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Integrated use of GIS and remote sensing for monitoring landslides in transportation pavements: the case study of Paphos area in Cyprus

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  • D. Alexakis
  • A. Agapiou
  • M. Tzouvaras
  • K. Themistocleous
  • K. Neocleous
  • S. Michaelides
  • D. Hadjimitsis

Abstract

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. Copyright Springer Science+Business Media Dordrecht 2014

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  • D. Alexakis & A. Agapiou & M. Tzouvaras & K. Themistocleous & K. Neocleous & S. Michaelides & D. Hadjimitsis, 2014. "Integrated use of GIS and remote sensing for monitoring landslides in transportation pavements: the case study of Paphos area in Cyprus," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 72(1), pages 119-141, May.
    • Handle: RePEc:spr:nathaz:v:72:y:2014:i:1:p:119-141
    DOI: 10.1007/s11069-013-0770-3
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    1. Maria Kouli & Constantinos Loupasakis & Pantelis Soupios & Filippos Vallianatos, 2010. "Landslide hazard zonation in high risk areas of Rethymno Prefecture, Crete Island, Greece," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 52(3), pages 599-621, March.
    2. Bakhtiar Feizizadeh & Thomas Blaschke, 2013. "GIS-multicriteria decision analysis for landslide susceptibility mapping: comparing three methods for the Urmia lake basin, Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(3), pages 2105-2128, February.
    3. Jenelius, Erik & Mattsson, Lars-Göran, 2012. "Road network vulnerability analysis of area-covering disruptions: A grid-based approach with case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 746-760.
    4. Yang Hong & Robert Adler & George Huffman, 2007. "Use of satellite remote sensing data in the mapping of global landslide susceptibility," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 43(2), pages 245-256, November.
    5. Jenelius, Erik & Petersen, Tom & Mattsson, Lars-Göran, 2006. "Importance and exposure in road network vulnerability analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 537-560, August.
    6. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    7. Sigrid Roessner & Hans-Ulrich Wetzel & Hermann Kaufmann & Aman Sarnagoev, 2005. "Potential of Satellite Remote Sensing and GIS for Landslide Hazard Assessment in Southern Kyrgyzstan (Central Asia)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 35(3), pages 395-416, July.
    8. Roberto Patuelli & Aura Reggiani & Sean Gorman & Peter Nijkamp & Franz-Josef Bade, 2007. "Network Analysis of Commuting Flows: A Comparative Static Approach to German Data," Networks and Spatial Economics, Springer, vol. 7(4), pages 315-331, December.
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    2. Dimitris Kouhartsiouk & Skevi Perdikou, 2021. "The application of DInSAR and Bayesian statistics for the assessment of landslide susceptibility," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(3), pages 2957-2985, February.
    3. Qi Wang & He Bing & Siqi Wang & Qing Xu, 2022. "Study on the Spatial Distribution Characteristics and Influencing Factors of Famous Historical and Cultural Towns or Villages in Hubei Province, China," Sustainability, MDPI, vol. 14(21), pages 1-29, October.
    4. Hong, Wei-Ting & Clifton, Geoffrey & Nelson, John D., 2022. "Rail transport system vulnerability analysis and policy implementation: Past progress and future directions," Transport Policy, Elsevier, vol. 128(C), pages 299-308.

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