Next Article in Journal
Time-Domain Functional Diffuse Optical Tomography System Based on Fiber-Free Silicon Photomultipliers
Previous Article in Journal
Value Systems Alignment Analysis in Collaborative Networked Organizations Management
Article Menu
Issue 12 (December) cover image

Export Article

Open AccessTechnical Note
Appl. Sci. 2017, 7(12), 1234; doi:10.3390/app7121234

A Multi-Source Early Warning System of MEMS Based Wireless Monitoring for Rainfall-Induced Landslides

1
Key Laboratory of Mountain Hazards and Surface Process, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
2
College of Hydrometeorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
3
Department of Civil & Environmental Engineering, Saitama University, Saitama 338-8570, Japan
*
Author to whom correspondence should be addressed.
Received: 22 October 2017 / Revised: 24 November 2017 / Accepted: 27 November 2017 / Published: 29 November 2017
View Full-Text   |   Download PDF [6233 KB, uploaded 29 November 2017]   |  

Abstract

Landslide monitoring and early warning systems are the most successful countermeasures to reduce fatalities and economic losses from landslide hazards. The traditional strategies such as GPS and extensometers are relatively expensive and difficult to be installed in steep, high mountains. In this study, a MEMS (Micro Electro Mechanical Systems) based multivariate wireless monitoring sensor unit was used to build a monitoring and early warning system for rainfall-triggered landslides, as one of the most practical and cost-effective countermeasures for hard-reached mountains. The multi-source wireless monitoring system and its well-developed equipment were tested in a landslide-prone slope to monitor the triggering of landslides and debris flows in the Wenchuan earthquake region, China. The variations of several state variables were observed, including the soil moisture content, soil matric suction, rainfall, inclination and ground vibration. The results of a slope stability analysis were benchmarked with the in situ measurements to identify the multivariate early warning parameters for rainfall-induced landslides. The proposed early warning system for the slope stability analysis can provide a more accurate prediction for rainfall-induced landslides and debris flows in earthquake hit regions. View Full-Text
Keywords: wireless early warning system; portable sensor unit; cost-effectiveequipment; multivariate thresholds; rainfall-induced landslides wireless early warning system; portable sensor unit; cost-effectiveequipment; multivariate thresholds; rainfall-induced landslides
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Yang, Z.; Shao, W.; Qiao, J.; Huang, D.; Tian, H.; Lei, X.; Uchimura, T. A Multi-Source Early Warning System of MEMS Based Wireless Monitoring for Rainfall-Induced Landslides. Appl. Sci. 2017, 7, 1234.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top