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How to avoid false interpretations of Sentinel-1A TOPSAR interferometric data in landslide mapping? A case study: recent landslides in Transdanubia, Hungary

Author

Listed:
  • I. P. Kovács

    (University of Pécs)

  • T. Bugya

    (University of Pécs)

  • Sz. Czigány

    (University of Pécs)

  • M. Defilippi

    (sarmap SA)

  • D. Lóczy

    (University of Pécs)

  • P. Riccardi

    (sarmap SA)

  • L. Ronczyk

    (University of Pécs)

  • P. Pasquali

    (sarmap SA)

Abstract

It is a crucial issue to better understand the usability of Sentinel-1 satellites in geomorphologic applications, since Sentinel-1 and the Copernicus Program are considered to be the workhorse of Earth observation by the European Space Agency during the next decades. Yet, a very limited experience is available on the applicability of Sentinel-1 images in the detection and identification of surface deformations and especially landslide mapping and monitoring in densely vegetated (low-coherence) areas. Few Synthetic Aperture Radar images (not more than 20) are sufficient for a successful run of interferometric stacking algorithms. This number is really low compared to the tremendous data flow of Sentinel-1 images that are available for interferometric analysis nowadays. Despite the availability of acquisitions, only a few papers exist on the accuracy of Sentinel-1 data, signal-to-noise ratio and the value of the acquired imagery for geomorphologic interpretation. Two test sites and a control site—affected by active surface deformations—have been investigated using 40 Sentinel-1A images and conventional persistent scatterers (PSI) method. PSI results have been combined with the geomorphologic information of the studied sites. We verified that the given number of Sentinel-1A acquisitions provide a unique base for surface deformation recognition and mapping in low-coherence areas. We found that scatterers were corrupted by a strong noise if their line of sight (LOS) velocity was below ± 6–7 mm/year all over the three test sites, although noise can easily be reduced. Noise reduction was achieved by a significant increase of the length of time series, i.e., time range between the first and last image to reduce the effect of atmospheric phase screen (APS).

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  • I. P. Kovács & T. Bugya & Sz. Czigány & M. Defilippi & D. Lóczy & P. Riccardi & L. Ronczyk & P. Pasquali, 2019. "How to avoid false interpretations of Sentinel-1A TOPSAR interferometric data in landslide mapping? A case study: recent landslides in Transdanubia, Hungary," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 96(2), pages 693-712, March.
  • Handle: RePEc:spr:nathaz:v:96:y:2019:i:2:d:10.1007_s11069-018-3564-9
    DOI: 10.1007/s11069-018-3564-9
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    References listed on IDEAS

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    1. Daniela Piacentini & Stefano Devoto & Matteo Mantovani & Alessandro Pasuto & Mariacristina Prampolini & Mauro Soldati, 2015. "Landslide susceptibility modeling assisted by Persistent Scatterers Interferometry (PSI): an example from the northwestern coast of Malta," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 78(1), pages 681-697, August.
    2. Chang-Jo Chung & Andrea Fabbri, 2003. "Validation of Spatial Prediction Models for Landslide Hazard Mapping," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 30(3), pages 451-472, November.
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    1. Matthias Schlögl & Karlheinz Gutjahr & Sven Fuchs, 2022. "The challenge to use multi-temporal InSAR for landslide early warning," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(3), pages 2913-2919, July.
    2. İbrahim Arslan & Mehmet Topakcı & Nusret Demir, 2022. "Monitoring Maize Growth and Calculating Plant Heights with Synthetic Aperture Radar (SAR) and Optical Satellite Images," Agriculture, MDPI, vol. 12(6), pages 1-27, June.

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