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Modern Technologies for Landslide Monitoring and Prediction pp 13–41Cite as

Close-Range Photogrammetric Techniques for Deformation Measurement: Applications to Landslides

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Abstract

In this chapter, the application of close-range photogrammetry for deformation measurements in the field of landslide investigation and monitoring is discussed. Main advantages of this approach are the non-contact operational capability, the large covered area on the slope to analyze, the high degree of automation, the high acquisition rate, the chance to derive information on the whole surface, not limited to a few control points (area-based deformation measurement), and, generally, a lower cost with respect to 3D scanning technology. Applications are organized into two categories: (1) surface-point tracking (SPT) and (2) comparison of surfaces obtained from dense image matching. Different camera configurations and geometric models to transform points from the image space to the object space are also discussed. In the last part of the chapter, a review of the applications reported in the literature and two case studies from the experience of the authors are reported.

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Notes

  1. 1.

    Although in the common technical language, the term ‘real time’ is used for sensors that are able to provide immediate outputs, in landslide monitoring the time frequency should be referred to the speed of the observed process (see Scaioni et al. (2014b)). Consequently, an earth observation system able to measure the deformation of slow-moving landslides with periodical monthly rate measurements can be considered a real-time system. Generally, the term ‘quasi-real time’ is used for those observations where some tasks of the measurement process introduce a short delay in the output of results. However, in ‘quasi-real time’ systems such delay does not influence the exploitation of the outcomes.

  2. 2.

    Despite of the name, stereo-camera systems are not usually aimed at obtaining the stereoscopic vision and cameras may be convergent to improve precision along depth (Fraser 1996).

  3. 3.

    The full resolution of the sensor (3,872 × 2,592 pixel) was not used.

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Acknowledgments

This research was partially funded by the 863 National High-tech R&D Program of China (No. 2012AA121302) and by the 973 National Basic Research Program of China (No. 2013CB733204). Also, this research was supported by the Italian Ministry of University and Research within the project FIRB—Futuro in Ricerca 2010 (No. RBFR10NM3Z).

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  1. College of Surveying and Geo-informatics, Tongji University, 1239 Siping Road, Shanghai, 200092, People’s Republic of China

    Marco Scaioni, Tiantian Feng, Ping Lu, Gang Qiao, Xiaohua Tong & Ron Li

  2. Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, via Ponzio 31, 20133, Milan, Italy

    Marco Scaioni, Luigi Barazzetti & Mattia Previtali

  3. Department of Civil, Environmental, Land Management Engineering and Architecture, University of Parma, via Parco Area delle Scienze, 181/a, 43124, Parma, Italy

    Riccardo Roncella

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  1. Marco Scaioni
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Correspondence to Marco Scaioni .

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  1. College of Surveying & Geo-Informatics, Department of Architecture, Built Environment and Construction Engineering,, Tongji University, Shanghai, Politecnico di Milano, Italy, China

    Marco Scaioni

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Scaioni, M. et al. (2015). Close-Range Photogrammetric Techniques for Deformation Measurement: Applications to Landslides. In: Scaioni, M. (eds) Modern Technologies for Landslide Monitoring and Prediction. Springer Natural Hazards. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45931-7_2

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