Home Journals Articles Updates About
CN
image
收藏切换
Debris-flow Susceptibility Assessment in Yongsheng County Based on Gray Relational Analysis-information Volume Method
收藏切换
PDF
Kang-tai CHANG1, Zhi-fang ZHAO2, 3, 4, 5, 6, *, Qiao-mu MOU1, Yong-lin YANG1, Yun-fei HU1, Yang QIN1
Science Technology and Engineering | 2025, 25(3) : 933 - 941
Less
收藏切换
Science Technology and Engineering | 2025, 25(3): 933-941
• Papers·Astronomy and Geosciences •
Debris-flow Susceptibility Assessment in Yongsheng County Based on Gray Relational Analysis-information Volume Method
Full
Kang-tai CHANG1, Zhi-fang ZHAO2, 3, 4, 5, 6, *, Qiao-mu MOU1, Yong-lin YANG1, Yun-fei HU1, Yang QIN1
Affiliations
  • 1. Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650050, China
  • 2. School of Earth Sciences, Yunnan University, Kunming 650050, China
  • 3. Key Laboratory of Sanjiang Metallogeny and Resources Exploration and Utilization, MNR, Kunming 650051, China
  • 4. Yunnan Key Laboratory of Sanjiang Metallogeny and Resources Exploration and Utilization, Kunming 650051, China
  • 5. Research Center of Domestic High-resolution Satellite Remote Sensing Geological Engineering, Kunming 650050, China
  • 6. Yunnan International Joint Laboratory of China-Laos-Bangladesh-Myanmar Natural Resources Remote Sensing Monitoring, Kunming 650051, China
Published: 2025-01-28 doi: 10.12404/j.issn.1671-1815.2402860
Outline
收藏切换

In order to study the disaster susceptibility of debris flow in Yongsheng County, the research area was Yongsheng County of Lijiang City, Yunnan Province, and it was divided into 475 sub-watershed units. Grey correlation analysis method was used to calculate the correlation degree of each factor, and the factor with the lowest correlation degree was eliminated. The independence of factors was tested by collinearity diagnosis. In the end, eight factors including average slope, average annual maximum rainfall, average vegetation coverage, average elevation, average melton ratio, average water system density, average landslide core density and average road density were retained. The information volume of the factors was calculated by the information volume method, and the correlation degree value was taken as the weight value of the superposition of each factor. The grey correlation analysis-information volume model was further constructed to carry out the evaluation research on the vulnerability of debris flow in Yongsheng County. The results show this as follows. The requency ratio of debris flow disaster points in the extremely vulnerable area is as high as 4.06, and the area under the ROC (receiver operating characteristic) curve is 0.818, indicating that the selected eight factors and the grey correlation analysation-information volume method have good forecasting ability for the evaluation of debris flow disaster vulnerability. The results can also be used as reference for the prevention and control of debris flow disaster in Yongsheng County.

debris-flow  /  gray relational analysis  /  information volume method  /  unit factors of catchments  /  susceptibility assessment  /  Yongsheng County
Kang-tai CHANG, Zhi-fang ZHAO, Qiao-mu MOU, Yong-lin YANG, Yun-fei HU, Yang QIN. Debris-flow Susceptibility Assessment in Yongsheng County Based on Gray Relational Analysis-information Volume Method[J]. Science Technology and Engineering, 2025 , 25 (3) : 933 -941 . DOI: 10.12404/j.issn.1671-1815.2402860
Appendix
Less
Year 2025 volume 25 Issue 3
PDF
330
132
Cite this Article
BibTeX
Article Info
doi: 10.12404/j.issn.1671-1815.2402860
  • Receive Date：2024-04-19
  • Online Date：2025-07-29
  • Published：2025-01-28
Article Data
Affiliations
History
  • Received：2024-04-19
  • Revised：2024-07-18
Funding
Affiliations
    1. Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650050, China
    2. School of Earth Sciences, Yunnan University, Kunming 650050, China
    3. Key Laboratory of Sanjiang Metallogeny and Resources Exploration and Utilization, MNR, Kunming 650051, China
    4. Yunnan Key Laboratory of Sanjiang Metallogeny and Resources Exploration and Utilization, Kunming 650051, China
    5. Research Center of Domestic High-resolution Satellite Remote Sensing Geological Engineering, Kunming 650050, China
    6. Yunnan International Joint Laboratory of China-Laos-Bangladesh-Myanmar Natural Resources Remote Sensing Monitoring, Kunming 650051, China
References
Share
https://castjournals.cast.org.cn/joweb/kxjsygc/EN/10.12404/j.issn.1671-1815.2402860
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House