Current progress of hyperspectral remote sensing in China
文献类型：期刊论文
| 作者 | Tong, Qingxi1; Zhang, Bing1; Zhang, Lifu1 |
| 刊名 | Yaogan Xuebao/Journal of Remote Sensing
 |
| 出版日期 | 2016 |
| 卷号 | 20期号:5页码:689-707 |
| 通讯作者 | Zhang, Lifu (zhanglf@radi.ac.cn) |
| 英文摘要 | Hyperspectral Remote Sensing (HRS), also known as hyperspectral imaging, has been considered one of the greatest breakthroughs in the remote sensing science and technology, attributed to its unique advantages in very high spectral resolutions as well as allowing for the synchronous acquisition of both images and spectra of objects. China, as one of the pioneers in HRS technology development, has made great achievements in both hypersepctral image processing and subsequent applications to real world problems under the supports of national and ministerial and provincial-level governments. These advances have bridged the gap between the most advanced theoretical contributions and their actual use in a number of applications including agriculture, mineral and energy resource exploration, environment, preservation of cultural relics, producing really rare and invaluable societal and economical impacts. This paper reviews current progresses in HRS in China, presenting main innovative achievements. © 2016, Science Press. All right reserved. |
| 收录类别 | EI |
| 语种 | 中文 |
| WOS记录号 | WOS:20164402965568 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39611]  |
| 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. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 2.100101, China |
| 推荐引用方式 GB/T 7714 | Tong, Qingxi,Zhang, Bing,Zhang, Lifu. Current progress of hyperspectral remote sensing in China[J]. Yaogan Xuebao/Journal of Remote Sensing,2016,20(5):689-707. |
| APA | Tong, Qingxi,Zhang, Bing,&Zhang, Lifu.(2016).Current progress of hyperspectral remote sensing in China.Yaogan Xuebao/Journal of Remote Sensing,20(5),689-707. |
| MLA | Tong, Qingxi,et al."Current progress of hyperspectral remote sensing in China".Yaogan Xuebao/Journal of Remote Sensing 20.5(2016):689-707. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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