Vision-Based Terrestrial Surface Monitoring

  • Gerhard PaarEmail author
  • Niko Benjamin Huber
  • Arnold Bauer
  • Michael Avian
  • Alexander Reiterer


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.


Terrestrial laser scanning Image-based tacheometers Digital surface model Point tracking Deformation monitoring Rock glacier movement Glacier change monitoring Snow avalanche prediction Geo-risk monitoring 



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 ( which is funded by the Austrian Science Fund (Fond zur Förderung der wissenschaftlichen Forschung Österreich, FWF) (project number: L514), the project ALPCHANGE ( 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 ( and Dibit Messtechnik GmbH (


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Gerhard Paar
    • 1
    Email author
  • Niko Benjamin Huber
    • 1
  • Arnold Bauer
    • 1
  • Michael Avian
    • 2
  • Alexander Reiterer
    • 3
  1. 1.DIGITAL, Institute for Information and Communication TechnologiesJOANNEUM RESEARCHGrazAustria
  2. 2.Institute of Remote Sensing and PhotogrammetryGraz University of TechnologyGrazAustria
  3. 3.Institute for Geodesy, GIS and Land ManagementUniversity of Technology, MunichMunichGermany

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