干旱区生态环境知识资源中心(Arid): 基于二次分类的葡萄干晾房遥感信息挖掘及反演

Arid

	基于二次分类的葡萄干晾房遥感信息挖掘及反演
其他题名	Data Mining and Retrieval of Remote Sensing Information in Raisin Room Based on Secondary Classification
	陈蜀江 1; 马静 2; 李春蕾 3; 黄铁成 1; 贾翔 1
来源期刊	西北农业学报
ISSN	1004-1389
出版年	2015
卷号	24 期号:3 页码:111-120
中文摘要	以鄯善绿洲为研究靶区,应用遥感技术对葡萄干晾房遥感影像特征进行光谱和纹理分析,使用二次分类方法提取葡萄干加工晾房信息。结果表明,晾房光谱特征由晾房顶部和阴影组成,纹理特征因具有阴影而增强;葡萄干晾房斑块共有701块,占地面积3 120 hm~2,最大斑块面积178 hm~2,最小斑块面积338.76 m~2,平均面积4.34 hm~2;建筑单体18 819栋,建筑面积261 hm~2。经验证,一次分类精度为84.06%,Kappa系数为0.80;二次分类精度为88.66%,Kappa系数为0.84。
英文摘要	Taking oasis in Shanshan area as research target,remote sensing images of rooms for drying raisin were analyzed in spectrum and texture,information about the rooms for trying raisins was extracted by secondary classification method during raisin processing.Result showed that the spectral characteristics of drying rooms were composed of hanged roof and shadow,and the texture feature was enhanced by the shadow; plaques of raisin drying rooms were 701 pieces together,which covered 3 120 hm~2,the patch area ranged from 338.76 m~2 to 178 hm~2,and the average area was 4.34 hm~2; single buildings were 18 819 with building area of 261 hm~2. Verification indicated that the first classification accuracy was 84.06% with the Kappa coefficient 0.80,and the secondary classification accuracy was 88.66% with the Kappa coefficient 0.84.
中文关键词	葡萄干加工晾房 ; 光谱特征 ; 纹理特征 ; 二次分类
英文关键词	Raisin room Spectral signature Texture feature Secondary classification
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:5389448
来源机构	新疆师范大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/233489
作者单位	1.新疆师范大学地理科学与旅游学院, 乌鲁木齐, 新疆 830054, 中国; 2.吐鲁番地区国土资源勘测规划院, 吐鲁番, 新疆 838000, 中国; 3.中国林业科学研究院森林生态环境与保护研究所, 北京 100091, 中国
推荐引用方式 GB/T 7714	陈蜀江,马静,李春蕾,等. 基于二次分类的葡萄干晾房遥感信息挖掘及反演[J]. 新疆师范大学,2015,24(3):111-120.
APA	陈蜀江,马静,李春蕾,黄铁成,&贾翔.(2015).基于二次分类的葡萄干晾房遥感信息挖掘及反演.西北农业学报,24(3),111-120.
MLA	陈蜀江,et al."基于二次分类的葡萄干晾房遥感信息挖掘及反演".西北农业学报 24.3(2015):111-120.