Multi-level measurements for uncertainty in classified remotely sensed imagery
文献类型：会议论文
| 作者 | Ge Y. |
| 出版日期 | 2008 |
| 关键词 | remote sensing classification image uncertainty measurement indices visual expression |
| 页码 | 171-178 |
| 英文摘要 | How to measure the uncertainty in remotely sensed data is one of key issues in the uncertainty research on remotely sensed information. In this paper, we utilize information theory, rough set theory to measure the uncertainty in classified remotely sensed imagery and then propose multi-level measurement indices for classified remotely sensed imagery, that is, pixel-level index, class/object-level indices and image-level indices. Following these above discussions, a case study of the Landsat TM image on China Yellow River Delta is used to describe the multi-level measurements. |
| 收录类别 | CPCI |
| 会议录出版者 | World Acad Union-World Acad Press |
| 语种 | 英语 |
| ISBN号 | 978-1-84626-171-8 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/25107]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Ge Y.. Multi-level measurements for uncertainty in classified remotely sensed imagery[C]. 见:. |
入库方式： OAI收割
来源：地理科学与资源研究所
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