Natural Hazards

, Volume 98, Issue 2, pp 485–505 | Cite as

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

  • Qingkai MengEmail author
  • Qiang Xu
  • Baocun Wang
  • Weile Li
  • Ying Peng
  • Dalei Peng
  • Xing Qi
  • Dongdong Zhou
Original Paper


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.


Loess landslides Time-series analysis Sentinel-1 TOPS Heifangtai 



This research was supported by National Natural Science Foundation of China (41807290), Key R&D and transformation plan of Qinghai Province (2019-SF-130), the Open foundation of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology (SKLGP2017K019), the Open foundation of State Key Laboratory of Hydroscience and Engineering, Tsinghua university (SKLHSE-2017-A-03), The Natural Science Foundation of Qinghai Province (2017-ZJ-926Q), the Open foundation of State Key Lab of Plateau Ecology and Agriculture (2017-ZZ-01). We also thank for ESA support the Sentinel data and anonymous reviewers for their careful work in improving the quality of the paper.


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.State Key Lab of Plateau Ecology and AgricultureQinghai UniversityXiningChina
  2. 2.State Key Laboratory of Geohazard Prevention and Geoenvironment ProtectionChengdu University of TechnologyChengduChina
  3. 3.Institute of Surveying, Mapping and Geoinformation of Henan Provincial Bureau of Geo-exploration and Mineral DevelopmentZhengzhouChina
  4. 4.The College of Nuckear Technology and Automation EngineeringChengdu Univeristy of TechnologyChengduChina
  5. 5.Department of Geo-engineerQinghai UniversityXiningChina

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