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Landslide Susceptibility Mapping of Central and Western Greece, Combining NGI and WoE Methods, with Remote Sensing and Ground Truth Data
Land ( IF 3.905 ) Pub Date : 2021-04-12 , DOI: 10.3390/land10040402
Charalampos Kontoes , Constantinos Loupasakis , Ioannis Papoutsis , Stavroula Alatza , Eleftheria Poyiadji , Athanassios Ganas , Christina Psychogyiou , Mariza Kaskara , Sylvia Antoniadi , Natalia Spanou

The exploitation of remote sensing techniques has substantially improved pre- and post- disaster landslide management over the last decade. A variety of landslide susceptibility methods exists, with capabilities and limitations related to scale and spatial accuracy issues, as well as data availability. The Interferometric Synthetic Aperture Radar (InSAR) capabilities have significantly contributed to the detection, monitoring, and mapping of landslide phenomena. The present study aims to point out the contribution of InSAR data in landslide detection and to evaluate two different scale landslide models by comparing a heuristic to a statistical method for the rainfall-induced landslide hazard assessment. Aiming to include areas with both high and low landslide occurrence frequencies, the study area covers a large part of the Aetolia–Acarnania and Evritania prefectures, Central and Western Greece. The landslide susceptibility product provided from the weights of evidence (WoE) method proved more accurate, benefitting from the expert opinion and the landslide inventory. On the other hand, the Norwegian Geological Institute (NGI) methodology has the edge on its immediate implementation, with minimum data requirements. Finally, it was proved that using sequential SAR image acquisitions gives the benefit of an updated landslide inventory, resulting in the generation of, on request, updated landslide susceptibility maps.

中文翻译:

结合NGI和WoE方法,结合遥感和地面真相数据,对希腊中部和西部的滑坡敏感性图

在过去的十年中,利用遥感技术已大大改善了灾前和灾后的滑坡管理。存在多种滑坡敏感性方法,其能力和局限性与规模和空间精度问题以及数据可用性有关。干涉式合成孔径雷达(InSAR)功能对滑坡现象的检测,监测和测绘做出了重要贡献。本研究旨在指出InSAR数据在滑坡检测中的作用,并通过比较启发式方法和统计方法对降雨引起的滑坡灾害评估进行评估,从而评估两种不同规模的滑坡模型。旨在包括高和低滑坡发生频率的区域,研究区域覆盖了希腊中部和西部的埃托利亚-阿卡尼亚尼亚州和埃夫里塔尼亚州的大部分地区。证据权重(WoE)方法提供的滑坡敏感性产品证明更为准确,这得益于专家的意见和滑坡清单。另一方面,挪威地质研究所(NGI)的方法在立即实施方面具有优势,所需数据最少。最后,事实证明,使用顺序SAR图像采集可以带来更新的滑坡清单的好处,从而可以根据要求生成更新的滑坡敏感性图。受益于专家意见和滑坡清单。另一方面,挪威地质研究所(NGI)的方法在立即实施方面具有优势,所需数据最少。最后,事实证明,使用顺序SAR图像采集可以带来更新的滑坡清单的好处,从而可以根据要求生成更新的滑坡敏感性图。受益于专家意见和滑坡清单。另一方面,挪威地质研究所(NGI)的方法在立即实施方面具有优势,所需数据最少。最后,事实证明,使用顺序SAR图像采集可以带来更新的滑坡清单的好处,从而可以根据要求生成更新的滑坡敏感性图。
更新日期:2021-04-12
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