EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 352 (2022) E3S Web Conf., 352 (2022) 03037 References
Open Access
Issue
E3S Web Conf.
Volume 352, 2022
7th International Conference on Energy Science and Applied Technology (ESAT 2022)
Article Number 03037
Number of page(s) 5
Section Energy Sustainability & Energy-Related Environmental Science
DOI https://doi.org/10.1051/e3sconf/202235203037
Published online 27 June 2022
  1. Cui Peng, Liu Shijian, Tan Wanpei. Status and Prospect of Debris Flow Monitoring and Prediction Research in China[J]. Journal of Natural Disasters, 2000, 10–15. [Google Scholar]
  2. Guo Fuyun, Song Xiaoling, Xie Yu, et al. Discussion on Meteorological Early Warning Technology and Methods of Geological Hazards in Gansu[J]. Chinese Journal of Geological Hazards and Prevention, 2015, 127–133. [Google Scholar]
  3. Wang Youmin. Soil and Water Loss in Qinba Mountains and Longnan Mountains and Principles of Ecological Protection[J]. Journal of Northwest Forestry University, 1999, 60–65. [Google Scholar]
  4. Yuan Liqiang. To deal with debris flow, monitoring is the best policy[J]. China's Strategic Emerging Industries, 2014, 42. [Google Scholar]
  5. Li Hongfu. Research on Debris Flow Monitoring and Early Warning System[D]: Jilin University, 2015. [Google Scholar]
  6. Qiao Jianping. Monitoring and early warning of mountain torrents, landslides and debris flows[J]. China Disaster Reduction, 2006, 13–15. [Google Scholar]
  7. Yang Chenglin, Ding Haitao, Chen Ningsheng. Debris flow monitoring and early warning system based on the formation and movement of debris flow[J]. Journal of Natural Disasters, 2014, 1–9. [Google Scholar]
  8. Zhang Wanxi, Zhang Shugang, Sun Chao. Research on monitoring and management of collapse, landslide and debris flow[J]. Science and Technology Information, 2012, 66. [Google Scholar]
  9. Wu Yue, Ren Tao, Yang Zhuojing, et al. Debris flow monitoring analyzer applied to geological disasters[J]. Electronic Measurement Technology, 2013, 67–70. [Google Scholar]
  10. Fang Hua. Research on Debris Flow Monitoring and Early Warning Technology[J]. People's Yellow River, 2011, 63–65, 68. [Google Scholar]
  11. Su Junfeng, Xiao Zhiqiang, Wei Bangxian, et al. GIS-based heavy rain disaster risk zoning in Longnan City, Gansu Province[J]. Arid Meteorology, 2012, 30(4): 650–655. [Google Scholar]
  12. Feng Jun, Shang Xuejun, Ming, et al. Research on rainfall zoning and critical rainfall of geological disasters in Longnan[J]. Arid Meteorology, 2006, 24(4): 20–24. [Google Scholar]
  13. Han Rucai, Fu Helin. A review of the current situation of landslide and debris flow monitoring and remediation technology at home and abroad[J]. Western Prospecting Engineering, 2004, 206–207. [Google Scholar]
  14. Xu Liang, Cheng Gang, Zhu Honghu. A review of landslide monitoring technology based on the integration of space, space and earth[J/OL]. Progress in Lasers and Optoelectronics: 1–16[2021-03-17].http://kns.cnki.net/kcms/detail/31.1690.TN.20210106.1039.004.html. [Google Scholar]
  15. Xu Wei, Li Penghui, Sheng Yuxing, Hu Yang. Review and prospect of landslide monitoring methods[J]. Anhui Architecture, 2020, 27(08): 92–94+102. [Google Scholar]
  16. Yang Shun, Pan Huali, Wang Jun, et al. A review of the research status of debris flow monitoring and early warning[J]. Hazard Science, 2014, 150–156. [CrossRef] [Google Scholar]
  17. Fan Jing, Xie Jianbin, Wang Jinlong, et al. Overview of Debris Flow Monitoring System in Wireless Heterogeneous Sensor Network[J]. Journal of Yunnan Minzu University(Natural Science Edition), 2014, 1–10. [Google Scholar]
  18. Zhou Ming. A comparative study on geoacoustic and infrasound characteristics of different types of debris flow[D]: Guangxi University, 2014. [Google Scholar]
  19. Wei Gaorong. Design of Debris Flow Infrasound Monitoring and Early Warning System [D]: China University of Geosciences (Beijing), 2017. [Google Scholar]
  20. Cui Wenjie. Design and analysis of debris flow monitoring system based on infrasound[D]: Shandong University of Science and Technology, 2017. [Google Scholar]
  21. Xu Wenjie. Research and design of debris flow monitoring system based on infrasound[D]: Donghua University, 2013. [Google Scholar]
  22. Liu Yunlong, Tian You, Feng Xu, Zheng Que, Chi Huanzhao. A Review of Microseismic Technology and Application Research[J]. Advances in eophysics, 2013, 28(04): 1801–1808. [Google Scholar]
  23. Yuan Zhonghou. Research and Design of Debris Flow Early Warning Monitoring Sensing Device[D]: Chengdu University of Technology, 2015. [Google Scholar]
  24. Li Xiaoen, Zhou Liang, Su Fenzhen, Wu Wenzhou. Research progress on the application of InSAR technology in landslide disasters[J]. Journal of Remote Sensing, 2021, 25(02): 614–629. [Google Scholar]
  25. Gong Bo, Jiang Long, Wang Zhenhua. Prediction and prediction of Wujiang landslide based on deformation space-time evolution[J]. Hunan Water Resources and Hydropower, 2020(06): 4–9. [Google Scholar]
  26. Li Ming. Landslide lateral boundary survey and morphological test based on microseismic monitoring technology [J]. Surface Mining echnology, 2015(08): 49–51. [Google Scholar]
  27. Tan Wanpei. Basic theory and current situation of rainstorm debris flow forecasting research in China[J]. Journal of Soil Erosion and Soil and Water Conservation, 1996, (1): 8. [Google Scholar]
  28. Zhong Dunlun, Zhang Jinshan, Xie Hong, et al. Exploration of Debris Flow Warning Technology [J]. Journal of Mountainous Sciences, 2011, 29(2): 234–242. [Google Scholar]
  29. Liu Hanlong, Ma Yanbin, Crane Wengang, Wen Haijia. A review of the application of big data technology in geological disaster prevention and control[J/OL]. Chinese Journal of Disaster Prevention and Mitigation Engineering: 1–13[2021-03-17]. https://doi.rg/10.13409/j.cnki.jdpme.2021.04.002. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.