Volume 6 Issue 2
May  2017
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Article Navigation >  Journal of Radars  > 2017  >  6(2): 204-212
Leng Ying, Li Ning. Improved Change Detection Method for Flood Monitoring[J]. Journal of Radars, 2017, 6(2): 204-212. doi: 10.12000/JR16139
Citation: Leng Ying, Li Ning. Improved Change Detection Method for Flood Monitoring[J]. Journal of Radars, 2017, 6(2): 204-212. doi: 10.12000/JR16139
shu

Improved Change Detection Method for Flood Monitoring

doi: 10.12000/JR16139
  • ①.

    Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China

  • ②.

    University of Chinese Academy of Sciences, Beijing 100190, China

Funds:  The National Natural Science Foundation for Excellent Young Scholars (61422113)
  • Received Date: 2016-12-05
  • Rev Recd Date: 2017-02-16
    • Available Online: 2017-03-21
  • Publish Date: 2017-04-28
    Abstract
  • An improved Hybrid Change Detection (HCD) method is proposed for multi-temporal Synthetic Aperture Radar (SAR) images. Firstly, a Pixel-Based Change Detection (PBCD) method is used to extract the initial change area, and the initial cluster center is estimated based on its results. Then, Fuzzy Clustering Method (FCM) is used to get three clusters, which including water, background, and the intermediate area. The Nearest Neighbor Clustering (NNC) is adopted as the second-level clustering to divide the pixels belonging to the intermediate area into water and background respectively, afterwards merge all pixels belonging to water. Finally, the difference map of flood region in the time series images is calculated to get the final change detection result. The algorithm is validated by the Sentinel-1A data obtained from Huaihe River and Poyang Lake. The results show that our proposed method can achieve better correctness and has lower total error compared to other methods.

     

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