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Using Sentinel-2 time series to detect slope movement before the Jinsha River landslide

A Correction to this article was published on 22 May 2019

This article has been updated


Detecting slope movement before landslides occur in mountain regions is crucial for disaster reduction. In October 2018, a gigantic landslide occurred on the Jinsha River, causing dammed-lake breach flood 500 km downstream. In this work, we used 25 Sentinel-2 images from November 2015 to August 2018 to explore the capability of this high temporal resolution optical images in detecting slope movement before the Jinsha River landslide. Normalized difference vegetation index (NDVI) was calculated to composite temporal profiles using all Sentinel-2 images. With this NDVI time series, unsupervised K-means classifier was applied to initially classify the study area and find the best thresholds for automatically extracting landslide scars in the image series. These extracted landslide scars were validated using interpreted results from two high spatial resolution images of similar dates in 2015 (user’s accuracy 89.7%, producer’s accuracy 83.6%) and 2018 (user’s accuracy 90.8%, producer’s accuracy 74.9%). After validation, extracted landslide scars of different years were counted and displayed in an RGB composite image to highlight slope movement. In addition, monotonous decrease/increase of NDVI was also observed, indicating continuous expansion of landslide scarps and movement of landslide head along the slope on the landslide surface. This work demonstrated the capability of Sentinel-2 time series images to capture slope movement with short revisit time at low cost. By incorporating other environmental information (such as elevation), this proposed method has the potential to consistently map pre-landslide slope movements over a large region.

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  • 22 May 2019

    The published version of this article, unfortunately, contained error.


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This work was supported by the National Science Foundation of China (NO. 41807500) and the National Key Research and Development Program of China (NO. 2017YFC1503000). We show gratitude to following MSc students: Jianghua Liao, Zhen Zhang, Yuhong Ma, and Lijuan Wang for their help in collecting some of the basic information for the Jinsha River landslide at the initial stage of this work. We also express our thanks to Prof. Qiang Xu and Dr. Weile Li from the Stake Key Laboratory of Geo-hazards for generously sharing Ziyuan-3 and Gaofen-2 high spatial resolution images in 2015 and 2018. Contributions by editor and reviewers of this work are also deeply appreciated.

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Correspondence to Wentao Yang or Yunqi Wang.

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Yang, W., Wang, Y., Sun, S. et al. Using Sentinel-2 time series to detect slope movement before the Jinsha River landslide. Landslides 16, 1313–1324 (2019).

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  • Pre-landslide
  • Slope movement detection
  • Sentinel-2
  • Optical remote sensing