Rainfall-induced slope landslide pontential and landslide distribution characteristics assessment

Yung Sheng Chue, Jing-Wen Chen, Yie Ruey Chen

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

According to observations over the few years before and after typhoon and extreme rainfall events in the Laonong catchment of Kaohsiung, Southern Taiwan, this study combined a genetic adaptive neural network architecture, image texture analysis, and a geographic information system (GIS) in satellite image interpretation and land use change analysis to obtain disaster records and surface information. A multivariate hazards evaluation method was applied to quantitatively analyze the weights of various natural environmental and slope development hazard factors. Furthermore, this study established a slope landslide potential assessment model and depicted a slope landslide potential diagram by using the GIS platform. The impact of extreme rainfall events on slope landslide and landslide developmental characteristics were discussed. The findings can be a reference for subsequent slope development countermeasures and as an assessment for the academia and engineering fields involved in predicting landslide disasters caused by slope development.

Original languageEnglish
Pages (from-to)705-716
Number of pages12
JournalJournal of Marine Science and Technology (Taiwan)
Volume23
Issue number5
DOIs
Publication statusPublished - 2015 Jan 1

Fingerprint

Landslides
Rain
landslide
rainfall
Disasters
Geographic information systems
Hazards
disaster
Image texture
hazard
Network architecture
Land use
Catchments
typhoon
land use change
distribution
Satellites
Neural networks
texture
diagram

All Science Journal Classification (ASJC) codes

  • Oceanography
  • Ocean Engineering
  • Mechanics of Materials
  • Mechanical Engineering

Cite this

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abstract = "According to observations over the few years before and after typhoon and extreme rainfall events in the Laonong catchment of Kaohsiung, Southern Taiwan, this study combined a genetic adaptive neural network architecture, image texture analysis, and a geographic information system (GIS) in satellite image interpretation and land use change analysis to obtain disaster records and surface information. A multivariate hazards evaluation method was applied to quantitatively analyze the weights of various natural environmental and slope development hazard factors. Furthermore, this study established a slope landslide potential assessment model and depicted a slope landslide potential diagram by using the GIS platform. The impact of extreme rainfall events on slope landslide and landslide developmental characteristics were discussed. The findings can be a reference for subsequent slope development countermeasures and as an assessment for the academia and engineering fields involved in predicting landslide disasters caused by slope development.",
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Rainfall-induced slope landslide pontential and landslide distribution characteristics assessment. / Chue, Yung Sheng; Chen, Jing-Wen; Chen, Yie Ruey.

In: Journal of Marine Science and Technology (Taiwan), Vol. 23, No. 5, 01.01.2015, p. 705-716.

Research output: Contribution to journalArticle

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