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Data Mining for Landslide Genetic Mechanism Analysis in the Yunnan Province of China

verfasst von: Yan Du, Chen Chen

Erschienen in: Geotechnical and Geological Engineering | Ausgabe 11/2022

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Abstract

Landslide susceptibility analysis based on the strong ability of data mining of Geographic Information System (GIS) has become a hot topic in international landslide research. This paper used optimized decision tree and GIS databases to analyze the sensitivity in the northwest mountain areas of Yunnan province of China, and then discussed the formation mechanism of the landslide happened in the area. The translational landslide located in the area with an average gradient less than or equal to 28.7° was reclassified as a higher level 3 sensitive area than before according to the normalized different fault index (NDFI). The results showed that the data mining based on GIS 3D space–time information database can help to find the unique topography, geology hydrology and the other typical spatial information of some special typed of landslides such as translational landslides, thus it can illustrate the relationship between the landslides and their sensitivity factors. The improved landslide susceptibility analysis will provide a new method for identifying the genetic mechanism of landslide, and play an important role in the government regional planning and disaster prevention measures.

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Titel: Data Mining for Landslide Genetic Mechanism Analysis in the Yunnan Province of China
verfasst von: Yan Du
Chen Chen
Publikationsdatum: 14.07.2022
Verlag: Springer International Publishing
Erschienen in: Geotechnical and Geological Engineering / Ausgabe 11/2022
Print ISSN: 0960-3182
Elektronische ISSN: 1573-1529
DOI: https://doi.org/10.1007/s10706-022-02237-z

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