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9 June 2006 Vegetation classification model based on high-resolution satellite imagery
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Proceedings Volume 6200, Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China; 62000F (2006) https://doi.org/10.1117/12.681279
Event: Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China, 2005, Guiyan City, China
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.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Junying Chen and Qingjiu Tian "Vegetation classification model based on high-resolution satellite imagery", Proc. SPIE 6200, Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China, 62000F (9 June 2006); https://doi.org/10.1117/12.681279
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