Abstract
Landslides are serious geologic hazards which have occurred in most countries and can cause significant loss of life and damage to property. The loss and damage may be avoided to some extent by monitoring and early warning systems for landslides. Currently, the most popular method to detect landslides is the wireless sensor network. In this paper, a human–machine cooperation system is proposed, which not only employs 500 sensor sets to collect data in the conventional way but also mobilizes over 6000 people to inspect landslides and gather data by simple tools daily, to take advantage of human wisdom and mobility to remedy the weakness of fixed sensors, which could not move, observe, think, and make decisions. For its 12 years of application in the Three Gorges Reservoir Region, China, the system has successfully predicted most threats which take place nearly 100 times each year.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Benoit L, Briole P, Martin O, Thom C, Malet JP, Ulrich P (2015) Monitoring landslide displacements with the geocube wireless network of low-cost gps. Eng Geol 195:111–121
Colesanti C, Wasowski J (2006) Investigating landslides with space-borne synthetic aperture radar (SAR) interferometry. Eng Geol 88(3–4):173–199
Dingfa H, Jun Q (1998) GPS-based target monitoring and navigation system for remote sensing-equipped flying balloon. In: Proc. SPIE 3504, Optical remote sensing for industry and environmental monitoring, pp. 131–135. https://doi.org/10.1117/12.319526
Jaboyedoff M, Oppikofer T, Abellan A, Derron MH, Loye A, Metzger R, Pedrazzini A (2012) Use of LIDAR in landslide investigations: a review. Nat Hazards 61(1):5–28
Ju Np, Huang J, Huang Rq, He Cy, Li Yr (2015) A real-time monitoring and early warning system for landslides in southwest china. J Mt Sci 12(5):1219–1228
Kaczmarek H, Mazaeva OA, Kozyreva EA, Babicheva VA, Tyszkowski S, Rybchenko AA, Brykala D, Bartczak A, Skowinski M (2016) Impact of large water level fluctuations on geomorphological processes and their interactions in the shore zone of a dam reservoir. J Great Lakes Res 42(5):926–941. https://doi.org/10.1016/j.jglr.2016.07.024
Lami Y, Nocera G, Genon-Catalot D, Lagreze A, Fourty N (2016) Landslide prevention using a buried sensor network. In: 2016 IEEE radio and antenna days of the Indian Ocean (Radio)
Maria Mateos R, Azanon JM, Roldan FJ, Notti D, Perez-Pena V, Galve JP, Luis Perez-Garcia J, Colomo CM, Gomez-Lopez JM, Montserrat O, Devantery N, Lamas-Fernandez F, Fernandez-Chacon F (2017) The combined use of PSInSAR and UAV photogrammetry techniques for the analysis of the kinematics of a coastal landslide affecting an urban area (SE Spain). Landslides 14(2):743–754
Palis E, Lebourg T, Tric E, Malet JP, Vidal M (2017) Long-term monitoring of a large deep-seated landslide (La Clapiere, South-East French Alps): initial study. Landslides 14(1):155–170. https://doi.org/10.1007/s10346-016-0705-7
Ramesh MV (2009) Real-time wireless sensor network for landslide detection. In: 2009 3rd international conference on sensor technologies and applications (Sensorcomm 2009) pp 405–409
Vera JE, Mora SF, Cervantes RA (2016) Design and testing of a network of sensors on land surfaces to prevent landslides. In: 2016 IEEE biennial congress of Argentina (Argencon)
Xu Q, Liu H, Ran J, Li W, Sun X (2016) Field monitoring of groundwater responses to heavy rainfalls and the early warning of the Kualiangzi landslide in Sichuan Basin, Southwestern China. Landslides 13(6):1555–1570. https://doi.org/10.1007/s10346-016-0717-3
Yue W, Xuebin H, Shaoquan X, Wenming C, Yingbing L (2006) Application of GPS technique for geological hazard professional monitoring in TGR area. J Geomatics 31(5):16-17
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
Li, Z., Cheng, G., Cheng, W., Mei, H. (2019). People as Sensors: Towards a Human–Machine Cooperation Approach in Monitoring Landslides in the Three Gorges Reservoir Region, China. In: Guo, S., Zeng, D. (eds) Cyber-Physical Systems: Architecture, Security and Application. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-92564-6_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-92564-6_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-92563-9
Online ISBN: 978-3-319-92564-6
eBook Packages: EngineeringEngineering (R0)