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Time-series analysis of the evolution of large-scale loess landslides using InSAR and UAV photogrammetry techniques: a case study in Hongheyan, Gansu Province, Northwest China

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Abstract

Loess landslides are a severe engineering geological problem on the Loess Plateau of China. This study relies on interferometric synthetic aperture radar (InSAR) and unmanned aerial vehicle (UAV) photogrammetry techniques to characterise a large-scale loess landslide deformation process in Northwest China. First, a total of 85 Sentinel-1 SAR images acquired from March 2015 to March 2019 were used to detect the spatial displacement and characterise the pattern of deformation from presliding to postsliding. Second, three UAV flight surveys were conducted to reconstruct landslide morphology, identify scarps, cracks and fissures; and generate elevation differences. By comparing these two technologies, we found that InSAR has more advantages in the retrieval of creeping deformation, while UAV data is valuable for detecting large sudden slides. Dynamic deformation zonation maps were generated based on comprehensive analysis, and the deformation pattern of the large loess landslide was deduced. The Hongheyan landslide was induced by heavy rainfall and then gradually became suspended owing to the topography effect. Recently, the western part of the slope showed a clear accelerating trend. This evolution provides comprehensive kinematic information for local governments to make further intensive observations or take effective precautions.

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Abbreviations

CHK:

Checked points

DGNSS:

Differential Global Navigation Satellite System

DSMs:

Digital surface models

DS:

Distributed scatters

ESA:

European Space Agency

EDA:

Extreme deformation area

FIP:

First investigation period

GPS:

Global Positioning System

GCPs:

Ground control points

GF-2:

Gaofen-2

HCP:

High coherence points

HP:

Homogeneous pixels

InSAR:

Interferometric synthetic aperture radar

LOS:

Line of sight

LDA:

Low deformation area

MVS:

Multi-view stereo

MCF:

Minimum cost flow

MT-InSAR:

Multi-temporal InSAR

POD:

Precise orbit ephemerides

PS:

Persistent scatter

PSC:

Persistent scatter candidate

RMSE:

Root mean squared error

SRTM:

Shuttle Radar Topography Mission

SFM:

Structure from Motion

SIP:

Second investigation period

SDA:

Strong deformation area

SA:

Stable area

TOPS:

Terrain observation with progressive scans

TIP:

Third investigation period

UAV:

Unmanned aerial vehicle

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Acknowledgements

We thank for the contribution of Qiongpei Cairen, Xianjie, Yin, Weiming Jiang, Yuanshuai Shi, Fan Yang, Cong Dai and Qinggang Li for supporting in field investigation, Doctor Fanyu Zhang of Lanzhou University for providing local topography and geology map and anonymous reviewers for their careful work in improving the quality of the paper.

Funding

This research was supported by National Natural Science Foundation of China (41807290), the Open foundation of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology (SKLGP2017K019), the Natural Science Foundation of Qinghai Province (2017-ZJ-926Q), the Key Research Project of Qinghai Province (2019-0101-ZJC-0001, 2019-ZJ-A10) and the China Scholarship Council (CSC201808635039).

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Authors and Affiliations

  1. State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, 810016, China

    Qingkai Meng

  2. State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China

    Qingkai Meng, Weile Li, Qiang Xu & Yuanzhen Ju

  3. Earth Sciences Department, University of Florence, 50121, Florence, Italy

    Qingkai Meng, Federico Raspini & Nicola Casagli

  4. School of Water Resources and Electric Power, Qinghai University, Xining, 810016, China

    Qingkai Meng

  5. College of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu, 610059, China

    Ying Peng

  6. Beijing Institute of Surveying and Mapping, Beijing, 100038, China

    Yueze Zheng

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  1. Qingkai Meng
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  2. Weile Li
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  3. Federico Raspini
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Correspondence to Weile Li.

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Meng, Q., Li, W., Raspini, F. et al. Time-series analysis of the evolution of large-scale loess landslides using InSAR and UAV photogrammetry techniques: a case study in Hongheyan, Gansu Province, Northwest China. Landslides 18, 251–265 (2021). https://doi.org/10.1007/s10346-020-01490-8

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