Environmental Earth Sciences

, Volume 74, Issue 4, pp 3315–3332 | Cite as

Model test study on monitoring dynamic process of slope failure through spatial sensor network

  • Ping Lu
  • Hangbin Wu
  • Gang Qiao
  • Weiyue Li
  • Marco Scaioni
  • Tiantian Feng
  • Shijie Liu
  • Wen Chen
  • Nan Li
  • Chun Liu
  • Xiaohua Tong
  • Yang Hong
  • Rongxing Li
Original Article

Abstract

Landslides represent a major type of natural hazards worldwide. For development of risk mitigation capabilities, an effective system for monitoring dynamic process of slope failure, capable of gathering spatially distributed information before, during and after a landslide occurrence at real-time manner is essential. A spatial sensor network (SSN), which integrates the real-time communication infrastructure and observations from in situ sensors and remote sensing platforms, offers an efficient and effective approach for such purpose. In this paper, a SSN-based landslide monitoring system was designed and evaluated through a model test study conducted at Tongji University, China. This system, MUNOLD (MUlti-Sensor Network for Observing Landslide Disaster), has been designed as a comprehensive monitoring framework, including sensor observations, multi-channel wireless communication, remote data storage, visualization, data processing and data analysis. In this model test study, initial experimentation demonstrated the capabilities of the MUNOLD system for collecting real-time information about the dynamic process and propagation of slope failure. Innovatively, generated from the high-speed stereo images, the sequential surface deformation vector field can be created and may exhibit the dynamic process during the extremely critical and short period of the slope failure. After this model test study, the MUNOLD system is going to be further improved and extended in a landslide prone region in Sichuan Province, China.

Keywords

Spatial sensor network Landslide Model test Real-time monitoring Wireless communication Remote sensing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Ping Lu
    • 1
  • Hangbin Wu
    • 1
  • Gang Qiao
    • 1
  • Weiyue Li
    • 1
  • Marco Scaioni
    • 1
  • Tiantian Feng
    • 1
  • Shijie Liu
    • 1
  • Wen Chen
    • 2
  • Nan Li
    • 1
  • Chun Liu
    • 1
  • Xiaohua Tong
    • 1
  • Yang Hong
    • 3
  • Rongxing Li
    • 1
  1. 1.College of Surveying and Geo-Informatics, Center for Spatial Information Science and Sustainable Development ApplicationsTongji UniversityShanghaiChina
  2. 2.Engineering Center of SHMEC for Space Information and GNSSEast China Normal UniversityShanghaiChina
  3. 3.School of Civil Engineering and Environmental Science, National Weather CenterUniversity of OklahomaNormanUSA

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