4.6 Article

Landslide Susceptibility Mapping of Central and Western Greece, Combining NGI and WoE Methods, with Remote Sensing and Ground Truth Data

期刊

LAND
卷 10, 期 4, 页码 -

出版社

MDPI
DOI: 10.3390/land10040402

关键词

landslides; SAR; NGI; WoE; evritania; aetolia-acarnania

资金

  1. Next Generation GEOSS for Innovation Business (NextGEOSS)
  2. European Commission [730329]
  3. European Union Seventh Framework Programme (FP7-REGPOT-2012-2013-1) [316210]
  4. National Network on Climate Change and its Impacts-Climpact - Ministry of Development and Investments
  5. H2020 Societal Challenges Programme [730329] Funding Source: H2020 Societal Challenges Programme

向作者/读者索取更多资源

The development of remote sensing techniques has significantly improved landslide management over the past decade. Different landslide susceptibility methods have their own advantages and limitations. This study compared two landslide models and found that the WoE method was more accurate due to expert opinion and landslide inventory data.
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.

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