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Citation:

A Study on Extracting Vegetation Information from the Hyperspectral Fusion Images of CHRIS/PROBA

  • Received Date: 2011-01-10
  • Based on Gram-Schmidt transformation and fusion method,the paper provides a improved method of extracting wetland vegetation information in Long Baotan area in Qinghai Province from the hyperspectral fusion image. Firstly to caculate the NDVI of-36° image, and to fuse with 0° image. Then, the Spectral Angle Mapper,SAM, a supervised classification method was carried out on the new fusion image.The result showed that the extraction accuracy of the vegetaion information approach to 92.23%, while it was only 66% if the SAM was used directly to the 0° CHRIS image. The result also indicated that multi-angle and hyperspectral remotely sensed data had important application potentiality in extraction of wetland vegetation information.
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A Study on Extracting Vegetation Information from the Hyperspectral Fusion Images of CHRIS/PROBA

  • 1. Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China

Abstract: Based on Gram-Schmidt transformation and fusion method,the paper provides a improved method of extracting wetland vegetation information in Long Baotan area in Qinghai Province from the hyperspectral fusion image. Firstly to caculate the NDVI of-36° image, and to fuse with 0° image. Then, the Spectral Angle Mapper,SAM, a supervised classification method was carried out on the new fusion image.The result showed that the extraction accuracy of the vegetaion information approach to 92.23%, while it was only 66% if the SAM was used directly to the 0° CHRIS image. The result also indicated that multi-angle and hyperspectral remotely sensed data had important application potentiality in extraction of wetland vegetation information.

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