Remote Estimation of Chlorophyll-a in Inland Waters by a NIR-Red-Based Algorithm: Validation in Asian Lakes
文献类型：期刊论文
| 作者 | Yu, Gongliang1,3; Yang, Wei2; Matsushita, Bunkei3; Li, Renhui1; Oyama, Yoichi3; Fukushima, Takehiko3 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2014-04-01 |
| 卷号 | 6期号:4页码:3492-3510 |
| 关键词 | chlorophyll-a concentration NIR-red algorithms blue-green algorithms Asian lakes accuracy assessment |
| ISSN号 | 2072-4292 |
| 通讯作者 | Yang, W (reprint author), Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China. |
| 中文摘要 | Satellite remote sensing is a highly useful tool for monitoring chlorophyll-a concentration (Chl-a) in water bodies. Remote sensing algorithms based on near-infrared-red (NIR-red) wavelengths have demonstrated great potential for retrieving Chl-a in inland waters. This study tested the performance of a recently developed NIR-red based algorithm, SAMO-LUT (Semi-Analytical Model Optimizing and Look-Up Tables), using an extensive dataset collected from five Asian lakes. Results demonstrated that Chl-a retrieved by the SAMO-LUT algorithm was strongly correlated with measured Chl-a (R-2 = 0.94), and the root-mean-square error (RMSE) and normalized root-mean-square error (NRMS) were 8.9 mg center dot m(-3) and 72.6%, respectively. However, the SAMO-LUT algorithm yielded large errors for sites where Chl-a was less than 10 mg center dot m(-3) (RMSE = 1.8 mg center dot m(-3) and NRMS = 217.9%). This was because differences in water-leaving radiances at the NIR-red wavelengths (i.e., 665 nm, 705 nm and 754 nm) used in the SAMO-LUT were too small due to low concentrations of water constituents. Using a blue-green algorithm (OC4E) instead of the SAMO-LUT for the waters with low constituent concentrations would have reduced the RMSE and NRMS to 1.0 mg center dot m(-3) and 16.0%, respectively. This indicates (1) the NIR-red algorithm does not work well when water constituent concentrations are relatively low; (2) different algorithms should be used in light of water constituent concentration; and thus (3) it is necessary to develop a classification method for selecting the appropriate algorithm. |
| 英文摘要 | Satellite remote sensing is a highly useful tool for monitoring chlorophyll-a concentration (Chl-a) in water bodies. Remote sensing algorithms based on near-infrared-red (NIR-red) wavelengths have demonstrated great potential for retrieving Chl-a in inland waters. This study tested the performance of a recently developed NIR-red based algorithm, SAMO-LUT (Semi-Analytical Model Optimizing and Look-Up Tables), using an extensive dataset collected from five Asian lakes. Results demonstrated that Chl-a retrieved by the SAMO-LUT algorithm was strongly correlated with measured Chl-a (R-2 = 0.94), and the root-mean-square error (RMSE) and normalized root-mean-square error (NRMS) were 8.9 mg center dot m(-3) and 72.6%, respectively. However, the SAMO-LUT algorithm yielded large errors for sites where Chl-a was less than 10 mg center dot m(-3) (RMSE = 1.8 mg center dot m(-3) and NRMS = 217.9%). This was because differences in water-leaving radiances at the NIR-red wavelengths (i.e., 665 nm, 705 nm and 754 nm) used in the SAMO-LUT were too small due to low concentrations of water constituents. Using a blue-green algorithm (OC4E) instead of the SAMO-LUT for the waters with low constituent concentrations would have reduced the RMSE and NRMS to 1.0 mg center dot m(-3) and 16.0%, respectively. This indicates (1) the NIR-red algorithm does not work well when water constituent concentrations are relatively low; (2) different algorithms should be used in light of water constituent concentration; and thus (3) it is necessary to develop a classification method for selecting the appropriate algorithm. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Remote Sensing |
| 研究领域[WOS] | Remote Sensing |
| 关键词[WOS] | TURBID PRODUCTIVE WATERS ; DISSOLVED ORGANIC-MATTER ; SEMIANALYTICAL MODEL ; EUTROPHIC LAKE ; CHINA ; KASUMIGAURA ; DIANCHI ; TAIHU ; COLOR ; CDOM |
| 收录类别 | SCI |
| 资助信息 | National Natural Science Foundation of China [41201423]; Major Science and Technology Program for Water Pollution Control and Treatment [2012ZX07105-004]; MEXT from Japan [25420555, 23404015]; Ministry of the Environment, Japan [S-9-4-(1)]; JSPS RONPAKU (Dissertation PhD) Program |
| 语种 | 英语 |
| WOS记录号 | WOS:000336746900044 |
| 公开日期 | 2014-08-13 |
| 源URL | [http://ir.ihb.ac.cn/handle/342005/20107]  |
| 专题 | 水生生物研究所_藻类生物学及应用研究中心_期刊论文 |
| 作者单位 | 1.Chinese Acad Sci, Inst Hydrobiol, Key Lab Algal Biol, Wuhan 430072, Hubei, Peoples R China 2.Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China 3.Univ Tsukuba, Grad Sch Life & Environm Sci, Tsukuba, Ibaraki 3058572, Japan |
| 推荐引用方式 GB/T 7714 | Yu, Gongliang,Yang, Wei,Matsushita, Bunkei,et al. Remote Estimation of Chlorophyll-a in Inland Waters by a NIR-Red-Based Algorithm: Validation in Asian Lakes[J]. REMOTE SENSING,2014,6(4):3492-3510. |
| APA | Yu, Gongliang,Yang, Wei,Matsushita, Bunkei,Li, Renhui,Oyama, Yoichi,&Fukushima, Takehiko.(2014).Remote Estimation of Chlorophyll-a in Inland Waters by a NIR-Red-Based Algorithm: Validation in Asian Lakes.REMOTE SENSING,6(4),3492-3510. |
| MLA | Yu, Gongliang,et al."Remote Estimation of Chlorophyll-a in Inland Waters by a NIR-Red-Based Algorithm: Validation in Asian Lakes".REMOTE SENSING 6.4(2014):3492-3510. |
入库方式： OAI收割
来源：水生生物研究所
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