Institutional Repository of Key Laboratory of Coastal Zone Environmental Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences (KLCEP)
| Remote-sensing estimation of dissolved inorganic nitrogen concentration in the Bohai Sea using band combinations derived from MODIS data | |
Yu, X; Yi, HP; Liu, XY; Wang, YB; Liu, X ; Zhang, H; Liu, X (reprint author), Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China. xliu@yic.ac.cn
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| 发表期刊 | INTERNATIONAL JOURNAL OF REMOTE SENSING
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| ISSN | 0143-1161 |
| 2016 | |
| 卷号 | 37期号:2页码:327-340 |
| DOI | 10.1080/01431161.2015.1125555 |
| 产权排序 | [Yu, Xiang; Liu, Xiangyang; Wang, Yebao; Liu, Xin; Zhang, Hua] Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China; [Yu, Xiang; Liu, Xiangyang; Wang, Yebao] Univ Chinese Acad Sci, Beijing, Peoples R China; [Yi, Huapeng] Ludong Univ, Inst Geog & Planning, Yantai, Peoples R China |
| 作者部门 | 海岸带信息集成与综合管理实验室 |
| 英文摘要 | Remote sensing has been widely used for water quality monitoring, but most monitoring studies have only focused on a few water quality variables, such as chlorophyll-a, turbidity, and total suspended solids, which have typically been considered optically active variables. Remote sensing presents a challenge in estimating dissolved inorganic nitrogen (DIN) concentration in water. DIN in inland waters and estuaries had been estimated from remotely sensed observations. However, remote-sensing estimation of DIN in seawater over a large area had not yet been performed. Moreover, the bands used to estimate DIN in water were limited to 4 or 7 anterior bands of Moderate Resolution Imaging Spectroradiometer (MODIS) data at high spatial resolution rather than high spectral resolution. In this study, we attempted to establish a model to estimate DIN concentration in the Bohai Sea using band combinations derived from all the visible/nearinfrared (Vis-NIR) bands of MODIS data. The results showed that regional multiple stepwise regression analysis (MLSR) yields a highly significant positive relationship between DIN concentration and certain remotely sensed combination variables. The modelling yielded higher accuracy for DIN concentration estimation in the Bohai Sea compared with previous studies. DIN concentration values showed a clear spatial variability, being high in coastal waters and relatively low further out. These results strongly suggest that the modelling demonstrates advantages for estimating DIN concentration in the Bohai Sea and has major potential for universal application in DIN concentration estimation in other waters. |
| 文章类型 | Article |
| 资助机构 | Key Research Programme of the Chinese Academy of Sciences(NSFC41371483 ; Shandong Province Natural Science Fund Committee(ZR2011DL013) ; KZZD-EW-14) |
| 收录类别 | SCI |
| 语种 | 英语 |
| 关键词[WOS] | WATER-QUALITY ; SENSED DATA ; PHOSPHORUS ; LAKES ; EUTROPHICATION ; LIMITATION ; ALGORITHM ; EVOLUTION ; RESERVOIR ; RIVER |
| 研究领域[WOS] | Remote Sensing ; Imaging Science & Photographic Technology |
| WOS记录号 | WOS:000368724700004 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.yic.ac.cn/handle/133337/9291 |
| 专题 | 中国科学院海岸带环境过程与生态修复重点实验室 中国科学院海岸带环境过程与生态修复重点实验室_污染过程与控制实验室 |
| 通讯作者 | Liu, X (reprint author), Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China. xliu@yic.ac.cn |
| 作者单位 | 1.Chinese Acad Sci, Yantai Inst Coastal Zone Res 2.Univ Chinese Acad Sci 3.Ludong Univ, Inst Geog & Planning |
| 推荐引用方式 GB/T 7714 | Yu, X,Yi, HP,Liu, XY,et al. Remote-sensing estimation of dissolved inorganic nitrogen concentration in the Bohai Sea using band combinations derived from MODIS data[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2016,37(2):327-340. |
| APA | Yu, X.,Yi, HP.,Liu, XY.,Wang, YB.,Liu, X.,...&Liu, X .(2016).Remote-sensing estimation of dissolved inorganic nitrogen concentration in the Bohai Sea using band combinations derived from MODIS data.INTERNATIONAL JOURNAL OF REMOTE SENSING,37(2),327-340. |
| MLA | Yu, X,et al."Remote-sensing estimation of dissolved inorganic nitrogen concentration in the Bohai Sea using band combinations derived from MODIS data".INTERNATIONAL JOURNAL OF REMOTE SENSING 37.2(2016):327-340. |
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