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Measuring precursory movements of the recent Xinmo landslide in Mao County, China with Sentinel-1 and ALOS-2 PALSAR-2 datasets

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Abstract

The Xinmo landslide occurred in the early morning of 24 June 2017 at about 5:38 am local time. This catastrophic event caused enormous casualties and huge economic losses in Xinmo Village, Mao County, Sichuan Province, China. In this study, Synthetic Aperture Radar (SAR) datasets acquired by X-band TerraSAR-X, Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) aboard the Advanced Land Observing Satellite-2 (ALOS-2), and C-band Sentinel-1 over the disaster area were collected and analyzed to characterize this landslide. The high-resolution TerraSAR-X intensity images were used to evaluate the landslide disaster and delineate the sliding area. Afterwards, two ALOS-2 PALSAR-2 image pairs and a stack of 45 Sentinel-1 images were processed to detect precursory movements of the landslide surface, using the conventional differential InSAR (DInSAR) method and advanced time series InSAR analysis. The unstable source area near the ridge was identified from the displacement rate map derived from Sentinel-1 datasets. The maximum displacement rate detected at the source area was −35mm/year along the radar line of sight (LOS) direction. The time series of LOS displacements over 2 years presents an easily discerned seasonal evolution pattern. In particular, a sudden acceleration of the displacement, dozens of days before the collapse was clearly captured by the Sentinel-1 observations, which might suggest that early warning of landslide disasters is possible given the availability of operational SAR data acquired in frequent repeat-pass mode, such as the Sentinel-1 twin-satellite constellation.

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Acknowledgements

Helpful suggestions and comments given by Dr. Teng Wang with Earth Observatory of Singapore, Dr. Xuguo Shi with China University of Geoscience (Wuhan), and Prof. Qiang Xu with Chengdu University of Technology are appreciated. The ALOS-2 PALSAR-2 datasets are provided by Japan Aerospace Exploration Agency (JAXA) through the ALOS-RA project (PI1247, PI1440, and PI3248). The Sentinel-1 datasets are provided by the European Space Agency (ESA) under the Dragon 4 project (id 32278). The TerraSAR-X datasets are provided by German Aerospace Center (DLR) and EADS Astrium. We thank Stephen C. McClure for providing assistance in language editing.

Funding

This work was financially supported by the National Key R&D Program of China (Grant No. 2017YFB0502700), the National Key Basic Research Program of China (Grant Nos. 2013CB733205 and 2013CB733204), and the National Natural Science Foundation of China (Grant Nos. 61331016, 41774006 and 41571435).

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Authors and Affiliations

  1. State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, 430079, People’s Republic of China

    Jie Dong, Lu Zhang, Menghua Li, Yanghai Yu, Mingsheng Liao, Jianya Gong & Heng Luo

  2. Collaborative Innovation Center for Geospatial Technology, Wuhan, 430079, People’s Republic of China

    Lu Zhang, Mingsheng Liao & Jianya Gong

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  1. Jie Dong
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  2. Lu Zhang
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  3. Menghua Li
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  7. Heng Luo
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Correspondence to Lu Zhang.

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Dong, J., Zhang, L., Li, M. et al. Measuring precursory movements of the recent Xinmo landslide in Mao County, China with Sentinel-1 and ALOS-2 PALSAR-2 datasets. Landslides 15, 135–144 (2018). https://doi.org/10.1007/s10346-017-0914-8

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