic analysis can be focused. [ABSTRACT FROM AUTHOR]

The occurrence of landslides in Moa poses a serious threat to the industry, communities, socio-economic activities and the environment. The objective of this research is to assess and map the risks generated by the occurrence of landslides in the area by applying the Geographic Information Systems (GIS). For a methodological guidance, the guideline dated 2012 prepared by the National Risk Management Group was used to conduct the landslide hazard, vulnerability, risk analysis on the ground. As a result, this work produced a map indicating the overall landslide dangerousness in Moa on a 1:100 000 scale. This map is one more risk management and mitigation tool in the territorial organization. [ABSTRACT FROM AUTHOR]

Landslide risk assessment is often a difficult task due to the lack of temporal data on landslides and triggering events (frequency), run-out distance, landslide magnitude and vulnerability. The probability of occurrence of landslides is often very difficult to predict, as well as the expected magnitude of events, due to the limited data availability on past landslide activity. In this paper, a qualitative procedure for assessing the exposure of elements at risk is presented for an area of the Apulia region (Italy) where no temporal information on landslide occurrence is available. Given these limitations in data availability, it was not possible to produce a reliable landslide hazard map and, consequently, a risk map. The qualitative analysis was carried out using the spatial multi-criteria evaluation method in a global information system. A landslide susceptibility composite index map and four asset index maps (physical, social, economic and environmental) were generated separately through a hierarchical procedure of standardising and weighting. The four asset index maps were combined in order to obtain a qualitative weighted assets map, which, combined with the landslide susceptibility composite index map, has provided the final qualitative landslide exposure map. The resulting map represents the spatial distribution of the exposure level in the study area; this information could be used in a preliminary stage of regional planning. In order to demonstrate how such an exposure map could be used in a basic risk assessment, a quantification of the economic losses at municipal level was carried out, and the temporal probability of landslides was estimated, on the basis of the expert knowledge. Although the proposed methodology for the exposure assessment did not consider the landslide run-out and vulnerability quantification, the results obtained allow to rank the municipalities in terms of increasing exposure and risk level and, consequently, to identify the priorities for designing appropriate landslide risk mitigation plans. [ABSTRACT FROM AUTHOR]

This paper analyses the dominant mechanisms of slope failures and identifies potential obstacles to landslide-hazard reduction at the Iva Valley area, Enugu, Nigeria. The landscape is replete with landslide scars and gullies of varied sizes and the slope deposits comprise unconsolidated, friable sands inter-bedded with thin units of montmorillonitic claystone. Forty-three landslide events were identified in the study area with most being shallow, short run-out movements with slip-surface depth <2 m. The study found the landslides mainly occur in the beginning of rainy season characterized by short duration, high intensity rainfall. An integrated approach comprising field mapping, laboratory tests and numerical analyses reveals that the barren nature of the slopes prior to the outset of rainy season, high rainfall intensity, erosion, overgrazing, soil characteristics and the site's unique lithologic sequence are the main causes of instability. Shearing tests under several conditions showed that the soils strongly strain-soften until low steady-state strength is achieved. A computer code, based on this strength reduction technique, used input parameters obtained from the field and laboratory studies to simulate a landslide with similar structure, travel distance and distribution area. It is noted that urbanization has gradually increased the vulnerability of the society's poor to landslide hazards as they now erect unplanned residence (tents and blocks) on the slopes. This work is part of a regional study aimed at finding ways of protecting the vulnerable by generating data that could be used to build future landslide susceptibility map. [ABSTRACT FROM AUTHOR]

Landslides are a hazard for humans and artificial structures. From an ecological point of view, they represent an important ecosystem disturbance, especially in tropical montane forests. Here, shallow translational landslides are a frequent natural phenomenon and one local determinant of high levels of biodiversity. In this paper, we apply weighted ensembles of advanced phenomenological models from statistics and machine learning to analyze the driving factors of natural landslides in a tropical montane forest in South Ecuador. We exclusively interpret terrain attributes, derived from a digital elevation model, as proxies to several driving factors of landslides and use them as predictors in our models which are trained on a set of five historical landslide inventories. We check the model generality by transferring them in time and use three common performance criteria (i.e. AUC, explained deviance and slope of model calibration curve) to, on the one hand, compare several state-of-the-art model approaches and on the other hand, to create weighted model ensembles. Our results suggest that it is important to consider more than one single performance criterion. Approaching our main question, we compare responses of weighted model ensembles that were trained on distinct functional units of landslides (i.e. initiation, transport and deposition zones). This way, we are able to show that it is quite possible to deduce driving factors of landslides, if the consistency between the training data and the processes is maintained. Opening the ‘black box’ of statistical models by interpreting univariate model response curves and relative importance of single predictors regarding their plausibility, we provide a means to verify this consistency. With the exception of classification tree analysis, all techniques performed comparably well in our case study while being outperformed by weighted model ensembles. Univariate response curves of models trained on distinct functional units of landslides exposed different shapes following our expectations. Our results indicate the occurrence of landslides to be mainly controlled by factors related to the general position along a slope (i.e. ridge, open slope or valley) while landslide initiation seems to be favored by small scale convexities on otherwise plain open slopes. [Copyright &y& Elsevier]

