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Introduction: Landslide Monitoring and Warning

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Advancing Culture of Living with Landslides (WLF 2017)

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Abstract

The Session Landslide Monitoring and Warning: Monitoring Techniques and Technologies, and Early Warning Systems, as a part of WLF4 Volume 3 Advances in Landslide Technology, collected the contributions that deal with techniques and technologies employed in landslide monitoring and establishing of early warning systems with the aims to reduce or completely eliminate landslide risk. These techniques and technologies include a wide spectra of monitoring equipment united in monitoring sensor networks including modern advanced remote sensing technologies based on satellite observations of Earth surface.

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Acknowledgements

The editors of the WLF4 Volume 3 Advances in Landslide Technology, Session 1 for Landslide Monitoring and Warning: Monitoring Techniques and Technologies, and Early Warning Systems would like to thank all the reviewers who have reviewed the papers submitted to this Session.

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Authors and Affiliations

  1. University of Rijeka, Faculty of Civil Engineering, Radmile Matejčić 3, 51000, Rijeka, Croatia

    Željko Arbanas

  2. University of Florence, Department of Earth Sciences, Via La Pira 4, 50121, Florence, Italy

    Veronica Tofani

Authors
  1. Željko Arbanas
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  2. Veronica Tofani
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Corresponding author

Correspondence to Željko Arbanas .

Editor information

Editors and Affiliations

  1. Faculty of Civil and Geodetic Engineering, University of Ljubljana, Ljubljana, Slovenia

    Matjaž Mikoš

  2. Faculty of Civil Engineering, University of Rijeka, Rijeka, Croatia

    Željko Arbanas

  3. China Institute of Geo-Environment Monitoring, China Geological Survey, Beijing, China

    Yueping Yin

  4. International Consortium on Landslides (ICL), Kyoto, Japan

    Kyoji Sassa

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© 2017 Springer International Publishing AG

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Arbanas, Ž., Tofani, V. (2017). Introduction: Landslide Monitoring and Warning. In: Mikoš, M., Arbanas, Ž., Yin, Y., Sassa, K. (eds) Advancing Culture of Living with Landslides. WLF 2017. Springer, Cham. https://doi.org/10.1007/978-3-319-53487-9_2

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