The Method of Segmenting the Early Warning Thresholds Based on Fisher Optimal Segmentation

Xiangyu Li, Tianjie Lei (), Jing Qin (), Jiabao Wang, Weiwei Wang, Baoyin Liu, Dongpan Chen, Guansheng Qian, Li Zhang and Jingxuan Lu
Additional contact information
Xiangyu Li: State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Tianjie Lei: Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Jing Qin: State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Jiabao Wang: College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing (CUMTB), Beijing 100083, China
Weiwei Wang: China Electronic Greatwall ShengFeiFan Information System Co., Ltd., Beijing 102200, China
Baoyin Liu: Institutes of Science and Development, University of Chinese Academy of Sciences, Beijing 100190, China
Dongpan Chen: Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
Guansheng Qian: Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Li Zhang: Beijing Institute of Technology, Beijing 100081, China
Jingxuan Lu: State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China

Land, 2023, vol. 12, issue 2, 1-14

Abstract: Most slope collapse accidents are indicated by certain signs before their occurrence, and unnecessary losses can be avoided by predicting slope deformation. However, the early warning signs of slope deformation are often misjudged. It is necessary to establish a method to determine the appropriate early warning signs in sliding thresholds. Here, to better understand the impact of different scales on the early warning signs of sliding thresholds, we used the Fisher optimal segmentation method to establish the early warning signs of a sliding threshold model based on deformation speed and deformation acceleration at different spatial scales. Our results indicated that the accuracy of the early warning signs of sliding thresholds at the surface scale was the highest. Among them, the early warning thresholds of the blue, yellow, orange, and red level on a small scale were 369.31 mm, 428.96 mm, 448.41 mm, and 923.7 mm, respectively. The evaluation accuracy of disaster non-occurrence and occurrence was 93.25% and 92.41%, respectively. The early warning thresholds of the blue, yellow, orange, and red level on a large scale were 980.11 mm, 1038.16 mm, 2164.63 mm, and 9492.75 mm, respectively. The evaluation accuracy of disaster non-occurrence and occurrence was 97.22% and 97.44%, respectively. Therefore, it is necessary to choose deformation at the surface scale with a large scale as the sliding threshold. Our results effectively solve the problem of misjudgment of the early warning signs of slope collapse, which is of great significance for ensuring the safe operation of water conservation projects and improving the slope deformation warning capability.

Keywords: fisher optimal segmentation method; warning; threshold determination; regression model (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2073-445X/12/2/344/pdf (application/pdf)
https://www.mdpi.com/2073-445X/12/2/344/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:12:y:2023:i:2:p:344-:d:1048333

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().