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Landslide Science and Practice pp 357–363Cite as

Advanced Image Analysis for Automated Mapping of Landslide Surface Fissures

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Abstract

Surface fissures are potential indicators of slope instabilities and considerably influence infiltration characteristics of the soil. The increasing availability of unmanned aerial vehicles (UAVs) enables the observation of surface features at unprecedented detail and this study develops an image processing method combining Gaussian filters and object-oriented image analysis to map such features in very-high resolution (VHR) aerial images largely automatically. At three different time steps the results of the technique are compared with expert elaborated maps.

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Acknowledgments

The work described in this paper was supported by the project SafeLand “Living with landslide risk in Europe: Assessment, effects of global change, and risk management strategies” under Grant Agreement No. 226479 in the 7th Framework Programme of the European Commission, the project SISCA ‘Système Intégré de Surveillance de Crises de Glissements de Terrain’ funded by the French Research Agency (ANR), and the project Grosshang “Coupling of Flow and Deformation Processes for Modeling the Movement of Natural Slopes” funded by the Deutsche Forschungsgemeinschaft (DFG). These supports are gratefully acknowledged.

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Authors and Affiliations

  1. Faculty of Geo-Information Science and Earth Observation, ITC, University of Twente, Enschede, The Netherlands

    A. Stumpf & N. Kerle

  2. Laboratoire Image, Ville, Environnement, CNRS ERL7230, University of Strasbourg, Strasbourg, France

    A. Stumpf

  3. Institut für Geophysik, University of Stuttgart, Stuttgart, Germany

    U. Niethhammer, S. Rothmund & M. Joswig

  4. Institut de Physique du Globe de Strasbourg, CNRS UMR 7516, University of Strasbourg, Strasbourg, France

    S. Rothmund, A. Mathieu & J. P. Malet

Authors
  1. A. Stumpf
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  2. U. Niethhammer
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  3. S. Rothmund
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  4. A. Mathieu
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  5. J. P. Malet
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  6. N. Kerle
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  7. M. Joswig
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Corresponding author

Correspondence to A. Stumpf .

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Editors and Affiliations

  1. Geological Survey of Italy, ISPRA - Italian Institute for Environmen, Rome, Italy

    Claudio Margottini

  2. ICL - International Consortium on Landsl, Florence, Italy

    Paolo Canuti

  3. Kyoto University Uji-Campus, Uji, Kyoto, Japan

    Kyoji Sassa

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Stumpf, A. et al. (2013). Advanced Image Analysis for Automated Mapping of Landslide Surface Fissures. In: Margottini, C., Canuti, P., Sassa, K. (eds) Landslide Science and Practice. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31445-2_46

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