Econ. Environ. Geol. 2005; 38(1): 33-43

Published online February 28, 2005

© THE KOREAN SOCIETY OF ECONOMIC AND ENVIRONMENTAL GEOLOGY

Landslide Susceptibility Analysis and Verification using Artificial Neural Network in the Kangneung Area

Saro Lee1, Moung-Jin Lee2 and Joong-Sun Won2

1Geoscience Information Center, Korea Institute of Geoscience & Mineral Resources (KIGAM), Daejeon 305-350, Korea
2Department of Earth System Science, Yonsei University, Seoul 120-749, Korea

Correspondence to :

Saro Lee

leesaro@kigam.re.kr

Received: September 2, 2004; Accepted: January 27, 2005

Abstract

The purpose of this study is to make and validate landslide susceptibility map using artificial neural network and GIS in Kangneung area. For this, topography, soil, forest, geology and land cover data sets were constructed as a spatial database in GIS. From the database, slope, aspect, curvature, water system, topographic type, soil texture, soil material, soil drainage, soil effective thickness, wood type, wood age, wood diameter, forest density, lithology, land cover, and lineament were used as the landslide occurrence factors. The weight of the each factor was calculated, and applied to make landslide susceptibility maps using artificial neural network. Then the maps were validated using rate curve method which can predict qualitatively the landslide occurrence. The landslide susceptibility map can be used to reduce associated hazards, and to plan land use and construction as basic data.

Keywords GIS, Landslide, Susceptibility, Artificial Neural Network, Kangneung

Article

Econ. Environ. Geol. 2005; 38(1): 33-43

Published online February 28, 2005

Copyright © THE KOREAN SOCIETY OF ECONOMIC AND ENVIRONMENTAL GEOLOGY.

Landslide Susceptibility Analysis and Verification using Artificial Neural Network in the Kangneung Area

Saro Lee1, Moung-Jin Lee2 and Joong-Sun Won2

1Geoscience Information Center, Korea Institute of Geoscience & Mineral Resources (KIGAM), Daejeon 305-350, Korea
2Department of Earth System Science, Yonsei University, Seoul 120-749, Korea

Correspondence to:

Saro Lee

leesaro@kigam.re.kr

Received: September 2, 2004; Accepted: January 27, 2005

Abstract

The purpose of this study is to make and validate landslide susceptibility map using artificial neural network and GIS in Kangneung area. For this, topography, soil, forest, geology and land cover data sets were constructed as a spatial database in GIS. From the database, slope, aspect, curvature, water system, topographic type, soil texture, soil material, soil drainage, soil effective thickness, wood type, wood age, wood diameter, forest density, lithology, land cover, and lineament were used as the landslide occurrence factors. The weight of the each factor was calculated, and applied to make landslide susceptibility maps using artificial neural network. Then the maps were validated using rate curve method which can predict qualitatively the landslide occurrence. The landslide susceptibility map can be used to reduce associated hazards, and to plan land use and construction as basic data.

Keywords GIS, Landslide, Susceptibility, Artificial Neural Network, Kangneung

    KSEEG
    Apr 30, 2024 Vol.57 No.2, pp. 107~280

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