Suchergebnisse

We are very grateful to all the referees for their indispensable and unselfish work that greatly contributed to the improvement of the quality of the papers. The Department of the Environment and the Department of Science, Technology and University of the Aragón Government, as well as the Innovation Ministry of the Spanish Government (CGL2011-12465), provided financial support to organise the scientific meeting "Geomorphological Research in Spain" (Zaragoza, September, 2011). We thank the International Association of Geomorphologists (IAG), the Spanish Society of Geomorphology (SEG), and the Spanish Society of Quaternary Studies (AEQUA) for supporting the initiative. We are also very grateful to Dr. Cinta Marín for helping with the preparation of the bibliometric data and supplementary material presented in this guest editorial. ; Peer Reviewed

This contribution presents a quantitative procedure for landslide risk analysis and zoning considering hazard, exposure (or value of elements at risk), and vulnerability. The method provides the means to obtain landslide risk models (expressing expected damage due to landslides on material elements and economic activities in monetary terms, according to different scenarios and periods) useful to identify areas where mitigation efforts will be most cost effective. It allows identifying priority areas for the implementation of actions to reduce vulnerability (elements) or hazard (processes). The procedure proposed can also be used as a preventive tool, through its application to strategic environmental impact analysis (SEIA) of land‐use plans. The underlying hypothesis is that reliable predictions about hazard and risk can be made using models based on a detailed analysis of past landslide occurrences in connection with conditioning factors and data on past damage. The results show that the approach proposed and the hypothesis formulated are essentially correct, providing estimates of the order of magnitude of expected losses for a given time period. Uncertainties, strengths, and shortcomings of the procedure and results obtained are discussed and potential lines of research to improve the models are indicated. Finally, comments and suggestions are provided to generalize this type of analysis.