中国地理科学(英文版) ›› 2004, Vol. 14 ›› Issue (3): 258-262.

• 论文 • 上一篇    下一篇

SHALLOW SEA WATER DEPTH RETRIEVAL BASED ON BOTTOM CLASSIFICATION FROM REMOTE SENSING IMAGERY

PANG Lei1,2, ZHANG Ming-bo3, ZHANG Ji-xian1, ZHENG Zhao-qing2, LIN Zong-jian1   

  1. 1. Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing 100039, P.R.China;
    2. Shandong University of Technology, Zibo 255049, P.R.China;
    3. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, P.R.China
  • 收稿日期:2004-04-07 出版日期:2004-09-20 发布日期:2011-12-15
  • 作者简介:PANG Lei(1971- ), female, a native of Weifang City of Shandong Province, Ph.D. candidate, specialized in remote sensing imagery processing and Synthetic Aperture Radar remote sensing application. E-mail: panglei.mail@163.com
  • 基金资助:

    Under the auspices of Scientific Foundation Research Project of the Ministry of Science and Technology and Chinese Academy of Surveying and Mapping (No.F0610)

SHALLOW SEA WATER DEPTH RETRIEVAL BASED ON BOTTOM CLASSIFICATION FROM REMOTE SENSING IMAGERY

PANG Lei1,2, ZHANG Ming-bo3, ZHANG Ji-xian1, ZHENG Zhao-qing2, LIN Zong-jian1   

  1. 1. Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing 100039, P.R.China;
    2. Shandong University of Technology, Zibo 255049, P.R.China;
    3. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, P.R.China
  • Received:2004-04-07 Online:2004-09-20 Published:2011-12-15

摘要:

Remote sensing technique, replacing conventional sonar bathymetry technique, has become an effective complementary method of mapping submarine terrain where special conditions make the sonar technique difficult to be carried out. At the same time, as one kind of data set, multispectral remote sensing data has the disadvantage of being influenced by the variable bottom types in shallow seawater, when it is applied in bathymetry. This paper puts forward a new method to extract water depth information from multispectral data, considering the bottom classification and the true water depth accuracy. That is the Principal Component Analysis (PCA) technique based on the bottom classification. By the least square regression with significance, the experiment near Qingdao City has obtained more satisfactory bathymetry accuracy than that of the traditional single-band method, with the mean absolute error about 2.57m.

关键词: multispectral remote sensing, bathymetry model, PCA, bottom classification

Abstract:

Remote sensing technique, replacing conventional sonar bathymetry technique, has become an effective complementary method of mapping submarine terrain where special conditions make the sonar technique difficult to be carried out. At the same time, as one kind of data set, multispectral remote sensing data has the disadvantage of being influenced by the variable bottom types in shallow seawater, when it is applied in bathymetry. This paper puts forward a new method to extract water depth information from multispectral data, considering the bottom classification and the true water depth accuracy. That is the Principal Component Analysis (PCA) technique based on the bottom classification. By the least square regression with significance, the experiment near Qingdao City has obtained more satisfactory bathymetry accuracy than that of the traditional single-band method, with the mean absolute error about 2.57m.

Key words: multispectral remote sensing, bathymetry model, PCA, bottom classification

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