The paper focuses on the assessment of landslide hazard and risk along or across the Trans Adriatic Pipeline (TAP) natural gas pipeline project in Albania. TAP is a natural gas pipeline that will transport gas from the Caspian Sea to Europe, crossing Northern Greece and Southern Albania. It has long been recognised that landsliding is a major factor for TAP's pipeline route selection in mountainous regions, especially the challenging area of central Albania. Experience from similar major pipelines has shown that hazard avoidance is generally the most cost- and time-efficient strategy to minimise the landslide risk since geohazard-related decision-making is usually risk-based. For landslides, the risk profile is expected to be dominated by the upslope expansion of existing landslides, resulting in a loss of ridge crest (where the Right of Way (RoW) is usually located), possibly leading to pipeline rupture. However, it is still possible that new landslides could develop under static and/or seismic conditions, especially on steep ridge flanks along the route. An expert determination approach was adopted to define a consensus for the estimate of the risk (i.e., chance of rupture) for the pipeline at eighty-two (82) identified landslide sites in Albania, to identify "hot spots" along the route, where risk-reduction measures could be prioritised. Ten landslides were characterised as "High Risk", fifteen as "Medium Risk" and nineteen as "Low Risk". Following this risk assessment, two large re-routings, as well as several local re-routings, were considered. Further investigation was required to identify the site-specific geotechnical conditions and probable remedial measures in cases where landslides could not be avoided by rerouting. [ABSTRACT FROM AUTHOR]

Loess environments such as the Chinese Loess Plateau are geologically fragile because of their great thickness, loose structure, crisscrossing ravines and gullies, broken terrain, dry climate, severe erosion and unevenly distributed rainfall. As a consequence, loess areas are highly prone to environmental problems and geological hazards. The geological structure of the loess is one of the main factors that controls occurrence of these geohazards. This study investigated the mechanism of loess landslides and their sliding control mode from the perspective of their geological structure. Using this mechanism, a three-dimensional geological model of loess landslides was established. The study shows that the structural planes in loess divide a complete slope into separate blocks, which enables the fast and deep infiltration of surface water via seepage channels and reduces the shear strength of the soil mass, inducing landslides. The development and formation of loess landslides are primarily controlled by structural planes and influenced by infiltrated water softening the structural plains. Various types of structural planes may combine and form structural bodies of different types and scales, which control the type, depth and scale of loess landslides. [ABSTRACT FROM AUTHOR]

Landslides cause damages to land and infrastructure and pose serious threat to human survival. To prepare a landslide susceptibility map of the region in Longnan, City Gansu Province, with a 330-kV transmission line, 10 parameters were selected by correlation analysis and sensitivity analysis from initial 18 and five different methods were used, including analytical hierarchy process (AHP), information value (IV), fractal theory (FT), back propagation neural network (BPNN), support vector machine (SVM). The susceptibility maps were validated through receiver operating characteristic (ROC) and cumulative landslides percentage curves based on 77 existing landslide events. The results indicate that BPNN and SVM model are most accurate, time-saving and easily implemented. All of the five methods accurately predict the spatial distribution of landslides and can be well applied to landslide susceptibility mapping. What needs to be emphasized is that the machine learning methods have the advantages of high efficiency, accurate prediction, time-saving, convenient implementation, which are relatively new and better evaluation models of susceptibility. [ABSTRACT FROM AUTHOR]

The main objective of the study was to develop a novel expert-based approach in order to construct a landslide susceptibility map for the Island of Lefkada, Greece. The developed methodology was separated into two actions. The first action involved the construction of a landslide inventory map and the second the exploitation of expert knowledge and the use of fuzzy logic to produce a landslide susceptibility map. Two types of movements were analyzed: rapid moving slides that involve rock falls and rock slides and slow to very slow moving slides. The landslide inventory map was constructed through an evaluation procedure that involved the use of a group of experts, who analyzed data acquired from remote sensing techniques supplemented by landslide records and fieldwork data. During the second action an expert-driven model was developed for identifying the tendency of landslide occurrences concerning both types of movements. A set of casual variables was selected, namely: lithological units, slope angle, slope orientation, distance from tectonic features, distance from hydrographic network and distance from road network. The performance and validation of the developed model were compared with models that are constructed on the bases of each expert’s judgment. The results proved that the most accurate and reliable outcomes are obtained from the aggregated values assigned by the group of experts and not from the individual values assigned by each expert. The area under the receiver operating characteristic curves for the models constructed by the expert’s group was 0.873 for prediction curves of rapid moving slides and 0.812 for prediction rate curves of slow to very slow moving slides, respectively. These values were much higher than those obtained by each expert. From the outcomes of the study it is clear that the produced landslide susceptibility maps could provide valuable information during landslide risk assessments at the Island of Lefkada. [ABSTRACT FROM AUTHOR]