Land use classification using CBERS-1 data

  • Wang, Huarui (JiaoZuoChemical Plant) ;
  • Liu, Aixia (LARSIS, Institute of Remote Sensing Applications, Chinese Academy of Sciences) ;
  • Lu, Zhenhjun (LARSIS, Institute of Remote Sensing Applications, Chinese Academy of Sciences)
  • 발행 : 2002.10.01

초록

This paper discussed and analyzed results of different classification algorithms for land use classification in arid and semiarid areas using CBERS-1 image, which in case of our study is Shihezi Municipality, Xinjiang Province. Three types of classifiers are included in our experiment, including the Maximum Likelihood classifier, BP neural network classifier and Fuzzy-ARTMAP neural network classifier. The classification results showed that the classification accuracy of Fuzzy-ARTMAP was the best among three classifiers, increased by 10.69% and 6.84% than Maximum likelihood and BP neural network, respectively. Meanwhile, the result also confirmed the practicability of CBERS-1 image in land use survey.

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