Monitoring activity at the Daguangbao mega-landslide (China) using Sentinel-1 TOPS time series interferometry

被引:142
|
作者
Dai, Keren [1 ,2 ]
Li, Zhenhong [2 ]
Tomas, Roberto [2 ,3 ]
Liu, Guoxiang [1 ]
Yu, Bing [4 ]
Wang, Xiaowen [1 ]
Cheng, Haiqin [5 ]
Chen, Jiajun [2 ]
Stockamp, Julia [2 ,6 ]
机构
[1] Southwest Jiaotong Univ, Dept Remote Sensing & Geospatial Informat Engn, Chengdu 610031, Peoples R China
[2] Newcastle Univ, COMET, Sch Civil Engn & Geosci, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England
[3] Univ Alicante, Escuela Politecn Super, Dept Ingn Civil, POB 99, E-03080 Alicante, Spain
[4] Southwest Petr Univ, Sch Civil Engn & Architecture, Chengdu 610500, Peoples R China
[5] East China Jiaotong Univ, Sch Civil Engn & Architecture, Nanchang 330013, Jiangxi, Peoples R China
[6] Univ Glasgow, Sch Geog & Earth Sci, Glasgow G12 8QQ, Lanark, Scotland
基金
中国国家自然科学基金;
关键词
InSAR; Sentinel-1; TOPS; Daguangbao landslide; Tandem-X; Wenchuan earthquake; PERMANENT SCATTERERS; WENCHUAN EARTHQUAKE; SAR INTERFEROMETRY; GROUND SUBSIDENCE; SOURCE PARAMETERS; X DATA; INSAR; DEFORMATION; DINSAR;
D O I
10.1016/j.rse.2016.09.009
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Daguangbao mega-landslide (China), induced by the 2008 Wenchuan earthquake (M-w = 7.9), with an area of approximately 8 km(2), is one of the largest landslides in the world. Experts predicted that the potential risk and instability of the landslide might remain for many decades, or even longer. Monitoring the activity of such a large landslide is hence critical. Terrain Observation by Progressive Scans (TOPS) mode from the Sentinel-1 satellite provides us with up-to-date high-quality Synthetic Aperture Radar (SAR) images over a wide ground coverage (250 x 250 km), enabling full exploitation of various InSAR applications. However, the TOPS mode introduces azimuth -dependent Doppler variations to radar signals, which requires an additional processing step especially for SAR interferometry. Sentinel-1 TOPS data have been widely applied to earthquakes, but the performance of TOPS data-based time series analysis requires further exploitation. In this study, Sentinel-1 TOPS data were employed to investigate landslide post-seismic activities for the first time. To deal with the azimuth-dependent Doppler variations, a processing chain of TOPS time series interferometry approach was developed. Since the Daguangbao landslide is as a result of the collapse of a whole mountain caused by the 2008 Mw 7.9 Wenchuan earthquake, the existing Digital Elevation Models (DEMs, e.g. SRTM and ASTER) exhibit height differences of up to approximately 500 m. Tandem-X images acquired after the earthquake were used to generate a high resolution post-seismic DEM. The high gradient topographic errors of the SRTM DEM (i.e. the differences between the pre-seismic SRTM and the actual post-seismic elevation), together with low coherence in mountainous areas make it difficult to derive a precise DEM using the traditional InSAR processing procedure. A re-flattening iterative method was hence developed to generate a precise TanDEM-X DEM in this study. The volume of the coseismic Daguangbao landslide was estimated to be of 1.189 +/- 0.110 x 109 m(3) by comparing the postseismic Tandem-X DEM with the preseismic SRTM DEM, which is consistent with the engineering geological survey result. The time-series results from Sentinel-1 show that some sectors of the Daguangbao landslide are still active (and displaying four sliding zones) and exhibiting a maximum displacement rate of 8 cm/year, even eight years after the Wenchuan earthquake. The good performance of TOPS in this time series analysis indicates that up-to-date high-quality TOPS data with spatiotemporal baselines offer significant potential in terms of future InSAR applications. (C) 2016 The Authors. Published by Elsevier Inc.
