InSAR Displacement with High-Resolution Optical Remote Sensing for the Early Detection and Deformation Analysis of Active Landslides in the Upper Yellow River

被引:3
|
作者
Tu, Kuan [1 ]
Ye, Shirong [1 ]
Zou, Jingui [2 ]
Hua, Chen [3 ]
Guo, Jiming [2 ]
机构
[1] Wuhan Univ, GNSS Res Ctr, Wuhan 430079, Peoples R China
[2] Wuhan Univ, Sch Geodesy & Geomatics, Wuhan 430079, Peoples R China
[3] Inst Disaster Prevent, Sch Emergency Management, Sanhe, Peoples R China
关键词
landslide detection; InSAR; optical remote sensing; Upper Yellow River (China); PERMANENT SCATTERERS; SURFACE DEFORMATION; HYDROPOWER STATION; SAR; RESERVOIR;
D O I
10.3390/w15040769
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Frequent landslides and other geological disasters pose a serious threat to human life and infrastructure in the Upper Yellow River. Detecting active landslides and ascertaining their impact necessitate the determination of deformation characteristics. In this study, we developed an integrated method combining interferometric synthetic aperture radar and high-resolution optical satellite remote sensing to detect active landslides in the Upper Yellow River region from Longyang Gorge to Lijia Gorge. Sentinel-1 satellite data from January 2019 to April 2021 with ascending and descending orbits were adopted to obtain deformation using the STACKING and interferometric point target analysis techniques. A 97.08% overlap rate in the detected results from the two InSAR technologies confirmed the suitability of both approaches. The missing detection rates (6.79% & 8.73%) from single line-of-sight (LOS) InSAR results indicate the necessity of different orbit direction data. Slight deformation rate changes (<4 mm/month) before and after rainy seasons of the Lijia Gorge landslide group indicate that precipitation exerted little impact on slope activity. This study supports the feasibility of integrated methods for the detection and analysis of active landslides in the Upper Yellow River and other regions.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Early Detection of Landslides in the Upstream and Downstream Areas of the Baige Landslide, the Jinsha River Based on Optical Remote Sensing and InSAR Technologies
    Lu H.
    Li W.
    Xu Q.
    Dong X.
    Dai C.
    Wang D.
    [J]. Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 2019, 44 (09): : 1342 - 1354
  • [2] HELIPORT DETECTION IN HIGH-RESOLUTION OPTICAL REMOTE SENSING IMAGES
    Baseski, Emre
    [J]. 2018 9TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS), 2018,
  • [3] Early Identifying and Monitoring Landslides in Guizhou Province with InSAR and Optical Remote Sensing
    Li, Genger
    Hu, Bo
    Li, Hui
    Lu, Feng
    [J]. JOURNAL OF SENSORS, 2021, 2021
  • [4] Analysis of the Spatial Distribution and Deformation Types of Active Landslides in the Upper Jinsha River, China, Using Integrated Remote Sensing Technologies
    Zhou, Shengsen
    Chen, Baolin
    Lu, Huiyan
    Shan, Yunfeng
    Li, Zhigang
    Li, Pengfei
    Cao, Xiong
    Li, Weile
    [J]. REMOTE SENSING, 2024, 16 (01)
  • [5] Object Detection with Proposals in High-Resolution Optical Remote Sensing Images
    Ding, Huoping
    Luo, Qinhan
    Zou, Zhengxia
    Guo, Cuicui
    Shi, Zhenwei
    [J]. INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2017, 2017, 10585 : 242 - 250
  • [6] High-resolution optical imaging for analysis of displacement and deformation fields in cell biology
    Helmke, BP
    [J]. CONFERENCE RECORD OF THE THIRTY-FIFTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, VOLS 1 AND 2, 2001, : 1687 - 1691
  • [7] UAV: low-cost remote sensing for high-resolution investigation of landslides
    Giordan, Daniele
    Manconi, Andrea
    Tannant, Dwayne D.
    Allasia, Paolo
    [J]. 2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2015, : 5344 - 5347
  • [8] High-Resolution Remote Sensing Image Analysis for Early Detection and Response Planning for Emerald Ash Borer
    Souci, Jason San
    Hanou, Ian
    Puchalski, Daniel
    [J]. PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2009, 75 (08): : 905 - 909
  • [9] Automatic Extraction of Potential Landslides by Integrating an Optical Remote Sensing Image with an InSAR-Derived Deformation Map
    Xun, Zhangyuan
    Zhao, Chaoying
    Kang, Ya
    Liu, Xiaojie
    Liu, Yuanyuan
    Du, Chengyan
    [J]. REMOTE SENSING, 2022, 14 (11)
  • [10] Research on Building Target Detection Based on High-Resolution Optical Remote Sensing Imagery
    Mei, Yong
    Chen, Hao
    Yang, Shuting
    [J]. ALGORITHMS, 2021, 14 (10)