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Geotechnical and Geological Engineering

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

  • 14-07-2022
  • Original Paper
Published in:
Authors
Yan Du
Chen Chen
Published in
Geotechnical and Geological Engineering | Issue 11/2022

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Abstract

The article delves into the application of data mining and decision tree models to analyze landslide susceptibility in Yunnan Province, China. It emphasizes the importance of considering geological and hydrological factors to improve landslide prediction and management. The study area, characterized by complex geomorphological types and a sub-monsoon climate, provides a unique setting for this analysis. The authors introduce the normalized differential fault index (NDFI) to optimize the decision tree model, enabling a more accurate classification of landslide susceptibility areas. The research also explores the genetic mechanisms of translational landslides, revealing that fault zones and soft fracture zones play a crucial role in landslide occurrence. By integrating GIS 3D space-time information databases and remote sensing data, the study offers valuable insights into the internal damage mechanisms of landslides, contributing to better risk management and prevention strategies.
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Title
Data Mining for Landslide Genetic Mechanism Analysis in the Yunnan Province of China
Authors
Yan Du
Chen Chen
Publication date
14-07-2022
Publisher
Springer International Publishing
Published in
Geotechnical and Geological Engineering / Issue 11/2022
Print ISSN: 0960-3182
Electronic ISSN: 1573-1529
DOI
https://doi.org/10.1007/s10706-022-02237-z
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