
Proceedings Paper
Vegetation classification model based on high-resolution satellite imageryFormat | Member Price | Non-Member Price |
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Paper Abstract
Based on a SPOT-5 image, this study built knowledge pool of vegetation spectral information, adopted classification algorithm of decision tree, proposed a vegetation classification model based on their spectral information and classified the vegetation of Nanjing. The results showed that the overall accuracy was 86.95% and Kappa coefficient was 0.8287. Then the classification model was validated by using an IKONOS image of Yuhuatai region and was improved through combining the textural information. The classification overall accuracy was increased to 92.70% and Kappa coefficient was increased to 0.8648.
Paper Details
Date Published: 9 June 2006
PDF: 9 pages
Proc. SPIE 6200, Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China, 62000F (9 June 2006); doi: 10.1117/12.681279
Published in SPIE Proceedings Vol. 6200:
Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China
Qingxi Tong; Wei Gao; Huadong Guo, Editor(s)
PDF: 9 pages
Proc. SPIE 6200, Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China, 62000F (9 June 2006); doi: 10.1117/12.681279
Show Author Affiliations
Published in SPIE Proceedings Vol. 6200:
Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China
Qingxi Tong; Wei Gao; Huadong Guo, Editor(s)
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