In landslide susceptibility assessment, an important issue is the correct identification of significant contributing factors, which leads to the improvement of predictions regarding this type of geomorphologic processes. In the scientific literature, different weightings are assigned to these factors, but contain large variations. This study aims to identify the spatial variability and range of variation for the coefficients of landslide predictors in different geographical conditions. Four sectors of 15 km × 15 km (225 km2) were selected for analysis from representative regions in Romania in terms of spatial extent of landslides, situated both on the hilly areas (the Transylvanian Plateau and Moldavian Plateau) and lower mountain region (Subcarpathians). The following factors were taken into consideration: elevation, slope angle, slope height, terrain curvature (mean, plan and profile), distance from drainage network, slope aspect, land use, and lithology. For each sector, landslide inventory, digital elevation model and thematic layers of the mentioned predictors were achieved and integrated in a georeferenced environment. The logistic regression was applied separately for the four study sectors as the statistical method for assessing terrain landsliding susceptibility. Maps of landslide susceptibility were produced, the values of which were classified by using the natural breaks method (Jenks). The accuracy of the logistic regression outcomes was evaluated using the ROC (receiver operating characteristic) curve and AUC (area under the curve) parameter, which show values between 0.852 and 0.922 for training samples, and between 0.851 and 0.940 for validation samples. The values of coefficients are generally confined within the limits specified by the scientific literature. In each sector, landslide susceptibility is essentially related to some specific predictors, such as the slope angle, land use, slope height, and lithology. The study points out that the coefficients assigned to the landslide predictors through logistic regression are capable to reveal some important characteristics in landslide manifestation. The study also shows that the logistic regression could be an alternative method to the current Romanian methodology for landslide susceptibility and hazard mapping.

Assessing landslide risk is a fundamental requirement to plan suitable prevention actions. To date, most risk studies focus on individual slopes or catchments. Whereas regional, national or continental scale assessments are hardly available because of methodological and/or data limitations. In this contribution, we present an overview of all requirements and limitations in landslide risk studies across all spatial scales, by means of a hybrid form that combines elements of original research with the comprehensive characteristics of a review study. The review critically analyses each component in the landslide risk analysis providing a detailed explanation of their state‐of‐the‐art, with dedicated sections on susceptibility, hazard, exposure, and vulnerability. To put the theoretical framework to test, we also dive into a case study, expressed at the continental scale. Specifically, we take the main European mountain ranges and provide the reader with a textbook example of risk assessment for such a large territory. In doing so, we take into account issues associated with cross‐national differences in landslide mapping. As a result, we identify landslide‐prone European landscape and explore the associated possible economic consequences (human settlements and agricultural areas). We also analyze the population at risk during daytime and nighttime. Moreover, a modern view of the problem is explored in the form of how risk outcomes should be delivered to master planners and geoscientific personnel alike. Specifically, we convert our output into an interactive Web Application (https://pan‐european‐landslide‐risk.github.io/) to include notions of scientific communication both to a large public as well as to a technical audience.

During the summer season 2018 and 2019, natural hazards (namely, floods and wildfires) have occurred at some of the most popular tourist destinations in Greece, endangering tourists’ safety and vacation quality. These have influenced tourists’ perception of Greece as a “potentially risky destination”, causing a decrease in the number of tourists willing to visit this country. However, the current study assumes that some tourists will show more courageous travel behavior in the aftermath of natural hazards, while others will remain cautious when deciding to travel to risky destinations. Therefore, the questionnaire on a sample group of 431 respondents from Serbia and Romania was conducted to explore the factors influencing such differences. The study aims to explore whether tourists’ individual characteristics influence tourism worries and tourist behavior based on perceived risks. The study also intends to analyze the moderating role of tourists’ nationality, considering the relationship between personality and tourist behavior based on the perceived risk. The findings provide evidence that not only tourists’ personality but also sociodemographic characteristics influence tourism worries and tourist behavior based on the perceived risk. Additionally, the study is the first to explore and confirm the role of nationality in tourist behavior based on the perceived risk, as well as the moderation role of nationality in regression between tourist’s personality and behavior based on the perception of risk. Theoretical and practical implications are discussed in the paper.