대한원격탐사학회:학술대회논문집 (Proceedings of the KSRS Conference)
- 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
- /
- Pages.294-297
- /
- 2004
- /
- 1226-9743(pISSN)
THE APPLICATION OF ARTIFICIAL NEURAL NETWORKS TO LANDSLIDE SUSCEPTIBILITY MAPPING AT JANGHUNG, KOREA
- LEE SARO (Geoscience Information Center, Korea Institute of Geology & Mineral Resources (KIGAM)) ;
-
LEE MOUNG-JIN
(Department of Earth System Science, Yonsei University) ;
-
WON JOONG-SUN
(Department of Earth System Science, Yonsei University)
- 발행 : 2004.10.01
초록
The purpose of this study was to develop landslide susceptibility analysis techniques using artificial neural networks and then to apply these to the selected study area of Janghung in Korea. We aimed to verify the effect of data selection on training sites. 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 was constructed. Thirteen landslide-related factors were extracted from the spatial database. Using these factors, landslide susceptibility was analyzed using an artificial neural network. The weights of each factor were determined by the back-propagation training method. Five different training datasets were applied to analyze and verify the effect of training. Then, the landslide susceptibility indices were calculated using the trained back-propagation weights and susceptibility maps were constructed from Geographic Information System (GIS) data for the five cases. The results of the landslide susceptibility maps were verified and compared using landslide location data. GIS data were used to efficiently analyze the large volume of data, and the artificial neural network proved to be an effective tool to analyze landslide susceptibility.