干旱区生态环境知识资源中心(Arid): NWFE结合纹理特征的SVM土地覆被分类方法研究

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	NWFE结合纹理特征的SVM土地覆被分类方法研究
其他题名	Land Cover Classification with SVM Based on NWFE and Texture Features
	崔林林; 罗毅; 包安明
来源期刊	国土资源遥感
ISSN	1001-070X
出版年	2012
期号	1 页码:36-42
中文摘要	为提高土地覆被分类精度,采用非参数权重特征提取(nonparametric weighted feature extraction,NWFE)结合纹理特征的支持向量机(support vector machines,SVM)的分类法,对新疆玛纳斯河流域绿洲区2006年的土地覆被进行分类,并将该方法与主成分分析(principal component analysis,PCA)结合纹理特征的SVM分类、原始波段结合纹理特征的SVM分类进行对比。结果表明,NWFE结合纹理特征的SVM分类结果优于其他2种分类结果,不仅反映了土地覆被分布的整体情况,而且使不同土地覆被类型得到较好的区分,总体分类精度达89.17%。
英文摘要	Land cover classification based on remote sensing image is of significant importance to agriculture,forestry and environment monitoring.Algorithm of remote sensing information retrieval is always an important research topic in this field.This paper made an effort to combine the Nonparametric Weighted Feature Extraction(NWFE) and texture features with the Support Vector Machines(SVM) so as to achieve a higher classification precision.The combined approach was applied to land cover classification of the Manasi River oasis in Xinjiang in 2006,and was compared with approaches of SVM based on Principal Component Analysis(PCA) and texture features and based on original bands and texture features.The results show that the method of SVM combined with NWFE and texture features can capture not only the distribution of land cover but also the difference among land cover types.An overall classification accuracy of 89.17% is obtained,which is better than those of two other classification results.
中文关键词	非参数权重特征提取(NWFE) ; 支持向量机(SVM) ; 土地覆被分类
英文关键词	nonparametric weighted feature extraction(NWFE) support vector machines(SVM) land cover classification
语种	中文
国家	中国
收录类别	CSCD
WOS类目	REMOTE SENSING ; AUTOMATION CONTROL SYSTEMS ; AGRICULTURE MULTIDISCIPLINARY
WOS研究方向	Remote Sensing ; Automation & Control Systems ; Agriculture
CSCD记录号	CSCD:4457356
来源机构	中国科学院新疆生态与地理研究所
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/228219
作者单位	中国科学院新疆生态与地理研究所, 乌鲁木齐, 新疆 830011, 中国
推荐引用方式 GB/T 7714	崔林林,罗毅,包安明. NWFE结合纹理特征的SVM土地覆被分类方法研究[J]. 中国科学院新疆生态与地理研究所,2012(1):36-42.
APA	崔林林,罗毅,&包安明.(2012).NWFE结合纹理特征的SVM土地覆被分类方法研究.国土资源遥感(1),36-42.
MLA	崔林林,et al."NWFE结合纹理特征的SVM土地覆被分类方法研究".国土资源遥感 .1(2012):36-42.