Study on Classification for Vegetation Spectral Feature Extraction Method Based on Decision Tree Algorithm

摘要：

Vegetation classification methods of spectral data are very important for remote sensing fields. We can get essential information from remote data by classification. This paper proposes a method for vegetation classification, which uses a decision tree algorithm for this target. First, we analyze spectral characteristics of extracted features of vegetation spectral data. Then, we use a decision tree algorithm that chooses three characteristics as candidate attributes for classification. Finally, we show some experimental results for the method. Experimental results indicate the effectiveness of the proposed method.

关键词： vegetation feature extract decision tree technology

作者: Weiwei Li Jian Du Baolin Yi

作者单位: Dept. of Computer Science, Huazhong Normal University, Wuhan, P. R. China Dept. of National Digital Learning Engineering Research Center, Huazhong Normal University,Wuhan, P.

会议类型: 国际会议

会议名称: 2011 International Conference on Image Analysis and Signal Processing(2011第三届图像分析与信号处理国际会议 IASP 2011)

会议地点: 武汉

会议语种:英文

页码: 665-669

在线出版日期: 2011-10-21（万方平台首次上网日期，不代表论文的发表时间）