TY - JOUR

T1 - The 21 July 2020 Shaziba landslide in China

T2 - Results from multi-source satellite remote sensing

AU - Wang, Wandi

AU - Motagh, Mahdi

AU - Mirzaee, Sara

AU - Li, Tao

AU - Zhou, Chao

AU - Tang, Hui

AU - Roessner, Sigrid

N1 - Funding Information: The authors acknowledge the anonymous reviewers and the Editor for their constructive suggestions and comments. The TerraSAR-X and TanDEM-X DEM data are copyright German Aerospace Center (DLR) (proposals: motagh_GEO1916 & motagh_XTI_LAND6959). The Sentinel-1/2 datasets were freely provided by the European Space Agency (ESA) through the Sentinels Scientific Data Hub. The authors also acknowledge Dr. Changhu Xue and Dr. Zhuge Xia for constructive discussions. W.W. is supported by China Scholarship Council (CSC) Grant #202006450011. This work was partially sponsored by the National Natural Science Foundation of China (Grant No. 42074031 and No. 41907253), the Key Research and Development Program of Hubei Province (Grant No. 2021BCA219), and Helmholtz within the framework of HIP project MultiSaT4SLOWS.

PY - 2023/9/1

Y1 - 2023/9/1

N2 - A catastrophic landslide occurred on 21 July 2020, 30 km from Enshi city, in Mazhe County of Hubei province, China. In this paper, we aimed to investigate the kinematic evolution and volumetric change related to this landslide using multi-source remote sensing measurements from synthetic aperture radar (SAR) and optical data. C-band Sentinel-1 and X-band TerraSAR-X SAR data are analyzed using several multi-temporal interferometry (MTI) time-series techniques including Persistent Scatterer Interferometry (PSI), Small Baseline subset (SBAS), and Combined eigenvalue maximum likelihood Phase Linking (CPL). The spatial pattern of surface deformation resulting from the interferometric analysis is then statistically analyzed to retrieve the pre-failure and post-failure displacements. Co-failure motions are analyzed using an image correlation technique applied to both the Planetscope and Sentinel-2 images. Moreover, 4 pairs of bistatic TerraSAR-X/TanDEM-X (TDX) data are utilized to generate high-precision digital elevation models (DEMs) and estimate the volumetric change related to the main slope failure. The pre-failure ground deformation analysis results suggest that the landslide was already active before the July 2020 failure, with the seasonality and hydraulic diffusivity being characteristics of a slow-moving landslide. Among the three different MTI methods applied, the CPL method results in a greater measurement points (MPs) density than the PSI and SBAS method when estimating the pre-failure movement of the Shaziba landslide. The July 2020 Shaziba disaster is divided into three main parts: (1) slightly horizontal deformation of 0.5–1.5 m within the northern part with ground and house cracks, (2) less collapse in the eastern part with horizontal motions reaching 30 m and (3) a highly eroded western part where vegetation was wholly lost in the main event, resulting in an collapse volume of approximately 4.98 million m3, out of which approximately around 3.4 million m3 was deposited and approximately 1.58 million m3 was washed away into the Qing River. After the failure, the marginal scrap of the main failure body, above crown of landslide and eastern part showed instability with rates of 20–30 mm/yr, suggesting that the failure zone may continue to expand.

AB - A catastrophic landslide occurred on 21 July 2020, 30 km from Enshi city, in Mazhe County of Hubei province, China. In this paper, we aimed to investigate the kinematic evolution and volumetric change related to this landslide using multi-source remote sensing measurements from synthetic aperture radar (SAR) and optical data. C-band Sentinel-1 and X-band TerraSAR-X SAR data are analyzed using several multi-temporal interferometry (MTI) time-series techniques including Persistent Scatterer Interferometry (PSI), Small Baseline subset (SBAS), and Combined eigenvalue maximum likelihood Phase Linking (CPL). The spatial pattern of surface deformation resulting from the interferometric analysis is then statistically analyzed to retrieve the pre-failure and post-failure displacements. Co-failure motions are analyzed using an image correlation technique applied to both the Planetscope and Sentinel-2 images. Moreover, 4 pairs of bistatic TerraSAR-X/TanDEM-X (TDX) data are utilized to generate high-precision digital elevation models (DEMs) and estimate the volumetric change related to the main slope failure. The pre-failure ground deformation analysis results suggest that the landslide was already active before the July 2020 failure, with the seasonality and hydraulic diffusivity being characteristics of a slow-moving landslide. Among the three different MTI methods applied, the CPL method results in a greater measurement points (MPs) density than the PSI and SBAS method when estimating the pre-failure movement of the Shaziba landslide. The July 2020 Shaziba disaster is divided into three main parts: (1) slightly horizontal deformation of 0.5–1.5 m within the northern part with ground and house cracks, (2) less collapse in the eastern part with horizontal motions reaching 30 m and (3) a highly eroded western part where vegetation was wholly lost in the main event, resulting in an collapse volume of approximately 4.98 million m3, out of which approximately around 3.4 million m3 was deposited and approximately 1.58 million m3 was washed away into the Qing River. After the failure, the marginal scrap of the main failure body, above crown of landslide and eastern part showed instability with rates of 20–30 mm/yr, suggesting that the failure zone may continue to expand.

KW - Hazard assessment

KW - InSAR

KW - Planet

KW - Sentinel-1

KW - Sentinel-2

KW - Shaziba landslide

KW - TanDEM-X

KW - TerraSAR-X

UR - http://www.scopus.com/inward/record.url?scp=85163725842&partnerID=8YFLogxK

U2 - 10.1016/j.rse.2023.113669

DO - 10.1016/j.rse.2023.113669

M3 - Article

AN - SCOPUS:85163725842

VL - 295

JO - Remote sensing of environment

JF - Remote sensing of environment

SN - 0034-4257

M1 - 113669

ER -