The Application of Remote Sensing Technology to the Interpretation of Land Use for Rainfall-Induced Landslides Based on Genetic Algorithms and Artificial Neural Networks

Yie Ruey Chen, Shun Chieh Hsieh, Po Ning Ni, Jing-Wen Chen

Research output: Contribution to journalArticle

33 Citations (Scopus)

Abstract

In this paper, we explore the relationship between land use practices and landslides triggered by rainfall in eastern Taiwan. Before-and-after satellite images, combined with an artificial neural network method, enable the classification of land use and landslide zones. Genetic algorithms are used to evaluate the land use factors causing landslides. Using the geographic information system ArcGIS to support spatial reasoning, predictive maps are produced. The results suggest that the proposed method and procedures can be an effective tool for landslide monitoring and would be easily transferred to other similar applications.

Original languageEnglish
Pages (from-to)87-95
Number of pages9
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume2
Issue number2
DOIs
Publication statusPublished - 2009 Jan 1

All Science Journal Classification (ASJC) codes

  • Computers in Earth Sciences
  • Atmospheric Science

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