Evidence map›Paper›PMID 39592696›Full record

ArticleScientific reports2024

Research on geological hazard characteristics and susceptibility of the Duku Highway based on SBAS-InSAR and improved spatiotemporal clustering.

Yaxuan Niu, Yan Xu, Chenyu Guo, Jie Liu, Jiangpeng Zhang, Qi Liu, Zhiwei Yang, Jun Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Yaxuan NiuXinjiang Transportation Planning Survey and Design Institute Co., Ltd, Urumqi, 830000, China.
Yan XuXinjiang Transportation Planning Survey and Design Institute Co., Ltd, Urumqi, 830000, China.
Chenyu GuoUniversity of Chinese Academy of Sciences, Beijing, 100049, China. guochenyu16@mails.ucas.ac.cn.
Jie LiuXinjiang Transportation Planning Survey and Design Institute Co., Ltd, Urumqi, 830000, China.
Jiangpeng ZhangXinjiang Transportation Planning Survey and Design Institute Co., Ltd, Urumqi, 830000, China.
Qi LiuXinjiang Transportation Planning Survey and Design Institute Co., Ltd, Urumqi, 830000, China.
Zhiwei YangXinjiang Transportation Planning Survey and Design Institute Co., Ltd, Urumqi, 830000, China.
Jun ZhangXinjiang Transportation Planning Survey and Design Institute Co., Ltd, Urumqi, 830000, China.

Funding

Outstanding young talents - young scientific and technologically innovative talents 2023TSYCCX0108Research Fund of Xinjiang Transportation Planning, Survey and Design Institute Co., Ltd KY202312102303
6 · The paper itself

Abstract

The high-altitude Duku Highway is characterized by complex terrain changes and frequent geological hazards, which severely impact the lives of local residents and the sustainable development of the regional economy. The lack of understanding of terrain deformation, coupled with scarce foundational observation data, makes it challenging to apply mainstream susceptibility assessment methods such as slope modeling and causality analysis. Consequently, this study utilizes Sentinel-1 A data and employs the SBAS-InSAR technique to extract and analyze the deformation characteristics of 184 hazard areas along the Duku Highway over nearly three years. Furthermore, the Correlation Clustering Evaluation Model is proposed, attributing hazard properties to unsupervised spatial clustering results, thus enabling the study of hazard susceptibility in data-scarce regions without prior knowledge. The results indicate that the SBAS-InSAR coherence is 0.64, with a validation accuracy of 85%. The high, relatively-high, and moderate susceptibility areas account for 24.7%, 17.1%, and 32.6% of the total area, respectively. The rapid uplift of terrain due to plate compression is a major factor leading to frequent hazards in high and relatively-high susceptibility areas. These regions may spontaneously experience cyclic hazards (minimum of 2 months) without extreme external factors. The research findings offer new insights into regional hazards and provide a basis for the sustainable management of highways.

Indexed as

Correlation clustering evaluation modelGeological hazardsHazard susceptibilitySBAS-InSARTemporal spatial clusteringTerrain deformation

Identifiers

PMID39592696
PMCPMC11599843

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