MOUNTAINOUS LANDSLIDE RECOGNITION BASED ON GAOFEN-3 POLARIMETRIC SAR IMAGERY

被引:0
|
作者
Ding, Yi [1 ]
Liu, Ming [1 ]
Li, Suju [1 ]
Jia, Dan [1 ]
Zhou, Lei [3 ]
Wu, Bin [3 ]
Wang, Yani [2 ]
机构
[1] Natl Disaster Reduct Ctr China, Beijing, Peoples R China
[2] Beijing Univ Civil Engn & Architecture, Beijing, Peoples R China
[3] Dongfanghong Satellite Co Ltd, Beijing, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
PolSAR; Mountainous Landslide; Recognition;
D O I
10.1109/igarss.2019.8900478
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Full-polarimetric SAR image is very useful for the landslide monitoring especially in the well vegetation-covered mountainous region. GaoFen-3 (GF-3) is the first civil C-band fully polarimetric SAR satellite in China. In order to test the ability of GF-3 full-polarimetric SAR data on landslide monitoring, 2 cases of mountainous landslide in southwestern part of China in 2017 and 4 polarimetric decomposition methods (Pauli, Krogager, Freeman, and H-alpha/A) were selected. It was found that GF-3 full-polarimetric SAR data had a good performance on that. The scattering mode had changed from volume to surface mode by the four methods which indicated the vegetation covered has been destroyed by landslide. In the incoherent decomposition methods, the scattering mode in the vegetation region around the landslides had a more consistent result than that in the incoherent decomposition methods. It can also be a good tool to do the autonomous landslide recognition in a larger region combined with some change detection methods.
引用
收藏
页码:9634 / 9637
页数:4
相关论文
共 50 条
  • [21] Retrieval of Significant Wave Height Under Typhoon Conditions from Gaofen-3 SAR Imagery
    Wang Xiaochen
    Han Bing
    Zhong Lihua
    Yuan Xinzhe
    [J]. JOURNAL OF OCEAN UNIVERSITY OF CHINA, 2022, 21 (01) : 81 - 90
  • [22] PRELIMINARY COHERENCE ASSESSMENT OF GAOFEN-3 SAR DATA
    Li, Tao
    Tang, Xinming
    Chen, Qianfu
    Gao, Xiaoming
    Zhang, Xiang
    Guo, Li
    [J]. IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2018, : 2172 - 2175
  • [23] Retrieval of Significant Wave Height Under Typhoon Conditions from Gaofen-3 SAR Imagery
    Xiaochen Wang
    Bing Han
    Lihua Zhong
    Xinzhe Yuan
    [J]. Journal of Ocean University of China, 2022, 21 : 81 - 90
  • [24] CNN and Transformer Fusion Network for Sea Ice Classification Using GaoFen-3 Polarimetric SAR Images
    Zhang, Jiande
    Zhang, Wenyi
    Zhou, Xiao
    Chu, Qingwei
    Yin, Xiaoyi
    Li, Guangzuo
    Dai, Xiangyu
    Hu, Shuo
    Jin, Fukun
    [J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024, 17 : 18898 - 18914
  • [25] Maritime targets classification based on CNN using Gaofen-3 SAR images
    Ma, Mengyuan
    Zhang, Haojie
    Sun, Xiaokun
    Chen, Jie
    [J]. JOURNAL OF ENGINEERING-JOE, 2019, 2019 (21): : 7843 - 7846
  • [26] Significant Wave Height Retrieval Using XGBoost from Polarimetric Gaofen-3 SAR and Feature Importance Analysis
    Song, Tianran
    Yan, Qiushuang
    Fan, Chenqing
    Meng, Junmin
    Wu, Yuqi
    Zhang, Jie
    [J]. REMOTE SENSING, 2023, 15 (01)
  • [27] Utilizing a single-temporal full polarimetric Gaofen-3 SAR image to map coseismic landslide inventory following the 2017 Mw 7.0 Jiuzhaigou earthquake (China)
    Liang, Rubing
    Dai, Keren
    Xu, Qiang
    Pirasteh, Saeid
    Li, Zhenhong
    Li, Tao
    Wen, Ningling
    Deng, Jin
    Fan, Xuanmei
    [J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2024, 127
  • [28] Preliminary Evaluation of Gaofen-3 Quad-Polarized SAR Imagery for Longbao Protected Plateau Wetland Reserve
    Wei, Qiufang
    Shao, Yun
    Wang, Xiaochen
    [J]. JOURNAL OF SENSORS, 2019, 2019
  • [29] Evaluation of Wind Retrieval from Co-Polarization Gaofen-3 SAR Imagery Around China Seas
    SHAO Weizeng
    ZHU Shuai
    SUN Jian
    YUAN Xinzhe
    SHENG Yexin
    ZHANG Qingjun
    JI Qiyan
    [J]. Journal of Ocean University of China, 2019, 18 (01) : 80 - 92
  • [30] Wave Retrieval Under Typhoon Conditions Using a Machine Learning Method Applied to Gaofen-3 SAR Imagery
    Shao, Weizeng
    Ding, Yingying
    Li, Jichao
    Gou, Shuiping
    Nunziata, Ferdinando
    Yuan, Xinzhe
    Zhao, Liangbo
    [J]. CANADIAN JOURNAL OF REMOTE SENSING, 2019, 45 (06) : 723 - 732