Preprints
https://doi.org/10.5194/esurf-2020-106
https://doi.org/10.5194/esurf-2020-106

  29 Dec 2020

29 Dec 2020

Review status: this preprint has been withdrawn by the authors.

Using Google Earth Engine to monitor co-seismic landslide recovery after the 2008 Wenchuan earthquake

Wentao Yang1, Wenwen Qi2, and Jian Fang3 Wentao Yang et al.
  • 1Three-gorges reservoir area (Chongqing) Forest Ecosystem Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing, 100083, China
  • 2National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing, China
  • 3School of Urban and Environmental Sciences, Central China Normal University, Wuhan, China

Abstract. Earthquake-triggered landslides can pose serious threats to mountain communities by remobilizing and providing loose materials for debris flows in post-seismic years. However, how long co-seismic landslides recover remains elusive due to limited observations. Using vegetation dynamics, we studied surface recovery of co-seismic landslides induced by the 2008 Wenchuan earthquake from May 2008 to July 2019 for over 20,000 km2. Landsat derived vegetation recovery on all co-seismic landslides has been assessed based on the Google Earth Engine, a cloud-based computing platform. We found most co-seismic landslides have been recovering after the earthquake but the spatial pattern is heterogeneous. The epicentre region with low elevations along the bottom of the Min River valley has the best landslide recovery, whereas many landslides on the high Longmen Mountain are poorly recovered ten years after the earthquake. These unrecovered hillslopes and gullies together with widespread loose debris indicate that surface processes on high mountains may still active and may provide source materials for debris flows, threatening communities at low elevations. To decipher possible mechanisms, we further analysed the relations between landslide recovery and twelve influencing factors, including slope, pre-seismic vegetation condition, landslide depth, landslide area, elevation, ground peak acceleration of the earthquake, aspect, slope curvatures, topographic positions, mean annual precipitation, ground cohesion strength and vegetation types. We found elevation, topographic position and pre-seismic vegetation condition are the most important factors that influence landslide recovery over all others. This work also demonstrates the efficiency of the Google Earth Engine for continuously monitoring landslide dynamics over large areas.

This preprint has been withdrawn.

Wentao Yang et al.

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Wentao Yang et al.

Wentao Yang et al.

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This preprint has been withdrawn.

Short summary
Major mountain earthquakes often trigger numerous co-seismic landslides. Vegetation dynamics on landslides can be used to indicate post-seismic landslide activity. We used thousands of remote sensing images and possible influencing factors to uncover the spatial pattern and drivers of vegetation recovery on landslides after the great 2008 Sichuan earthquake. Detailed pattern for the entire region is revealed and three paramount influencing factors were determined.