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Earth Science Informatics

, Volume 10, Issue 3, pp 287–301 | Cite as

Unmanned aerial vehicle based remote sensing method for monitoring a steep mountainous slope in the Three Gorges Reservoir, China

  • Haifeng HuangEmail author
  • Jingjing Long
  • Haiyu Lin
  • Lei Zhang
  • Wu Yi
  • Bangjun Lei
Research Article

Abstract

Monitoring has been considered to be the most effective means of preventing and mitigating geo-hazards. Unmanned aerial vehicle (UAV) based remote sensing has been proven to be a viable method for monitoring relatively flat areas, but has typically encountered challenges on steep mountainous slopes. The Qinglingou Slope, which is located at the head of the Three Gorges Reservoir, China, was selected as a case study, and a UAV-based remote sensing method was applied to monitor this steep mountainous slope. The UAV, which was equipped with a camera, was used to acquire images on May 10 and Sept. 13, 2015. At the same time, a plan for establishing and measuring a detailed network of ground control points (GCPs) and check points was carefully designed and implemented, according to the local conditions. Georeferenced digital surface models (DSMs) and digital orthophotos were obtained by photogrammetric processing. Based on the results, a simple and quick method that identified and quantified slope deformation by calculating and analyzing the changes in the DSMs was developed. The results showed that the UAV-based remote sensing method was rapid, safe and effective, and it could be valuable for monitoring a large number of steep mountainous slopes in the Three Gorges Reservoir.

Keywords

Unmanned aerial vehicle (UAV) Remote sensing Slope monitoring Digital surface model (DSM) Digital orthophoto Volume change 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (41302260/D0215), the Open Research Fund of the Key Laboratory of Disaster Prevention and Mitigation of Hubei Province (2016KJZ16), the Open Research Fund of the Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering (2016KLA02), and in part by the Hubei Science and Technology Support Program (2015 BCE070, 2015 BCE038) and the Innovation Groups Project of the Natural Science Foundation of Hubei Province (2015CFA025).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Haifeng Huang
    • 1
    • 2
    • 3
    Email author
  • Jingjing Long
    • 1
    • 3
  • Haiyu Lin
    • 1
    • 3
  • Lei Zhang
    • 1
    • 3
  • Wu Yi
    • 3
    • 4
  • Bangjun Lei
    • 2
  1. 1.Key Laboratory of Disaster Prevention and Mitigation of Hubei ProvinceChina Three Gorges UniversityYichangPeople’s Republic of China
  2. 2.Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric EngineeringChina Three Gorges UniversityYichangPeople’s Republic of China
  3. 3.National Field Observation and Research Station of Landslides in the Three Gorges Reservoir Area of Yangtze RiverChina Three Gorges UniversityYichangPeople’s Republic of China
  4. 4.Collaborative Innovation Center for Geo-Hazards and Eco-Environment in the Three Gorges AreaYichangPeople’s Republic of China

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