Flood Monitoring Using Sentinel-1 SAR for Agricultural Disaster Assessment in Poyang Lake Region

被引:3
|
作者
Li, Hengkai [1 ]
Xu, Zikun [1 ]
Zhou, Yanbing [2 ]
He, Xiaoxing [1 ]
He, Minghua [1 ]
机构
[1] Jiangxi Univ Sci & Technol, Sch Civil & Surveying & Mapping Engn, Jiangxi Prov Educ Dept, Ganzhou 341000, Peoples R China
[2] Beijing Acad Agr & Forestry Sci, Informat Technol Res Ctr, Beijing 100097, Peoples R China
关键词
Sentinel-1; water extraction; flood disaster; decision tree; random forest; improved U-Net;
D O I
10.3390/rs15215247
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
An extensive number of farmlands in the Poyang Lake region of China have been submerged due to the impact of flood disasters, resulting in significant agricultural economic losses. Therefore, it is of great importance to conduct the long-term temporal monitoring of flood-induced water body changes using remote sensing technology. However, the scarcity of optical images and the complex, fragmented terrain are pressing issues in the current water body extraction efforts in southern hilly regions, particularly due to difficulties in distinguishing shadows from numerous mountain and water bodies. For this purpose, this study employs Sentinel-1 synthetic aperture radar (SAR) data, complemented by water indices and terrain features, to conduct research in the Poyang Lake area. The results indicate that the proposed multi-source data water extraction method based on microwave remote sensing data can quickly and accurately extract a large range of water bodies and realize long-time monitoring, thus proving a new technical means for the accurate extraction of floodwater bodies in the Poyang Lake region. Moreover, the comparison of several methods reveals that CAU-Net, which utilizes multi-band imagery as the input and incorporates a channel attention mechanism, demonstrated the best extraction performance, achieving an impressive overall accuracy of 98.71%. This represents a 0.12% improvement compared to the original U-Net model. Moreover, compared to the thresholding, decision tree, and random forest methods, CAU-Net exhibited a significant enhancement in extracting flood-induced water bodies, making it more suitable for floodwater extraction in the hilly Poyang Lake region. During this flood monitoring period, the water extent in the Poyang Lake area rapidly expanded and subsequently declined gradually. The peak water area reached 4080 km2 at the height of the disaster. The severely affected areas were primarily concentrated in Yongxiu County, Poyang County, Xinjian District, and Yugan County.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Monitoring Surface Water Inundation of Poyang Lake and Dongting Lake in China Using Sentinel-1 SAR Images
    Wang, Zirui
    Xie, Fei
    Ling, Feng
    Du, Yun
    [J]. REMOTE SENSING, 2022, 14 (14)
  • [2] Full Lifecycle Monitoring on Drought-Converted Catastrophic Flood Using Sentinel-1 SAR: A Case Study of Poyang Lake Region during Summer 2020
    Yang, Haoxiao
    Wang, Hongxian
    Lu, Jianzhong
    Zhou, Zhenzhong
    Feng, Qi
    Wu, Yue
    [J]. REMOTE SENSING, 2021, 13 (17)
  • [3] Flood monitoring in an Giang Province, Vietnam using global flood mapper and Sentinel-1 SAR
    Afifi, Ahmed S.
    Magdy, Ahmed
    [J]. REMOTE SENSING LETTERS, 2024, 15 (09) : 883 - 892
  • [4] Water Body Mapping Using Long Time Series Sentinel-1 SAR Data in Poyang Lake
    Shen, Guozhuang
    Fu, Wenxue
    Guo, Huadong
    Liao, Jingjuan
    [J]. WATER, 2022, 14 (12)
  • [5] Freshwater lake inundation monitoring using Sentinel-1 SAR imagery in Eastern Uganda
    Barasa, Bernard
    Wanyama, Joshua
    [J]. ANNALS OF GIS, 2020, 26 (02) : 191 - 200
  • [6] OPERATIONAL AGRICULTURAL FLOOD MONITORING WITH SENTINEL-1 SYNTHETIC APERTURE RADAR
    Boryan, Claire G.
    Yang, Zhengwei
    Sandborn, Avery
    Willis, Patrick
    Haack, Barry
    [J]. IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2018, : 5831 - 5834
  • [7] SENTINEL-1 SAR IMAGE CAPABILITIES FOR LAKE ICE COVER MONITORING
    Chaabani, Chayma
    Homayouni, Saeid
    Chokmani, Karem
    [J]. IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 203 - 206
  • [8] Flood Monitoring in Rural Areas of the Pearl River Basin (China) Using Sentinel-1 SAR
    Qiu, Junliang
    Cao, Bowen
    Park, Edward
    Yang, Xiankun
    Zhang, Wenxin
    Tarolli, Paolo
    [J]. REMOTE SENSING, 2021, 13 (07)
  • [9] STUDY ON POYANG LAKE HYDROLOGIC REGIME USING SENTINEL-1/3 DATA
    Shen, Guozhuang
    Fu, Wenxue
    [J]. 2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022), 2022, : 6197 - 6200
  • [10] AN AUTOMATIC FLOOD MONITORING SERVICE FROM SENTINEL-1 SAR: PRODUCTS, DELIVERY PIPELINES, AND PERFORMANCE ASSESSMENT
    Meyer, Franz J.
    Ajadi, Olaniyi A.
    Schultz, Lori
    Bell, Jordan
    Arnoult, Ken M.
    Gens, Rudiger
    Nicoll, Jeremy B.
    [J]. IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2018, : 6576 - 6579