Remote Sensing of Secchi Depth in Highly Turbid Lake Waters and Its Application with MERIS Data
文献类型：期刊论文
| 作者 | Liu, Xiaohan1,4; Lee, Zhongping4; Zhang, Yunlin; Lin, Junfang1,5; Shi, Kun; Zhou, Yongqiang; Qin, Boqiang; Sun, Zhaohua2; liux@pml.ac.uk; zhongping.lee@umb.edu |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2019 |
| 卷号 | 11期号:19页码:2226 |
| 关键词 | Secchi disk depth quasi-analytical algorithm remote sensing turbid lake water |
| DOI | 10.3390/rs11192226 |
| 英文摘要 | The Secchi disk depth (Z(SD), m) has been used globally for many decades to represent water clarity and an index of water quality and eutrophication. In recent studies, a new theory and model were developed for Z(SD), which enabled its semi-analytical remote sensing from the measurement of water color. Although excellent performance was reported for measurements in both oceanic and coastal waters, its reliability for highly turbid inland waters is still unknown. In this study, we extend this model and its evaluation to such environments. In particular, because the accuracy of the inherent optical properties (IOPs) derived from remote sensing reflectance (R-rs, sr(-1)) plays a key role in determining the reliability of estimated Z(SD), we first evaluated a few quasi-analytical algorithms (QAA) specifically tuned for turbid inland waters and determined the one (QAA(TI)) that performed the best in such environments. For the absorption coefficient at 443 nm (a(443), m(-1)) ranging from 0.2 to 12.5 m(-1), it is found that the QAA(TI)-derived absorption coefficients agree well with field measurements (r(2) > 0.85, and mean absolute percentage difference (MAPD) smaller than 39%). Furthermore, with QAA(TI)-derived IOPs, the MAPD was less than 25% between the estimated and field-measured Z(SD) (r(2) > 0.67, Z(SD) in a range of 0.1-1.7 m). Furthermore, using matchup data between R-rs from the Medium Resolution Imaging Spectrometer (MERIS) and in-situ Z(SD), a similar performance in the estimation of Z(SD) from remote sensing was obtained (r(2) = 0.73, MAPD = 37%, Z(SD) in a range of 0.1-0.9 m). Based on such performances, we are confident to apply the Z(SD) remote sensing scheme to MERIS measurements to characterize the spatial and temporal variations of Z(SD) in Lake Taihu during the period of 2003-2011. |
| 资助机构 | National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41621002]; Key Research Program of Frontier Sciences of Chinese Academy of Sciences [QYZDB-SSW-DQC016]; Key Program of the Chinese Academy of SciencesChinese Academy of Sciences [ZDRW-ZS-2017-3-4]; Natural Science for Youth Foundation [41807362]; Science and Technology Planning Project of Guangdong Province [2017B010118004] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41621002]; Key Research Program of Frontier Sciences of Chinese Academy of Sciences [QYZDB-SSW-DQC016]; Key Program of the Chinese Academy of SciencesChinese Academy of Sciences [ZDRW-ZS-2017-3-4]; Natural Science for Youth Foundation [41807362]; Science and Technology Planning Project of Guangdong Province [2017B010118004] |
| 源URL | [http://ir.scsio.ac.cn/handle/344004/18215]  |
| 专题 | 南海海洋研究所_热带海洋环境国家重点实验室(LTO) |
| 作者单位 | 1.Univ Massachusetts, Sch Environm, Boston, MA 02125 USA 2.Dalhousie Univ, Dept Oceanog, Halifax, NS B3H 4R2, Canada 3.Chinese Acad Sci, State Key Lab Trop Oceanog, South China Sea Inst Oceanol, Guangzhou 510301, Guangdong, Peoples R China 4.Chinese Acad Sci, Taihu Lab Lake Ecosyst Res, State Key Lab Lake Sci & Environm, Nanjing Inst Geog & Limnol, Nanjing 210008, Peoples R China 5.Plymouth Marine Lab, Plymouth PL1 3DH, Devon, England |
| 推荐引用方式 GB/T 7714 | Liu, Xiaohan,Lee, Zhongping,Zhang, Yunlin,et al. Remote Sensing of Secchi Depth in Highly Turbid Lake Waters and Its Application with MERIS Data[J]. REMOTE SENSING,2019,11(19):2226. |
| APA | Liu, Xiaohan.,Lee, Zhongping.,Zhang, Yunlin.,Lin, Junfang.,Shi, Kun.,...&joeysun@scsio.ac.cn.(2019).Remote Sensing of Secchi Depth in Highly Turbid Lake Waters and Its Application with MERIS Data.REMOTE SENSING,11(19),2226. |
| MLA | Liu, Xiaohan,et al."Remote Sensing of Secchi Depth in Highly Turbid Lake Waters and Its Application with MERIS Data".REMOTE SENSING 11.19(2019):2226. |
入库方式： OAI收割
来源：南海海洋研究所
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。