Multi-dimensional Data Visualization Method for Geological Subsidence Deformation Monitoring
Conference: ICMLCA 2021 - 2nd International Conference on Machine Learning and Computer Application
12/17/2021 - 12/19/2021 at Shenyang, China
Proceedings: ICMLCA 2021
Pages: 5Language: englishTyp: PDF
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Authors:
Shao, Yongheng; Wang, Hongjun; Liu, Chenxu (Shenyang Institute of Computing Technology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shenyang, China)
Zhang, Yonghong (R.C. of Big Data and Artificial Intelligence Technology, Shandong University, Beijing Zhongke Zhihe Digital Technology Co., Ltd, Jinan, China)
Abstract:
At present, geological subsidence deformation monitoring is widely used. For the massive multi-dimensional heterogeneous data monitored, how to express and display the data accurately and intuitively, and how to use suitable data visual analysis methods to make relevant monitoring personnel analyze the results of geological subsidence deformation more conveniently and quickly become the main problem. In this research, a visual analysis system combining traditional technology with data visualization technology is designed according to InSAR geological monitoring data of a city in Jiangsu Province, and a visualization model of geological subsidence deformation monitoring based on multi-dimensional data set is proposed. This method has been applied to the evaluation of geological deformation and settlement examples. The appraisal by experts in the field of geology has verified the practicability and effectiveness of the method under the system.