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https://hdl.handle.net/20.500.14279/8618
Τίτλος: | Integrated use of GIS and remote sensing for monitoring landslides in transportation pavements: the case study of Paphos area in Cyprus | Συγγραφείς: | Alexakis, Dimitrios Agapiou, Athos Tzouvaras, Marios Themistocleous, Kyriacos Neocleous, Kyriacos Michaelides, S. Hadjimitsis, Diofantos G. |
Major Field of Science: | Engineering and Technology | Field Category: | Environmental Engineering | Λέξεις-κλειδιά: | Landslides;Transportation;GIS;Remote sensing | Ημερομηνία Έκδοσης: | 25-Ιου-2013 | Πηγή: | Natural Hazards, 2013, vol. 72, no. 1, pp. 119-141 | Volume: | 72 | Issue: | 1 | Start page: | 119 | End page: | 141 | Περιοδικό: | Natural Hazards | Περίληψη: | This study considers the impact of landslides on transportation pavements in rural road network of Cyprus using remote sensing and geographical information system (GIS) techniques. Landslides are considered to be one of the most extreme natural hazards worldwide, causing both human losses and severe damages to the transportation network. Risk assessment for monitoring a road network is based on the combination of the probability of landslides occurrence and the extent and severity of the resultant consequences should the disasters (landslides) occur. Factors that can trigger landslide episodes include proximity to active faults, geological formations, fracture zones, degree and high curvature of slopes, water conditions, etc. In this study, the reliability and vulnerability of a rural network are examined. Initially, landslide locations were identified from the interpretation of satellite images. Different geomorphological factors such as aspect, slope, distance from the watershed, lithology, distance from lineaments, topographic curvature, land use and vegetation regime derived from satellite images were selected and incorporated in GIS environment in order to develop a decision support and continuous landslide monitoring system of the area. These parameters were then used in the final landslide hazard assessment model based on the analytic hierarchy process method. The results indicated good correlation between classified high-hazard areas and field-confirmed slope failures. The CA Markov model was also used to predict the landslide hazard zonation map for 2020 and the possible future hazards for transportation pavements. The proposed methodology can be used for areas with similar physiographic conditions all over the Eastern Mediterranean region. | URI: | https://hdl.handle.net/20.500.14279/8618 | ISSN: | 0921030X 15730840 |
DOI: | 10.1007/s11069-013-0770-3 | Rights: | © Springer | Type: | Article | Affiliation: | Cyprus University of Technology Meteorological Service of Cyprus |
Publication Type: | Peer Reviewed |
Εμφανίζεται στις συλλογές: | Άρθρα/Articles |
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