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Early Identification of the Jiangdingya Landslide of Zhouqu Based on SBAS-InSAR Technology
作者姓名:YU Haihu  CAI Guolin  GAN Quan  SHEN Dong
作者单位:Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China;Sichuan Bureau of Surveying, Mapping and Geoinformation, Chengdu 610000, China
基金项目:This project is sponsored by the Research on Early Identification of Landslide Hazards based on High-resolution SAR Image (KJ-2018-13).
摘    要:SBAS-InSAR technology is characterized by the advantages of reducing the influence of terrain-simulation error, time-space decorrelation, atmospheric error, thereby improving the reliability of surface-deformation monitoring. This paper studies the early landslide identification method based on SBAS-InSAR technology. Selecting the Jiangdingya landslide area in Zhouqu County, Gansu Province as the research area, 84 ascending-orbit Sentinel-1A SAR images from 2015 to 2019 are collected. In addition, using SBAS-InSAR technology, the rate and time-series results of surface deformation of the landslide area in Jiangdingya during this period are extracted, and potential landslides are identified. The results show that the early landslide identification method based on SBAS-InSAR technology is highly feasible and is a better tool for identifying potential landslides in large areas.

关 键 词:SBAS-InSAR  Jiangdingya  landslide  Early  identification  Deformation  rate  Sentinel-1A
收稿时间:2020/5/7 0:00:00
修稿时间:2020/9/27 0:00:00

Early Identification of the Jiangdingya Landslide of Zhouqu Based on SBAS-InSAR Technology
YU Haihu,CAI Guolin,GAN Quan,SHEN Dong.Early Identification of the Jiangdingya Landslide of Zhouqu Based on SBAS-InSAR Technology[J].Earthquake Research in China,2020,34(4):510-522.
Authors:YU Haihu  CAI Guolin  GAN Quan  SHEN Dong
Institution:Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China;Sichuan Bureau of Surveying, Mapping and Geoinformation, Chengdu 610000, China
Abstract:SBAS-InSAR technology is characterized by the advantages of reducing the influence of terrain-simulation error, time-space decorrelation, atmospheric error, thereby improving the reliability of surface-deformation monitoring. This paper studies the early landslide identification method based on SBAS-InSAR technology. Selecting the Jiangdingya landslide area in Zhouqu County, Gansu Province as the research area, 84 ascending-orbit Sentinel-1A SAR images from 2015 to 2019 are collected. In addition, using SBAS-InSAR technology, the rate and time-series results of surface deformation of the landslide area in Jiangdingya during this period are extracted, and potential landslides are identified. The results show that the early landslide identification method based on SBAS-InSAR technology is highly feasible and is a better tool for identifying potential landslides in large areas.
Keywords:SBAS-InSAR  Jiangdingya landslide  Early identification  Deformation rate  Sentinel-1A
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