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This paper shows the results of a study aimed at quantitatively estimating—in terms of direct (repair) costs, at large scale (1:5000)—the slow-moving landslide risk to a road network assumed as undamaged as well as the consequences to the same network in damaged conditions. The newly conceived methodological approaches address some challenging tasks concerning (i) the hazard analysis, which is expressed in terms of probability of occurrence of slow-moving landslides with a given intensity level that, in turn, is established based on empirical fragility curves, and (ii) the consequence analysis, which brings to the generation of time-dependent vulnerability curves. Their applicability is successfully tested in a case study in the Campania region (southern Italy) for which both very high-resolution DInSAR data and information gathered from in situ surveys on the severity of damage sustained by the selected road sections are available. Benefits associated with the use of the obtained results in informed decision-making processes are finally discussed.

Landslide susceptibility assessment is vital for landslide risk management and urban planning, and the scientific community is continuously proposing new approaches to map landslide susceptibility, especially by hybridizing state-of-the-art models and by proposing new ones. A common practice in landslide susceptibility studies is to compare (two or more) different models in terms of AUC (area under ROC curve) to assess which one has the best predictive performance. The objective of this paper is to show that the classical scheme of comparison between susceptibility models can be expanded and enriched with substantial geomorphological insights by focusing the comparison on the mapped susceptibility values and investigating the geomorphological reasons of the differences encountered. To this aim, we used four susceptibility maps of the Wanzhou County (China) obtained with four different classification methods (namely, random forest, index of entropy, frequency ratio, and certainty factor). A quantitative comparison of the susceptibility values was carried out on a pixel-by-pixel basis, to reveal systematic spatial patterns in the differences among susceptibility maps; then, those patterns were put in relation with all the explanatory variables used in the susceptibility assessments. The lithological and morphological features of the study area that are typically associated to underestimations and overestimations of susceptibility were identified. The results shed a new light on the susceptibility models, identifying systematic errors that could be probably associated either to shortcomings of the models or to distinctive morphological features of the test site, such as nearly flat low altitude areas near the main rivers, and some lithological units.

This paper presents rainfall-induced landslide thresholds and predicts landslide hazard in Kuala Lumpur metropolitan city and surrounding areas. Landslide events from 2000 to 2012 were collected. The long and short antecedent rainfall days were prepared for landslide and non-landslide days simultaneously. First, threshold analysis was conducted by using data obtained from rainfall stations located in highly urbanized areas of Kuala Lumpur metropolis. Six rainfall gauges were selected, and the study area was divided into six zones according to rainfall gauges: Taman Desa Station (TD-KL), Genting Klang (GK-KL), LDG Edinburgh Station (LDGE-KL), SG Raya Hulu Langat Station (SRHL-Slg), Puchong Drop Station (PD-Slg), and Bukit Antarabangsa (BTA-Slg). After the threshold analysis was conducted for different periods (10, 15, and 30 days) in each station, reliability index test was conducted to optimize the best threshold that limits the predicted events along the study period for each region. Second, the threshold analysis results were used as input in the Poisson probability model to estimate landslide temporal probability (P T). Third, the spatial probability (P S) analysis was prepared by using the evidential belief function multiplied by the P T to obtain the hazard maps for 1-, 3-, and 5-year scenarios. Finally, a validation process was conducted to test the prediction performance of the resultant hazard map for a 1- and 2-year prediction by using the landslide inventory of 2012 to early 2014, which was not included in the modeling of the hazard map. Results showed a valid correlation between the high and moderate hazardous areas for the six zones. The predicted hazard maps indicated a quantitative assessment of the prone areas and proved to be a valid disaster management tool. The produced hazard maps may play a vital role as input component in risk analysis.

The results of the first investigation on historical landslides that occurred in Nicaragua before 1990 are presented. The paper shows how the analysis of historical documents can provide important information about the type and the temporal and spatial distribution of landslide events, especially for countries where landslide investigation is a young discipline. The methodology included research of historical sources at national institutions, public libraries, international journals, the Internet, and the collection of original texts from newspapers and their transcription in analog format. Analysis and interpretation of the data was performed, followed up by the digitalization of landslide spatial locations using the software ArcGIS and the integration of the landslide attributes in a structured query language (SQL) server database. Finally, the analysis of the stored data was done using SQL interactive queries. The type and quality of the historical sources available are described. Limitations and problems, common in the preparation of any historical catalogue, and possible sources of error derived from the collection, interpretation, and storage of the data are discussed as well. One hundred thirty-five historical landslides were identified. The study shows that these events occurred mostly in combination with other natural phenomena. The collected data were used to construct a geo-referenced inventory of historical landslide events, including information about damage and human losses caused by them. The inventory provides the basis for a more comprehensive landslide hazard assessment in Nicaragua.

This paper explains the procedure for the generation of a landslide risk index map at national level in Cuba, using a semi-quantitative model with ten indicator maps and a cell size of 90 × 90 m. The model was designed and implemented using spatial multi-criteria evaluation techniques in a GIS system. Each indicator was processed, analysed and standardised according to its contribution to hazard and vulnerability. The indicators were weighted using direct, pairwise comparison and rank-ordering weighting methods, and weights were combined to obtain the final landslide risk index map. The results were analysed per physiographic region and administrative units at provincial and municipal levels. The Sierra Maestra mountain system was found to have the largest concentration of high landslide risk index values while the Nipe–Cristal–Baracoa system has the highest absolute values, although they are more dispersed. The results obtained allow designing an appropriated landslide risk mitigation plan at national level and to link the information to the national hurricane early warning system, allowing also warning and evacuation for landslide-prone areas.

Recently, design of public works in a landslide area trends to demand evaluation for landslide susceptibility from the viewpoint of prevention against disasters. A conventional method for this evaluation is carried out in the following manner. The first step is collection of data which characterize the feature of a landslide area with the aid of field survey, and secondly each area is empirically ranked for landslide susceptibility. However, this method requires such experience for landslide that of ten givse a different result of ranking in correspondence to the degree of experience. On the other hand, this paper proposes a new method applying the quantification theory to categorical data which are collected from field survey. A region of Shikoku district in Japan was dealt with, an evaluation map was obtained showing land slide susceptibility, and comparison was made between the present method and the conventional method. The result convictsus the reliability of the present method for evaluation of landslide susceptibility.