Effective vegetation optical depth retrieval using microwave vegetation indices from WindSat data for short vegetation
文献类型：期刊论文
| 作者 | Li, Yunqing1; Shi, Jiancheng1; Zhao, Tianjie1 |
| 刊名 | JOURNAL OF APPLIED REMOTE SENSING
 |
| 出版日期 | 2015 |
| 卷号 | 9页码:88-101 |
| 关键词 | microwave vegetation indices from WindSat data effective vegetation optical depth retrieval short vegetation normalized difference vegetation index |
| 通讯作者 | Shi, JC (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, CAS Olymp S&T Pk 20 Da Tun Rd,POB 9718, Beijing 100101, Peoples R China. |
| 英文摘要 | Vegetation optical depth (VOD) and effective vegetation optical depth (EVOD) are key factors for estimating soil moisture and vegetation parameters. Microwave vegetation indices (MVIs, including A and B parameters) have been recently developed for short-vegetation covered surfaces. The MVIs parameter B (MVIs_B) is mainly related to vegetation conditions, which makes it provide a potential way of EVOD retrieval. A theoretical expression deriving EVOD was deduced using MVIs_B from WindSat data. Global patterns of EVOD were analyzed subsequently. It has been shown that EVOD retrieved from MVIs performed a consistent global pattern and seasonal variation with normalized difference vegetation index. Time-series data from the Central Tibetan Plateau Soil Moisture/Temperature Monitoring Network, which is grassland dominated, was selected for temporal analysis. It was found that the temporal EVOD from WindSat MVIs can capture the growth trend of vegetation. Comparisons between EVOD estimations from MVIs and a radiative transfer model were also performed over this network. It was found that EVOD from the two methods exhibited comparable values and similar trends. MVIs_B-derived EVOD can be obtained without any other auxiliary data and has great potential in land-surface parameter retrieval over short-vegetation covered areas. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE) |
| 研究领域[WOS] | Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000365887900001 |
| 源URL | [http://ir.ceode.ac.cn/handle/183411/38083]  |
| 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.[Li, Yunqing 2.Shi, Jiancheng 3.Zhao, Tianjie] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China 4.[Li, Yunqing] Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.[Shi, Jiancheng 6.Zhao, Tianjie] Joint Ctr Global Change Studies, Beijing 100875, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Yunqing,Shi, Jiancheng,Zhao, Tianjie. Effective vegetation optical depth retrieval using microwave vegetation indices from WindSat data for short vegetation[J]. JOURNAL OF APPLIED REMOTE SENSING,2015,9:88-101. |
| APA | Li, Yunqing,Shi, Jiancheng,&Zhao, Tianjie.(2015).Effective vegetation optical depth retrieval using microwave vegetation indices from WindSat data for short vegetation.JOURNAL OF APPLIED REMOTE SENSING,9,88-101. |
| MLA | Li, Yunqing,et al."Effective vegetation optical depth retrieval using microwave vegetation indices from WindSat data for short vegetation".JOURNAL OF APPLIED REMOTE SENSING 9(2015):88-101. |
入库方式： OAI收割
来源：遥感与数字地球研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。