摘要
通过Fisher判别法得到的混淆矩阵计算分类评价指标构建层次分类树模型,提出了一种基于Fisher判别的遥感影像森林地类层次分类法。利用杭州市部分地区的森林资源清查样地数据和Landsat8遥感影像数据进行试验,并与最大似然分类、支持向量机和随机森林分类的结果进行比较。结果表明:基于Fisher判别的层次分类法总分类精度为79.45%,比最大似然分类、支持向量机和随机森林分别高了12.33%、21.00%和10.50%,kappa系数为0.756 8,比最大似然法、支持向量机和随机森林分别高了0.145 5、0.256 4和0.126 4;基于Fisher判别分析方法的层次分类法模型中,层次分类树的节点依次是建设用地—水体—农地—竹林—阔叶林—针叶林—针阔混交林;基于Fisher判别的层次分类法中一个模型只能分出一个类别。
Fisher discriminant analysis has been applied to obtain the confusion matrix, which was used to calculate the classification evaluation index, and hierarchical classification tree model was built in accordance with these index. Thus, Fisher hierarchical classification method based on Fisher discriminant analysis was proposed to forest remote sensed images. A part of sample data from forest resources inventory and Landsat8 remote sensed image data of Hangzhou city were used to test this method, furthermore the results was compared to those of maximum likelihood classification method, support vector machine and random forest classification method. Results showed that the total classification accuracy of Fisher based hierarchical classification is 79.45%, which is higher than that of maximum likelihood classification, support vector machine and random forest by 12.33%, 21.00% and 10.50%, respectively. Kappa coefficient was 0.756 8, which meant it was higher than those from maximum likelihood method, support vector machine and random forest whose values were 0.145 5, 0.256 4 and 0.126 4, respectively. In the hierarchical classification model based on Fisher discriminant analysis, the gradation of hierarchical classification tree are construction land→water→farmland→bamboo grove→broad-leaved forest→coniferous forest→conifer-broadleaf forest. In the hierarchical classification based on Fisher discrimination, a model can only distinguish 1 category.
作者
杜靖媛
葛宏立
路伟
孟森
Du Jingyuan Ge Hongli Lu Wei Meng Sen(College of Information Engineering, Zhejiang A ＆ F University, Lin＇an Zhejiang 311300, China Zhejiang Provincial Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration, Lin＇an Zhejiang 311300, China)
出处
《西南林业大学学报（自然科学）》
CAS
北大核心
2017年第4期175-182,共8页
Journal of Southwest Forestry University：Natural Sciences
基金
国家自然科学基金项目(41371411)资助
关键词
Fisher判别法
层次分类法
影像分类
最大似然
支持向量机
随机森林
Fisher discriminant analysis, hierarchical classification, image classification, maximum likelihood, SVM, random forest
