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Vision-Based Terrestrial Surface Monitoring

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Terrigenous Mass Movements

Abstract

The monitoring of geo-risk areas is getting more and more importance due to increasing damage caused by hazardous events such as rock slides, as a result of the environmental change. Terrestrial long-range sensing (up to several kilometres of distance between sensor and target region) is a valuable means for monitoring such sites using non-signalized targets in high resolution, which is necessary to detect regions, amount, direction and trends of motion early enough to take risk mitigation measures. The technology to realize such a sensing strategy combines various fields of research, such as sensor technology, surveying, computer vision and geological sciences. This chapter describes two vision-based sensing techniques suited for terrestrial surface monitoring (terrestrial laser scanning, and image-based tacheometers), and their sensing strategies, data processing and data exploitation issues. Examples for monitoring frameworks are given, and technical and engineering solutions are described. A set of applications from permafrost, glacier and snow cover monitoring, as well as rock fall site monitoring shows the relevance, technologic maturity and limits of existing approaches. Rock falls and other geo-hazards being the major fields of application for such systems, the chances of saving lives, protecting infrastructure and habitats and avoiding injury to field personnel are increased so that the better and more accurate event can be monitored. The research and technology described in this chapter will help the surveying, photogrammetry and computer vision community fighting global warming impacts.

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Notes

  1. 1.

    Of course an active system such as Radar Interferometry is not prone to such restrictions.

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Acknowledgments

The content of this chapter was produced in multiple research projects which deserve further mentioning. Namely the i-MeaS—“An Intelligent Image-Based Measurement system for Geo-Hazard Monitoring” project (info.tuwien.ac.at/ingeo/research/imeas) which is funded by the Austrian Science Fund (Fond zur Förderung der wissenschaftlichen Forschung Österreich, FWF) (project number: L514), the project ALPCHANGE (www.alpchange.at) also funded by the FWF (project number P18304-N10) and the “K plus program” of “K plus Competence Center Advanced Computer Vision” together with FWF Project P14664. Furthermore we kindly acknowledge the help of Viktor Kaufmann (Institute of Remote Sensing and Photogrammetry, Graz University of Technology) for providing data from geodetic surveys and kindly reviewing this chapter. Viktor Kaufmann, Gerhard Karl Lieb, Andreas Kellerer-Pirklbauer-Eulenstein and Herwig Proske provided valuable source material from related publications, this is very much appreciated. We also thank students of the Institute of Geography and Regional Science, University of Graz and the Institute of Remote Sensing and Photogrammetry, Graz University of Technology, Austria as well as several volunteers of the National Park Hohe Tauern for their support during field campaigns. Last but not least we thank our important research partners and funding sources Joanneum Research (www.joanneum.at) and Dibit Messtechnik GmbH (www.dibit-scanner.at).

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Authors and Affiliations

  1. DIGITAL, Institute for Information and Communication Technologies, JOANNEUM RESEARCH, Steyrergasse 17, Graz, 8010, Austria

    Gerhard Paar, Niko Benjamin Huber & Arnold Bauer

  2. Institute of Remote Sensing and Photogrammetry, Graz University of Technology, Steyrergasse 30, Graz, 8010, Austria

    Michael Avian

  3. Institute for Geodesy, GIS and Land Management, University of Technology, Munich, Arcisstrasse 21, 80333, Munich, Germany

    Alexander Reiterer

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  1. Gerhard Paar
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Correspondence to Gerhard Paar .

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  1. , Institute of Advanced Technology Spatial, University Putra Malaysia (UPM) Serdang, Selangor Darul Ehsan, 43400, Malaysia

    Biswajeet Pradhan

  2. TU Dresden, Mommsenstr. 23, Dresden, 01062, Germany

    Manfred Buchroithner

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Paar, G., Huber, N.B., Bauer, A., Avian, M., Reiterer, A. (2012). Vision-Based Terrestrial Surface Monitoring. In: Pradhan, B., Buchroithner, M. (eds) Terrigenous Mass Movements. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25495-6_10

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