4.6 Article

Monitoring the regional deformation of loess landslides on the Heifangtai terrace using the Sentinel-1 time series interferometry technique

Journal

NATURAL HAZARDS
Volume 98, Issue 2, Pages 485-505

Publisher

SPRINGER
DOI: 10.1007/s11069-019-03703-3

Keywords

Loess landslides; Time-series analysis; Sentinel-1 TOPS; Heifangtai

Funding

  1. National Natural Science Foundation of China [41807290]
  2. Key R&D and transformation plan of Qinghai Province [2019-SF-130]
  3. Open foundation of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology [SKLGP2017K019]
  4. Open foundation of State Key Laboratory of Hydroscience and Engineering, Tsinghua university [SKLHSE-2017-A-03]
  5. Natural Science Foundation of Qinghai Province [2017-ZJ-926Q]
  6. Open foundation of State Key Lab of Plateau Ecology and Agriculture [2017-ZZ-01]

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The Heifangtai terrace of Gansu Province is a hotspot for loess landslide research, as massive and continuous landslides occur here every year. Detecting the spatial and temporal deformations of landslides and acquiring precursor information are very important for hazard prediction and risk management. In this paper, 51 newly launched Sentinel-1a scenes using the novel terrain observation with progressive scans (TOPS) mode from March 2015 to November 2017 are gathered, and a preprocessed chain of TOPS with the small baseline subset interferometric synthetic aperture radar technology is generated to obtain the deformation time-series. Our results show that (1) 44 active landslides with mean deformation velocities ranging from - 12.3 to - 58.57 mm yr(-1) along the steepest slope, were detected and consisted of 18 loess-bedrock landslides, 12 loess flows, 7 loess flow-slides, and 7 loess slides; (2) four typical active regions and two potential risk places were recognized on the basis of high coherent point distribution, the average measured velocities along the steep slope and high-resolution orthographic images; (3) geological structures and special geomorphologies (e.g., cracks, sinkholes and concave gullies) can be mainly attributed to induce reactivity via long term irrigation. Finally, our research also demonstrates the potential ability of Sentinel-1 TOPS images to be applied to the monitoring of loess landslides, which is essential for risk mitigation and emergence management.

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