Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)

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Analysis of Influencing Factors of Geological Disaster Risk Based on Big Data

Authors
Xin Lu1, *, Huanghuang Lu1, Xun Wang2, Jiao Yuan2
1School of Software, University of Electronic Science and Technology of China, Chengdu, China
2China Railway Eryuan Engineering Group Co. Ltd., Chengdu, China
*Corresponding author. Email: un365@qq.com
Corresponding Author
Xin Lu
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-064-0_111How to use a DOI?
Keywords
geological disasters; risk factors; big data analysis; relevance
Abstract

Geological disaster risk is affected by many internal and external factors. It is very necessary to understand the influence relationship of these internal and external factors for the prevention and control of geological disasters. This paper combines Apriori correlation analysis method with data statistical analysis method to analyze the internal and external incentives of geological disaster risk, so as to solve the problems of limited analysis data, less disaster samples and narrow adaptability of analysis conclusions in the existing research. This subject collects the data related to geological disasters in China in recent ten years as analysis samples for big data analysis experiments. The analysis data not only includes the elevation, slope, slope direction, terrain type, stratum lithology, geological structure, surface coverage type, vegetation coverage and other internal factors of geological disaster areas, but also covers the rainfall, rainfall and vegetation in geological disaster areas External factors such as surface temperature and soil humidity. The results show that geological disaster risk is related to internal and external factors, but their correlation and influence are different, which has certain application significance for geological disaster prevention and control.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
27 December 2022
ISBN
10.2991/978-94-6463-064-0_111
ISSN
2589-4900
DOI
10.2991/978-94-6463-064-0_111How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Xin Lu
AU  - Huanghuang Lu
AU  - Xun Wang
AU  - Jiao Yuan
PY  - 2022
DA  - 2022/12/27
TI  - Analysis of Influencing Factors of Geological Disaster Risk Based on Big Data
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
PB  - Atlantis Press
SP  - 1062
EP  - 1074
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-064-0_111
DO  - 10.2991/978-94-6463-064-0_111
ID  - Lu2022
ER  -