We investigate the possibility of detecting landslide precursors by means of Synthetic Aperture Radar Differential Interferometry. We show a methodology to retrieve signal associated with key precursors of destabilisation for landslides that present characteristics unfavourable to unwrapping and to time series inversion methods. This methodology entails analysis and description of the interferometric phase signal obtained from raw, wrapped interferograms in combination with the analysis of interferometric coherence drops as marker for key geomorphological features of gravitational origin.

Dini, B., Doin, M., Lacroix, P., Gay, M. (2022). Satellite-based InSAR: application and signal extraction for the detection of landslide precursors. In GRETSI'22: XXVIIIth Francophone Symposium on Signal and Image Processing (pp.1-4).

Satellite-based InSAR: application and signal extraction for the detection of landslide precursors

Dini, B;
2022

Abstract

We investigate the possibility of detecting landslide precursors by means of Synthetic Aperture Radar Differential Interferometry. We show a methodology to retrieve signal associated with key precursors of destabilisation for landslides that present characteristics unfavourable to unwrapping and to time series inversion methods. This methodology entails analysis and description of the interferometric phase signal obtained from raw, wrapped interferograms in combination with the analysis of interferometric coherence drops as marker for key geomorphological features of gravitational origin.
paper
InSAR, landslide precursors
English
GRETSI'22 XXVIIIème Colloque Francophone de Traitement du Signal et des Images 06 – 09 Septembre 2022
2022
GRETSI'22: XXVIIIth Francophone Symposium on Signal and Image Processing
2022
1
4
ID987
https://gretsi.fr/data/colloque/pdf/2022_dini987.pdf
none
Dini, B., Doin, M., Lacroix, P., Gay, M. (2022). Satellite-based InSAR: application and signal extraction for the detection of landslide precursors. In GRETSI'22: XXVIIIth Francophone Symposium on Signal and Image Processing (pp.1-4).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/600683
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