Articles | Volume 21, issue 2
https://doi.org/10.5194/nhess-21-629-2021
https://doi.org/10.5194/nhess-21-629-2021
Research article
 | 
15 Feb 2021
Research article |  | 15 Feb 2021

Leveraging time series analysis of radar coherence and normalized difference vegetation index ratios to characterize pre-failure activity of the Mud Creek landslide, California

Mylène Jacquemart and Kristy Tiampo

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Cited articles

Agram, P. S., Jolivet, R., Riel, B., Lin, Y. N., Simons, M., Hetland, E., Doin, M.-P., and Lasserre, C.: New Radar Interferometric Time Series Analysis Toolbox Released, Eos Trans. Am. Geophys. Union, 94, 69–70, https://doi.org/10.1002/2013EO070001, 2013. a
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Berardino, P., Fornaro, G., Lanari, R., and Sansosti, E.: A New Algorithm for Surface Deformation Monitoring Based on Small Baseline Differential SAR Interferograms, IEEE T. Geosci. Remote, 40, 2375–2383, https://doi.org/10.1109/TGRS.2002.803792, 2002. a
Burrows, K., Walters, R. J., Milledge, D., Spaans, K., and Densmore, A. L.: A New Method for Large-Scale Landslide Classification from Satellite Radar, Remote Sens., 11, 237, https://doi.org/10.3390/rs11030237, 2019. a, b
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Short summary
We used interferometric radar coherence – a data quality indicator typically used to assess the reliability of radar interferometry data – to document the destabilization of the Mud Creek landslide in California, 5 months prior to its catastrophic failure. We calculated a time series of coherence on the slide relative to the surrounding hillslope and suggest that this easy-to-compute metric might be useful for assessing the stability of a hillslope.
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