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

• Main Authors: Xiaoping, Xie, Yujie, Liu, Bingyu, Du
• Format: Article in Journal/Newspaper
• Language: English
• Published: Polar Research Institute of China - PRIC 2007
• Subjects: Cryosphere; Arctic; Advances in Polar Science; Polar Science
• Online Access: http://library.arcticportal.org/2331/; http://library.arcticportal.org/2331/1/A200701007.pdf

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 days classifying result of Arctic snow and ice cover area, complete Arctic snow and ice cover area can be obtained. The result agrees with NO-AA/NESD IS MS products up to 70%.