极地研究

极地研究 ›› 2007, Vol. 18 ›› Issue (1-English): 54-62.

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Detecting Arctic snow and ice cover with FY-1D global data

 Xie Xiaoping1, Liu Yujie2 and Du Bingyu1   

  1. 1 School of Remote Sensing of NUIST, Nanjing 210044, China;
    2 National Satellite Meteorological Center, Beijing 100081, China
  • 出版日期:1957-03-30 发布日期:1957-03-30
  • 通讯作者: Xie Xiaoping

Detecting Arctic snow and ice cover with FY-1D global data

 Xie Xiaoping1, Liu Yujie2 and Du Bingyu1   

  1. 1 School of Remote Sensing of NUIST, Nanjing 210044, China;
    2 National Satellite Meteorological Center, Beijing 100081, China
  • Online:1957-03-30 Published:1957-03-30
  • Contact: Xie Xiaoping

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摘要：

Chinese meteorological satellite FY-1D can obtain global data from four spectral channels which include visible channel (0.58-0.68 μm) and infrared channels (0.84-0.89 μm, 10.3-11.3 μm, 11.5-12.5 μm). 2366 snow and ice samples, 2024 cloud samples,1602 land samples and 1648 water samples were selected randomly from Arctic imageries. Land and water can be detected by spectral features. Snow-ice and cloud can be classified by textural features. The classifier is Bayes classifier. By synthesizing five d ays classifying result of Arctic snow and ice cover area, complete Arctic snow and ice cover area can be obtained. The result agrees with NOAA/NESDIS IMS products up to 70%.

关键词: FY-1D, Arctic, snow and ice cover, Bayes classification

Abstract:

Chinese meteorological satellite FY-1D can obtain global data from four spectral channels which include visible channel (0.58-0.68 μm) and infrared channels (0.84-0.89 μm, 10.3-11.3 μm, 11.5-12.5 μm). 2366 snow and ice samples, 2024 cloud samples,1602 land samples and 1648 water samples were selected randomly from Arctic imageries. Land and water can be detected by spectral features. Snow-ice and cloud can be classified by textural features. The classifier is Bayes classifier. By synthesizing five d ays classifying result of Arctic snow and ice cover area, complete Arctic snow and ice cover area can be obtained. The result agrees with NOAA/NESDIS IMS products up to 70%.

Key words: FY-1D, Arctic, snow and ice cover, Bayes classification