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Landslides

, Volume 2, Issue 3, pp 221–228 | Cite as

Accuracy assessment of InSAR derived input maps for landslide susceptibility analysis: a case study from the Swiss Alps

  • Lalan P. Singh
  • C. J. van WestenEmail author
  • P. K. Champati Ray
  • P. Pasquali
Original Article

Abstract

In recent years SAR interferometry has become a widely used technique for measuring altitude and displacement of the surface of the earth. Both these capabilities are highly relevant for landslide susceptibility studies. Although there are many problems that make the use of SAR interferometry less suitable for landslide inventory mapping, it’s use in landslide monitoring and in the generation of input maps for landslide susceptibility assessment looks very promising. The present work attempts to evaluate the usefulness and limitations of this technique based on a case study in the Swiss Alps. Input maps were generated from ERS repeat pass data using SAR interferometry. A land cover map has been generated by image classification of multi-temporal SAR intensity images. An InSAR DEM was generated and a number of maps were derived from it, such as slope-, aspect, altitude- and slope form classes. These maps were used to generate landslide and rockfall susceptibility maps, which give fairly well acceptable results. However, a comparison of the InSAR DEM with the conventional Swisstopo DEM, indicated significant errors in the absolute height and slope angles derived from InSAR, especially along the ridges and in the valleys. These errors are caused by low coherence mostly due to layover and shadow effects. Visual comparison of stereo images created from hillshading maps and corresponding DEMs demonstrate that a considerable amount of topographic details have been lost in the InSAR-derived DEM. It is concluded that InSAR derived input maps are not ideal for landslide susceptibility assessment, but could be used if more accurate data is lacking.

Keywords

Landslide susceptibility InSAR Digital elevation models 

Notes

Acknowledgements

Part of this work was carried out in the framework of the DUP SLAM2 project “Service for Landslides Monitoring - Integration of Remote Sensing techniques with statistical methods for Landslide Monitoring and Risk Assessment” for the European Space Agency

We would like to thank Olivier Lateltin and Hugo Raetzo of the Swiss Federal Office for Water and Geology (FOWG) for providing us the landslide map of the study area, and Swisstopo for providing us the DHM25 Digital Elevation Model.

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Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  • Lalan P. Singh
    • 1
  • C. J. van Westen
    • 2
    Email author
  • P. K. Champati Ray
    • 3
  • P. Pasquali
    • 4
  1. 1.Geological Survey of IndiaIndia
  2. 2.International Institute for Geo-Information Science and Earth ObservationThe Netherlands
  3. 3.Indian Institute of Remote SensingDehradunIndia
  4. 4.Sarmap, Cascine de BaricoPurascaSwitzerland

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