3 November 2008 Development and research on the GIS-based landslide prediction system of the Three Gorges area
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Proceedings Volume 7145, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments; 714506 (2008); doi: 10.1117/12.812981
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China
Abstract
In this paper we discussed the development and research of the GIS-based landslide prediction system of the Three Gorges area. First of all, we systematically revisited the basic issues of the landslide prediction, including the principles of landslide prediction, the division of sliding-time and sliding-deformation stages, prediction parameters selection and monitoring sites selection. In addition to reviewing the landslide prediction models, this paper detailed discussed an improved model which makes an integration of the results of multiple prediction models. On the basis of those landslide prediction models, we developed a GIS-based landslide prediction system by using Visual C#.NET and ESRI ArcObjects components. Finally, this paper selected two typical landslide cases in the Three Gorges area: the Xintan landslide and the Lianzi Cliff dangerous rock body, and used the system to calculate and analyze. It validated the applicability and accuracy of the prediction models, made a test of the practicality of the system, and achieved good results.
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Qiao Ge, Zhongshi Tang, Haiwei Wang, "Development and research on the GIS-based landslide prediction system of the Three Gorges area", Proc. SPIE 7145, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments, 714506 (3 November 2008); doi: 10.1117/12.812981; https://doi.org/10.1117/12.812981
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KEYWORDS
Landslide (networking)

Geographic information systems

Visualization

Data modeling

Analytical research

Systems modeling

Complex systems

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