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Landslide geometry and activity in Villa de la Independencia (Bolivia) revealed by InSAR and seismic noise measurements

Lookup NU author(s): Chuang Song, Chen Yu, Professor Zhenhong Li, Professor Stefano Utili

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Interferometric Synthetic Aperture Radar (InSAR) enables detailed investigation of surface landslide movements, but it cannot provide information about subsurface structures. In this work, InSAR measurements were integrated with seismic noise in situ measurements to analyse both the surface and subsurface characteristics of a complex slow-moving landslide exhibiting multiple failure surfaces. The landslide body involves a town of around 6000 inhabitants, Villa de la Independencia (Bolivia), where extensive damages to buildings have been observed. To investigate the spatial-temporal characteristics of the landslide motion, Sentinel-1 displacement time series from October 2014 to December 2019 were produced. A new geometric inversion method is proposed to determine the best-fit sliding direction and inclination of the landslide. Our results indicate that the landslide is featured by a compound movement where three different blocks slide. This is further evidenced by seismic noise measurements which identified that the different dynamic characteristics of the three sub-blocks were possibly due to the different properties of shallow and deep slip surfaces. Determination of the slip surface depths allows for estimating the overall landslide volume (9.18 ยท 107 m3). Furthermore, Sentinel-1 time series show that the landslide movements manifest substantial accelerations in early 2018 and 2019, coinciding with increased precipitations in the late rainy season which are identified as the most likely triggers of the observed accelerations. This study showcases the potential of integrating InSAR and seismic noise techniques to understand the landslide mechanism from ground to subsurface.


Publication metadata

Author(s): Song C, Chen Y, Li Z, Pazzi V, DelSoldato M, Cruz A, Utili S

Publication type: Article

Publication status: Published

Journal: Landslides

Year: 2021

Pages: ePub ahead of Print

Online publication date: 23/04/2021

Acceptance date: 10/03/2021

Date deposited: 25/05/2021

ISSN (print): 1612-510X

ISSN (electronic): 1612-5118

URL: https://doi.org/10.1007/s10346-021-01659-9

DOI: 10.1007/s10346-021-01659-9


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