中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Evaluation of the Chinese fine spatial resolution hyperspectral satellite TianGong-1 in urban land-cover classification

文献类型:期刊论文

作者Li, Xueke1; Wu, Taixia1; Liu, Kai1; Li, Yao1; Zhang, Lifu1
刊名Remote Sensing
出版日期2016
卷号8期号:5
关键词SURFACE SHORTWAVE RADIATION CLEAR-SKY DAYS BROAD-BAND MODELS LANDSAT-TM DATA NET-RADIATION HETEROGENEOUS LANDSCAPE IRRADIANCE PREDICTIONS RUGGED TERRAIN EARTHS SURFACE SATELLITE DATA
通讯作者Wu, Taixia (wutx@radi.ac.cn)
英文摘要The successful launch of the Chinese high spatial resolution hyperspectral satellite TianGong-1 (TG-1) opens up new possibilities for applications of remotely-sensed satellite imagery. One of the main goals of the TG-1 mission is to provide observations of surface attributes at local and landscape spatial scales to map urban land cover accurately using the hyperspectral technique. This study attempted to evaluate the TG-1 datasets for urban feature analysis, using existing data over Beijing, China, by comparing the TG-1 (with a spatial resolution of 10 m) to EO-1 Hyperion (with a spatial resolution of 30 m). The spectral feature of TG-1 was first analyzed and, thus, finding out optimal hyperspectral wavebands useful for the discrimination of urban areas. Based on this, the pixel-based maximum likelihood classifier (PMLC), pixel-based support vector machine (PSVM), hybrid maximum likelihood classifier (HMLC), and hybrid support vector machine (HSVM) were implemented, as well as compared in the application of mapping urban land cover types. The hybrid classifier approach, which integrates the pixel-based classifier and the object-based segmentation approach, was demonstrated as an effective alternative to the conventional pixel-based classifiers for processing the satellite hyperspectral data, especially the fine spatial resolution data. For TG-1 imagery, the pixel-based urban classification was obtained with an average overall accuracy of 89.1%, whereas the hybrid urban classification was obtained with an average overall accuracy of 91.8%. For Hyperion imagery, the pixel-based urban classification was obtained with an average overall accuracy of 85.9%, whereas the hybrid urban classification was obtained with an average overall accuracy of 86.7%. Overall, it can be concluded that the fine spatial resolution satellite hyperspectral data TG-1 is promising in delineating complex urban scenes, especially when using an appropriate classifier, such as the hybrid classifier. © 2016 by the authors.
学科主题Remote Sensing
类目[WOS]Remote Sensing
收录类别SCI ; EI
语种英语
WOS记录号WOS:20162302468668
源URL[http://ir.radi.ac.cn/handle/183411/39440]  
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. Department of Geography, University of Connecticut, Storrs, Mansfield
2.CT
3.06269, United States
4. State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing
5.100101, China
6. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources, Chinese Academy of Sciences, Beijing
7.100101, China
8. University of Chinese Academy of Sciences, Beijing
9.100094, China
推荐引用方式
GB/T 7714
Li, Xueke,Wu, Taixia,Liu, Kai,et al. Evaluation of the Chinese fine spatial resolution hyperspectral satellite TianGong-1 in urban land-cover classification[J]. Remote Sensing,2016,8(5).
APA Li, Xueke,Wu, Taixia,Liu, Kai,Li, Yao,&Zhang, Lifu.(2016).Evaluation of the Chinese fine spatial resolution hyperspectral satellite TianGong-1 in urban land-cover classification.Remote Sensing,8(5).
MLA Li, Xueke,et al."Evaluation of the Chinese fine spatial resolution hyperspectral satellite TianGong-1 in urban land-cover classification".Remote Sensing 8.5(2016).

入库方式: OAI收割

来源:遥感与数字地球研究所

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