引用
收藏
页码:501 / 513
页数:13
相关论文
共 50 条
  • [1] PAKISTAN EARTHQUAKE STUDY USING SENTINEL-1 TOPS INTERFEROMETRY
    Ali, M.
    Afzal, Z.
    Budillon, A.
    Ferraioli, G.
    Hussain, S.
    Schirinzi, G.
    [J]. IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 2181 - 2184
  • [2] SENTINEL-1 TOPS INTERFEROMETRIC TIME SERIES RESULTS AND VALIDATION
    Prats-Iraola, Pau
    Nannini, Matteo
    Yague-Martinez, Nestor
    Scheiber, Rolf
    Minati, Federico
    Vecchioli, Francesco
    Costantini, Mario
    Borgstrom, Sven
    De Martino, Prospero
    Siniscalchi, Valeria
    Walter, Thomas
    Nikkhoo, Mehdi
    Foumelis, Michael
    Desnos, Yves-Louis
    [J]. 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 3894 - 3897
  • [3] Monitoring and analysis of Woda landslide (China) using InSAR and Sentinel-1 data
    Li, Bingquan
    Jiang, Wenliang
    Li, Yongsheng
    Luo, Yi
    Jiao, Qisong
    Zhang, Qingyun
    [J]. ADVANCES IN SPACE RESEARCH, 2023, 72 (05) : 1789 - 1802
  • [4] A Modification to Time-Series Coregistration for Sentinel-1 TOPS Data
    Tian, Xin
    Ma, Zhang-Feng
    Jiang, Mi
    [J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2020, 13 : 1639 - 1648
  • [5] Monitoring the regional deformation of loess landslides on the Heifangtai terrace using the Sentinel-1 time series interferometry technique
    Qingkai Meng
    Qiang Xu
    Baocun Wang
    Weile Li
    Ying Peng
    Dalei Peng
    Xing Qi
    Dongdong Zhou
    [J]. Natural Hazards, 2019, 98 : 485 - 505
  • [6] Monitoring the regional deformation of loess landslides on the Heifangtai terrace using the Sentinel-1 time series interferometry technique
    Meng, Qingkai
    Xu, Qiang
    Wang, Baocun
    Li, Weile
    Peng, Ying
    Peng, Dalei
    Qi, Xing
    Zhou, Dongdong
    [J]. NATURAL HAZARDS, 2019, 98 (02) : 485 - 505
  • [7] Classification of ground deformation using sentinel-1 persistent scatterer interferometry time series
    Mirmazloumi, S. Mohammad
    Wassie, Yismaw
    Navarro, Jose Antonio
    Palama, Riccardo
    Krishnakumar, Vrinda
    Barra, Anna
    Cuevas-Gonzalez, Maria
    Crosetto, Michele
    Monserrat, Oriol
    [J]. GISCIENCE & REMOTE SENSING, 2022, 59 (01) : 374 - 392
  • [8] Time-series co-registration for Sentinel-1 TOPS SAR Data
    Ma Z.
    Jiang M.
    Ding Q.
    [J]. Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 2021, 50 (05): : 634 - 640
  • [9] Monitoring Harvesting by Time Series of Sentinel-1 SAR Data
    Kavats, Olena
    Khramov, Dmitriy
    Sergieieva, Kateryna
    Vasyliev, Volodymyr
    [J]. REMOTE SENSING, 2019, 11 (21)
  • [10] Monitoring Irrigation Events and Crop Dynamics Using Sentinel-1 and Sentinel-2 Time Series
    Ma, Chunfeng
    Johansen, Kasper
    McCabe, Matthew F.
    [J]. REMOTE SENSING, 2022, 14 (05)