Share Email Print
cover

Proceedings Paper

Design and application analysis of prediction system of geo-hazards based on GIS in the Three Gorges Reservoir
Author(s): Deying Li; Kunlong Yin; Huaxi Gao; Changchun Liu
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Although the project of the Three Gorges Dam across the Yangtze River in China can utilize this huge potential source of hydroelectric power, and eliminate the loss of life and damage by flood, it also causes environmental problems due to the big rise and fluctuation of the water, such as geo-hazards. In order to prevent and predict geo-hazards, the establishment of prediction system of geo-hazards is very necessary. In order to implement functions of hazard prediction of regional and urban geo-hazard, single geo-hazard prediction, prediction of landslide surge and risk evaluation, logical layers of the system consist of data capturing layer, data manipulation and processing layer, analysis and application layer, and information publication layer. Due to the existence of multi-source spatial data, the research on the multi-source transformation and fusion data should be carried on in the paper. Its applicability of the system was testified on the spatial prediction of landslide hazard through spatial analysis of GIS in which information value method have been applied aims to identify susceptible areas that are possible to future landslide, on the basis of historical record of past landslide, terrain parameter, geology, rainfall and anthropogenic activity. Detailed discussion was carried out on spatial distribution characteristics of landslide hazard in the new town of Badong. These results can be used for risk evaluation. The system can be implemented as an early-warning and emergency management tool by the relevant authorities of the Three Gorges Reservoir in the future.

Paper Details

Date Published: 15 October 2009
PDF: 7 pages
Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 749239 (15 October 2009); doi: 10.1117/12.837229
Show Author Affiliations
Deying Li, China Univ. of Geosciences (China)
Kunlong Yin, China Univ. of Geosciences (China)
Huaxi Gao, Zhejiang Ocean Univ. (China)
Changchun Liu, China Univ. of Geosciences (China)


Published in SPIE Proceedings Vol. 7492:
International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining
Yaolin Liu; Xinming Tang, Editor(s)

© SPIE. Terms of Use
Back to Top