安徽农业科学2017，Vol.45Issue(28)：207-210,4.
基于水稻特征波段的决策树分类研究
Study on Decision Tree Classification Based on Multi-temporal Characteristic Bands of Rice
摘要
Abstract
Taking Chuzhou City as an example, combined with the characteristic band of rice phenology in remote sensing image, using TM data of the typical rice phenology, planting area of rice was extracted by CART decision tree classification based on the multi-feature band.The results showed that CART algorithm classification involved by vegetation index, humidity factor,green degree factor,texture feature and other characteristics can improve the overall accuracy.The decision tree classification based on spectral information, vegetation indices and texture features was 6.9421 percentage point higher in overall accuracy than that of supervised classification method based on maximum likelihood, and its Kappa coefficient increased 0.1104.So the reasonable selection of the characteristic bands of crop phenological data and remote sens-ing images could effectively reduce the classification error, which could provide new method for obtaining crop planting area extraction in the complex terrain area.关键词
多特征选择/CART决策树/水稻Key words
Multi-features selection/CART decision tree/Paddy rice分类
农业科技引用本文复制引用
张博文,崔林丽,史军,魏培培..基于水稻特征波段的决策树分类研究[J].安徽农业科学,2017,45(28):207-210,4.基金项目
国家自然科学基金项目(41571044,41401661,41001283) （41571044,41401661,41001283）
中国清洁发展机制基金项目(2012043). （2012043）
