干旱区生态环境知识资源中心(Arid): 基于C5.0决策树算法的西北干旱区土地覆盖分类研究以甘肃省武威市为例

Arid

	基于C5.0决策树算法的西北干旱区土地覆盖分类研究以甘肃省武威市为例
其他题名	The Study of the Northwest Arid Zone Land-Cover Classification Based on C5.0 Decision Tree Algorithm at Wuwei City,Gansu Province
	齐红超; 祁元; 徐瑱
ISSN	1004-0323
出版年	2009
卷号	24 期号:5 页码:648-653,图版Ⅴ
中文摘要	西北干旱区面积广阔,由于土地利用类型多样,成因复杂,对环境变化敏感、变化过程快、幅度大、景观差异明显等特点,在影像上表现出的"同物异谱"现象明显;利用常规目视解译、监督非监督分类、人工参与的决策树分类等方法在效率或精度等方面各有其缺陷.采用机器学习C5.0决策树算法,综合利用地物波谱、NDVI、TC、纹理等信息,根据样本数据自动挖掘分类规则并对整个研究区进行地物分类.机器学习的决策树可以挖掘出更多的分类规则,C5.0算法对采样数据的分布没有要求,可以处理离散和连续数据,生成的规则易于理解,分类精度高,可以满足西北干旱区大面积的土地利用/覆被变化制图的需要.
英文摘要	In the broadly northwest arid regions,frequently,same object has different spectral characters because of the special characteristics of land cover change such as complex causes of formation,sensitivity to environment change,rapid and violent change and obvious differences in landscape. The conventional methods of classification including visual interpretation,supervised classification,unsupervised classification,and artificial decision tree classification have disadvantages in the efficiency or the accuracy. In this paper,machine learning algorithm based on C5. 0 decision tree was used to classify the entire study area automatically according to the sample data mining classification rules. Spectral features,NDVI,TC,texture and other informations were involved in the algorithm. More classification rules could be mined by machine learning decision tree. C5. 0 algorithm handling with both continuous and discrete data is independent of the distribution of sampling sites,The classification rules mined by this algorithm were interpretable. Other superiority of this algorithm included the fast speed of training and higher accuracy than many other classifiers. Thus,it is able to be used in the mapping of land use/cover change in a large scale in northwest arid regions.
中文关键词	C5.0算法 ; 西北干旱区 ; 土地覆被
英文关键词	See5.0 NLCD C5. 0 algorithm The northwest arid region Land cover See5. 0 NLCD
语种	中文
国家	中国
收录类别	CSCD
WOS类目	REMOTE SENSING
WOS研究方向	Remote Sensing
CSCD记录号	CSCD:3736976
来源机构	中国科学院西北生态环境资源研究院
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/224400
作者单位	中国科学院寒区旱区环境与工程研究所, 兰州, 甘肃 730000, 中国
推荐引用方式 GB/T 7714	齐红超,祁元,徐瑱. 基于C5.0决策树算法的西北干旱区土地覆盖分类研究以甘肃省武威市为例[J]. 中国科学院西北生态环境资源研究院,2009,24(5):648-653,图版Ⅴ.
APA	齐红超,祁元,&徐瑱.(2009).基于C5.0决策树算法的西北干旱区土地覆盖分类研究以甘肃省武威市为例.,24(5),648-653,图版Ⅴ.
MLA	齐红超,et al."基于C5.0决策树算法的西北干旱区土地覆盖分类研究以甘肃省武威市为例".24.5(2009):648-653,图版Ⅴ.