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Li, J.M., Xing, Y.Q., Yang, C. and Li, Z.Y. (2013) Forest Type Identification Based on Hyperspectral Remote Sensing Image of Environment and Disaster Monitoring Satellite. Journal of Northeast Forestry University, 41, 41-45+50.

has been cited by the following article:

• TITLE: Applications of Hyperspectral Remote Sensing in Ground Object Identification and Classification

  AUTHORS: Yu Wei, Xicun Zhu, Cheng Li, Xiaoyan Guo, Xinyang Yu, Chunyan Chang, Houxing Sun

  KEYWORDS: Hyperspectral Remote Sensing, Ground Object Identification and Classification, Statistical Model, Spectral Matching

  JOURNAL NAME: Advances in Remote Sensing, Vol.6 No.3, September 14, 2017

  ABSTRACT: Hyperspectral remote sensing has become one of the research frontiers in ground object identification and classification. On the basis of reviewing the application of hyperspectral remote sensing in identification and classification of ground objects at home and abroad. The research results of identification and classification of forest tree species, grassland and urban land features were summarized. Then the researches of classification methods were summarized. Finally the prospects of hyperspectral remote sensing in ground object identification and classification were prospected.