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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

机译:地理信息系统和遥感技术在交通运输路面滑坡监测中的综合应用:以塞浦路斯帕福斯地区为例

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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.
机译:这项研究使用遥感和地理信息系统(GIS)技术来考虑滑坡对塞浦路斯农村公路网中运输路面的影响。滑坡被认为是全球范围内最极端的自然灾害之一,既造成人员伤亡,又对运输网络造成严重破坏。监控道路网络的风险评估是基于滑坡发生的可能性以及灾难(滑坡)发生时后果的程度和严重性的组合。可能引发滑坡事件的因素包括靠近活动断层,地质构造,断裂带,斜坡的程度和高曲率,水况等。在这项研究中,研究了农村网络的可靠性和脆弱性。最初,通过对卫星图像的解释来确定滑坡的位置。选择了不同的地貌因素,例如纵横比,坡度,距集水区的距离,岩性,距地层的距离,地形曲率,土地利用和卫星图像衍生的植被状况,并将其纳入GIS环境中,以提供决策支持和连续滑坡监测该区域的系统。然后,基于层次分析法,将这些参数用于最终的滑坡灾害评估模型。结果表明,分类高危险区域与现场确认的边坡破坏之间具有良好的相关性。 CA Markov模型还被用于预测2020年的滑坡灾害分区图以及交通道路的未来可能发生的灾害。所建议的方法可以用于整个东地中海地区具有相似生理条件的地区。

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