The application of artificial neural networks to landslide susceptibility mapping at Janghung, Korea

Saro Lee, Joo Hyung Ryu, Moung Jin Lee, Joong Sun Won

Research output: Contribution to journalArticle

61 Citations (Scopus)

Abstract

The purpose of this study was to develop techniques for landslide susceptibility using artificial neural networks and then to apply these to the selected study area at Janghung in Korea. Landslide locations were identified from interpretation of satellite images and field survey data, and a spatial database of the topography, soil, forest, and land use. Thirteen landslide-related factors were extracted from the spatial database. These factors were then used with an artificial neural network to analyze landslide susceptibility. Each factor's weight was determined by the back-propagation training method. Five different training sets were applied to analyze and verify the effect of training. Then the landslide susceptibility indices were calculated using the back-propagationweights, and susceptibility maps were constructed from Geographic Information System (GIS) data for the five cases. Landslide locations were used to verify results of the landslide susceptibility maps and to compare them. The artificial neural network proved to be an effective tool for analyzing landslide susceptibility.

Original languageEnglish
Pages (from-to)199-220
Number of pages22
JournalMathematical Geology
Volume38
Issue number2
DOIs
Publication statusPublished - 2006 Feb 1

Fingerprint

Landslide
Susceptibility
artificial neural network
Artificial Neural Network
landslide
Spatial Database
Verify
Geographic Information Systems
back propagation
Satellite Images
Land Use
Survey Data
Back Propagation
Topography
forest soil
field survey
Soil
topography
land use

All Science Journal Classification (ASJC) codes

  • Mathematics (miscellaneous)
  • Earth and Planetary Sciences (miscellaneous)

Cite this

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abstract = "The purpose of this study was to develop techniques for landslide susceptibility using artificial neural networks and then to apply these to the selected study area at Janghung in Korea. Landslide locations were identified from interpretation of satellite images and field survey data, and a spatial database of the topography, soil, forest, and land use. Thirteen landslide-related factors were extracted from the spatial database. These factors were then used with an artificial neural network to analyze landslide susceptibility. Each factor's weight was determined by the back-propagation training method. Five different training sets were applied to analyze and verify the effect of training. Then the landslide susceptibility indices were calculated using the back-propagationweights, and susceptibility maps were constructed from Geographic Information System (GIS) data for the five cases. Landslide locations were used to verify results of the landslide susceptibility maps and to compare them. The artificial neural network proved to be an effective tool for analyzing landslide susceptibility.",
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The application of artificial neural networks to landslide susceptibility mapping at Janghung, Korea. / Lee, Saro; Ryu, Joo Hyung; Lee, Moung Jin; Won, Joong Sun.

In: Mathematical Geology, Vol. 38, No. 2, 01.02.2006, p. 199-220.

Research output: Contribution to journalArticle

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