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Proceedings Paper

Real-time geological disaster monitoring with deformation parameters auto-detection technique
Author(s): Chenggang Li; Xiaochun Shi; Liming Tang; Honghua Qiu; Ming Tan
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Paper Abstract

CORS/GMS integration can be used to monitor displacement of surface deformation in geological disasters at the mm accuracy level. In order to detect the distinct geological disaster-related displacement deformation automatically and extract the temporal and spatial characteristics in the process of deformation, an algorithm DDExM (Deformation Detection & Exaction Method) for deformation parameter estimation is presented in this paper. The algorithm DDExM includes four steps: outlier detection, adaptive threshold classification, deformation evaluation, and deformation parameters auto-detection. The hypothesis and test, and threshold classification tools are used, based on Kalman filter, to realize the auto-detection of uniform deformation parameters applicable to multi-scale accuracy demand from decimeter to millimeter level. Experimental data from both the slope at Tiansan stone pit and the Guangdong Continuously Operating Reference Stations (GDCORS) based geological disaster dynamic monitoring are used to evaluate the performance of the DDExM. The DDExM leads to the application of CORS/GMS integration based geological disasters dynamic monitoring in provincial region automatically and continually with high temporal and spatial resolution.

Paper Details

Date Published: 10 October 2009
PDF: 8 pages
Proc. SPIE 7471, Second International Conference on Earth Observation for Global Changes, 74711P (10 October 2009); doi: 10.1117/12.836324
Show Author Affiliations
Chenggang Li, Institute of Surveying and Mapping (China)
Xiaochun Shi, Institute of Surveying and Mapping (China)
Liming Tang, Institute of Surveying and Mapping (China)
Honghua Qiu, Institute of Surveying and Mapping (China)
Ming Tan, Institute of Surveying and Mapping (China)


Published in SPIE Proceedings Vol. 7471:
Second International Conference on Earth Observation for Global Changes
Xianfeng Zhang; Jonathan Li; Guoxiang Liu; Xiaojun Yang, Editor(s)

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