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Rainfall-induced slope landslide pontential and landslide distribution characteristics assessment

Research output: Contribution to journalArticlepeer-review

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 15 - Life on Land
    SDG 15 Life on Land

All Science Journal Classification (ASJC) codes

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

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