Abstract
This paper presents an integrated approach to landslide research based on remote sensing and sensor networks. This approach is composed of three important parts: (i) landslide susceptibility mapping using remote-sensing techniques for susceptible determination of landslide spots; (ii) scaled-down landslide simulation experiments for validation of sensor network for landslide monitoring, and (iii) in situ sensor network deployment for intensified landslide monitoring. The study site is the Taziping landslide located in Hongkou Town (Sichuan, China). The landslide features generated by landslides triggered by the 2008 Wenchuan Earthquake were first extracted by means of object-oriented methods from the remote-sensing images before and after the landslides events. On the basis of correlations derived between spatial distribution of landslides and control factors, the landslide susceptibility mapping was carried out using the Artificial Neural Network (ANN) technique. Then the Taziping landslide, located in the above mentioned study area, was taken as an example to design and implement a scaled-down landslide simulation platform in Tongji University (Shanghai, China). The landslide monitoring sensors were carefully investigated and deployed for rainfall induced landslide simulation experiments. Finally, outcomes from the simulation experiments were adopted and employed to design the future in situ sensor network in Taziping landslide site where the sensor deployment is being implemented.
Highlights
Landslides are major geo-hazards heavily impacting many regions of the world in terms of human lives and economic losses [1]
A systematic approach to landslide investigation based on remote sensing and Sensor
Network (SN) has been developed and assessed. This approach is composed of three parts, landslide susceptibility mapping for susceptible spots determination in Hongkou Town (Sichuan, China), scaled-down landslide simulation for SN prototype system test on the campus of Tongji University (Shanghai, China), and in situ SN design for field landslide observation at the Taziping landslide, Hongkou Town
Summary
Landslides are major geo-hazards heavily impacting many regions of the world in terms of human lives and economic losses [1]. Landslide susceptibility mapping is an attempt to derive spatial variation of area-based slope failure probability or instability at a regional scale This is based on a number of factors categorized into (a) preparatory factors such as lithology and geomorphology; and (b) triggering factors such as seismicity, rainfall, land cover, and anthropogenic causes. A Sensor Network (hereafter “SN”) can comprehend the different categories of sensors that are in use for gathering information about the underground layers, about the topographic of the slope surface, and about meteorological conditions These data inputs need to be updated at high-to-medium level of frequency (i.e., from minutes to within a few days). Information concerning the surrounding region (human settlements, hydraulic networks, communication infrastructures) and important targets (such as river barrages, energy power-plants and the like) is fundamental for designing risk scenarios outlining the serious impacts that could be caused directly by the landslide or by other domino effect such as the Na-Tech disasters [29,30]
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