Welcome to Scholar Publishing Group

International Journal of Engineering Technology and Construction, 2022, 3(2); doi: 10.38007/IJETC.2022.030201.

Agricultural Geological Landslide Monitoring Based on Beidou Navigation System


Zheng Zeng

Corresponding Author:
Zheng Zeng

Hope Academy, Xi’an Jiaotong University, Xi’an, China


Discuss the application of Beidou navigation system in agricultural geological landslide monitoring. To conduct a simulated monitoring test in a mountainous area in southwestern China, first set up observation points to monitor the data under three sets of plans. The three sets of plans are specifically expressed as GPS single-system dynamic real-time precision single-point positioning technology (PPP), single-system RTK positioning , Single system baseline solution, BDS single system dynamic real-time precision single point positioning technology (PPP), single system RTK positioning, single system baseline solution and GPS / BDS combined dynamic real-time precision single point positioning technology (PPP), combined RTK positioning , Combined baseline solution. Based on the above monitoring, a landslide monitoring system under the Beidou navigation system is set up to analyze the monitoring effect of the Beidou navigation system on geological landslides. Through verification analysis, we know that in the analysis of dynamic precision single-point positioning technology, the accuracy of BDS, GPS / BDS is better than GPS in the same base station monitoring point, in the three directions of ENU, in terms of plane accuracy, point accuracy, GPS / BDS has the best accuracy, followed by BDS, and GPS has the worst; within the set distance range, the convergence time of GPS / BDS is much faster than BDS and GPS; PPP positioning accuracy of BDS system is slightly worse than GPS system, BDS / GPS combined PPP has the best positioning accuracy, reaching the centimeter level. In the real-time dynamic relative positioning analysis, the accuracy of the three schemes of ENU in all three directions is in the millimeter level. The RTK accuracy results under BDS are slightly lower than the GPS system, and the BDS / GPS combined RTK positioning accuracy is the highest. In the static relative positioning analysis, the accuracy obtained by the three schemes is equivalent, which is better than 5mm. Based on the Beidou navigation system positioning analysis technology, the accuracy and reliability required for landslide monitoring can be achieved. The real-time landslide monitoring system under the Beidou navigation system can actually meet the engineering accuracy and reliability requirements of landslide monitoring.


Ecological Environment, Geological Landslide, Satellite Navigation, Monitoring System

Cite This Paper

Zheng Zeng. Agricultural Geological Landslide Monitoring Based on Beidou Navigation System. International Journal of Engineering Technology and Construction (2022), Vol. 3, Issue 2: 1-13. https://doi.org/10.38007/IJETC.2022.030201.


[1] Jiao, Juying, Wang, Zhijie, Wei, Yanhong, Su, Yuan, Cao, Binting, & Li, Yujin.(2017). “Characteristics of Erosion Sediment Yield with Extreme Rainstorms in Yanhe Watershed Based on Field Measurement”,Transactions of the Chinese Society of Agricultural Engineering,33(13), pp.159-167.DOI: 10.11975/j.issn.1002-6819.2017.13.021

[2] G. Duan, R. Niu, L. Peng, & J. Fu. (2017).“A Landslide Displacement Prediction Research Based on Optimization- Parameter Arima Model under the inducing Factors”,Geomatics & Information Science of Wuhan University, 42(4), pp.531-536. DOI:10.13203/j.whugis20140913

[3] Hua LI. (2018).“Tunnel Deformation Monitoring Based on Vision Assistant”, Journal of Mechanical Engineering, 54(1), pp.90. https://doi.org/10.3901/JME.2018.01.090

[4] Hiroomi NAKAZATO, Hidekazu TAGASHIRA, Tasuku NAGAE, Ryoichi TOMETSUKA, & Junichi KABAMOTO. (2018).“Wireless Sensors for Monitoring Landslide with Multiple Slip Surfaces”, Journal of the Japan Landslide Society, 55(5), pp.223-231. https://doi.org/10.3313/jls.55.223

[5] Yuming Zhang, Xinli Hu, Dwayne D. Tannant, Guangcheng Zhang, & Fulin Tan.(2018). “Field Monitoring and Deformation Characteristics of A Landslide with Piles in the Three Gorges Reservoir Area”, Landslides, 15(5), pp.581-592. https://doi.org/10.1007/s10346-018-0945-9

[6] Zhang, Guijun, Zhao, Li, Zhang, Pengtao, Zhang, Yigong, & Wei, Minghuan. (2017).“Cultivated Land Resource Security Evaluation and Consolidation Division Based on Farmland Classification”, Nongye Gongcheng Xuebao/transactions of the Chinese Society of Agricultural Engineering, 33(16), pp.248-255. DOI:10.11975/j.issn.1002-6819.2017.16.033

[7] J.-Y. Yu, X.-D. Shao, B.-F. Yan, & P. Zhu. (2016).“Research and Development on Global Navigation Satellite System Technology for Bridge Health Monitoring”, China Journal of Highway & Transport, 29(4), pp.30-41. http://zgglxb.chd.edu.cn/EN/Y2016/V29/I4/30

[8] Xiaohui Yuan , Reem Atassi, Geological Landslide Disaster Monitoring Based on Wireless Network Technology, International Journal of Wireless and Ad Hoc Communication, 2021, Vol. 2, No. 1, pp: 21-32. https://doi.org/10.54216/IJWAC.020102

[9] Cai-Cong Wu, Peng Qiao, Jing Zhao, Jie Wang, & Ya-Ping Cai. (2016).“Evaluating Model and Beidou Based Management System for Scale Operation of Cotton-pickers”, Positioning, 7(1), pp.21-31. https://doi.org/10.4236/pos.2016.71002

[10] Ooi Ghee Leng, Tan Pin Siang, Lin Meei-Ling, Wang Kuo-Lung, Zhang,Qian, & Wang Yu-Hsing. (2016).“Near Real-time Landslide Monitoring with the Smart Soil Particles”, Japanese Geotechnical Society Special Publication, 2(28), pp.1031-1034. https://doi.org/10.3208/jgssp.HKG-05

[11] Sonia Jenifer Rayen, Survey On Smart Cane For Visually Impaired Using IOT, Journal of Cognitive Human-Computer Interaction, 2021, Vol. 1, No. 2, pp: 81 – 85. https://doi.org/10.54216/JCHCI.010205

[12] L. Kang, X. Lu, X. Wang, C. He, & Y. Rao. (2018).“Navigation Signal Chip Domain Assessment on Beidou Navigation System”, Journal of Electronics & Information Technology, 40(4), pp.1002-1006. DOI:10.11999/JEIT170591

[13] Shaojie Zhang, Luqiang Zhao, Ricardo Delgado-Tellez, & Hongjun Bao. (2016).“A Physics-based Probabilistic Forecasting Model for Rainfall-induced Shallow Landslides at Regional Scale”, Natural Hazards & Earth System Sciences, 18(3), pp.1-17. https://doi.org/10.5194/nhess-2016-348

[14] X. Wang, Y. Zhang, M. Xu, B. Xing, & H. Zeng. (2017).“Development of Integrated Network Platform for Heterogeneous Agricultural Information Remote Monitoring Terminal”,Nongye Gongcheng Xuebao/transactions of the Chinese Society of Agricultural Engineering,33(23),pp. 211-218.

[15] Rajalakshmi, M., Saravanan, V., Arunprasad, V., A., C., Khalaf, O. I. et al. (2022). Machine Learning for Modeling and Control of Industrial Clarifier Process. Intelligent Automation & Soft Computing, 32(1), 339-359. https://doi.org/10.32604/iasc.2022.021696