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Assessment of the Sentinel-1 based ground motion data feasibility for large scale landslide monitoring

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Abstract

In this paper, a systematic procedure to assess the feasibility of Advanced Differential Interferometric SAR (A-DInSAR) technique for landslide monitoring using SAR images acquired by Sentinel-1 sensors is presented. The methodology is named “Assessment of the advanced differentiaL interferometric synthetic aperture radar technique Feasibility for large scale lAndslide monitoring – ALFA” and it is structured in two main phases, which includes pre-processing and post-processing elaborations. The methodology was developed and tested in the Alpine sector of the Piedmont region in Italy, which represents a landslide prone area. In particular, ALFA represents a methodology based on previous algorithms available in the literature to assess the a-prior feasibility assessment and post-processing analysis of A-DInSAR data for landslide, which introduces three novel aspects such as (1) a systematic scheme suitable within regional practices; (2) the use of Sentinel-1 data and the development of (3) an index to take into account of the kind of distribution of the measuring points along the landslide. The approach was applied over an area extended about 5300 km2 affected by 5703 landslides mapped in the database of the Piedmont Region (Landslides information system in Piedmont—SIFRAP). Sentinel-1 images covering the period 2014–2018 were analysed. The results show the potential of the Sentinel-1 data for large-scale landslide monitoring. The developed methodology presents reliable tools that could be useful as feasibility for the use of Sentinel-1 data for landslide monitoring at regional and national scale.

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Acknowledgements

The work was developed in the framework of the Project “Servizio di analisi di dati radar interferometrici satellitari”. CIG80287920C2, CUP AdVitam: J85C17000120007—RiskFor: J69F18001670007. The data were provided by Piedmont Region and the Regional Environmental Agency of Piedmont (ARPA Piemonte, Italy) in the framework of this project (P.I. Claudia Meisina). The Sentinel-1 data were processed by TRE Altamira.

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Authors and Affiliations

  1. Department of Earth and Environmental Sciences, University of Pavia, Via Ferrata, 1, 27100, Pavia, Italy

    Roberta Bonì, Massimiliano Bordoni, Valerio Vivaldi, Francesco Zucca & Claudia Meisina

  2. Regione Piemonte, Direzione Regionale Opere pubbliche, Difesa del suolo, Montagna, Foreste, Protezione civile, Trasporti e Logistica - Settore Geologico, C.so Bolzano 44, 10121, Torino, Italy

    Carlo Troisi

  3. Dipartimento Rischi Naturali e Ambientali, ARPA Piemonte - Agenzia Regionale per la Protezione Ambientale, Via Pio VII, 9, 10135, Torino, Italy

    Mauro Tararbra & Luca Lanteri

Authors
  1. Roberta Bonì
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  2. Massimiliano Bordoni
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  3. Valerio Vivaldi
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  4. Carlo Troisi
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  5. Mauro Tararbra
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  6. Luca Lanteri
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  7. Francesco Zucca
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  8. Claudia Meisina
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Contributions

Roberta Bonì developed and test the methodological approach in the framework of the post-doc project financed by the Dept. of Earth and Environment Sciences of the University of Pavia, “Assegno premiale di tipo A” (supervisor Claudia Meisina) and prepared the manuscript; Massimiliano Bordoni, Francesco Zucca and Valerio Vivaldi helped in the interpretation of the results; Carlo Troisi, Mauro Tararbra and Luca Lanteri supplied the data and supported their analysis; Claudia Meisina provided support and guidance throughout the research process. All authors co-wrote and reviewed the manuscript.

Corresponding author

Correspondence to Roberta Bonì.

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Bonì, R., Bordoni, M., Vivaldi, V. et al. Assessment of the Sentinel-1 based ground motion data feasibility for large scale landslide monitoring. Landslides 17, 2287–2299 (2020). https://doi.org/10.1007/s10346-020-01433-3

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  • DOI: https://doi.org/10.1007/s10346-020-01433-3

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