Impervious surface extraction using coupled spectral-spatial features
文献类型：期刊论文
| 作者 | Yu, Xinju1; Shen, Zhanfeng1; Cheng, Xi1; Xia, Liegang1; Luo, Jiancheng1 |
| 刊名 | Journal of Applied Remote Sensing
 |
| 出版日期 | 2016 |
| 卷号 | 10期号:3 |
| 关键词 | SUPPORT VECTOR MACHINES OBJECT DETECTION BAG REPRESENTATION FUSION KERNEL SCALE |
| 通讯作者 | Shen, Zhanfeng (shenzf@radi.ac.cn) |
| 英文摘要 | Accurate extraction of urban impervious surface data from high-resolution imagery remains a challenging task because of the spectral heterogeneity of complex urban land-cover types. Since the high-resolution imagery simultaneously provides plentiful spectral and spatial features, the accurate extraction of impervious surfaces depends on effective extraction and integration of spectral-spatial multifeatures. Different features have different importance for determining a certain class; traditional multifeature fusion methods that treat all features equally during classification cannot utilize the joint effect of multifeatures fully. A fusion method of distance metric learning (DML) and support vector machines is proposed to find the impervious and pervious subclasses from Chinese ZiYuan-3 (ZY-3) imagery. In the procedure of finding appropriate spectral and spatial feature combinations with DML, optimized distance metric was obtained adaptively by learning from the similarity side-information generated from labeled samples. Compared with the traditional vector stacking method that used each feature equally for multifeatures fusion, the approach achieves an overall accuracy of 91.6% (4.1% higher than the prior one) for a suburban dataset, and an accuracy of 92.7% (3.4% higher) for a downtown dataset, indicating the effectiveness of the method for accurately extracting urban impervious surface data from ZY-3 imagery. © 2016 Society of Photo-Optical Instrumentation Engineers (SPIE). |
| 学科主题 | Environmental Sciences & Ecology; Remote Sensing; Imaging Science & Photographic Technology |
| 类目[WOS] | Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:20163402732790 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39377]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1. Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing 2.100101, China 3. Chengdu University of Technology, School of Geophysics, Chengdu 4.610059, China 5. Zhejiang University of Technology, College of Computer Science and Technology, Hangzhou 6.310014, China |
| 推荐引用方式 GB/T 7714 | Yu, Xinju,Shen, Zhanfeng,Cheng, Xi,et al. Impervious surface extraction using coupled spectral-spatial features[J]. Journal of Applied Remote Sensing,2016,10(3). |
| APA | Yu, Xinju,Shen, Zhanfeng,Cheng, Xi,Xia, Liegang,&Luo, Jiancheng.(2016).Impervious surface extraction using coupled spectral-spatial features.Journal of Applied Remote Sensing,10(3). |
| MLA | Yu, Xinju,et al."Impervious surface extraction using coupled spectral-spatial features".Journal of Applied Remote Sensing 10.3(2016). |
入库方式： OAI收割
来源：遥感与数字地球研究所
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