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Remote Sens. 2013, 5(9), 4319-4346; doi:10.3390/rs5094319
Article

Landslide Investigation with Remote Sensing and Sensor Network: From Susceptibility Mapping and Scaled-down Simulation towards in situ Sensor Network Design

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Received: 5 August 2013; in revised form: 3 September 2013 / Accepted: 3 September 2013 / Published: 6 September 2013
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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.
Keywords: landslide; sensor network; susceptibility mapping; remote sensing landslide; sensor network; susceptibility mapping; remote sensing
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.

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MDPI and ACS Style

Qiao, G.; Lu, P.; Scaioni, M.; Xu, S.; Tong, X.; Feng, T.; Wu, H.; Chen, W.; Tian, Y.; Wang, W.; Li, R. Landslide Investigation with Remote Sensing and Sensor Network: From Susceptibility Mapping and Scaled-down Simulation towards in situ Sensor Network Design. Remote Sens. 2013, 5, 4319-4346.

AMA Style

Qiao G, Lu P, Scaioni M, Xu S, Tong X, Feng T, Wu H, Chen W, Tian Y, Wang W, Li R. Landslide Investigation with Remote Sensing and Sensor Network: From Susceptibility Mapping and Scaled-down Simulation towards in situ Sensor Network Design. Remote Sensing. 2013; 5(9):4319-4346.

Chicago/Turabian Style

Qiao, Gang; Lu, Ping; Scaioni, Marco; Xu, Shuying; Tong, Xiaohua; Feng, Tiantian; Wu, Hangbin; Chen, Wen; Tian, Yixiang; Wang, Weian; Li, Rongxing. 2013. "Landslide Investigation with Remote Sensing and Sensor Network: From Susceptibility Mapping and Scaled-down Simulation towards in situ Sensor Network Design." Remote Sens. 5, no. 9: 4319-4346.


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