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题名: Remote Estimation of Chlorophyll-a in Inland Waters by a NIR-Red-Based Algorithm: Validation in Asian Lakes
作者: Yu, Gongliang1, 3; Yang, Wei2; Matsushita, Bunkei3; Li, Renhui1; Oyama, Yoichi3; Fukushima, Takehiko3
通讯作者: Yang, W (reprint author), Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China.
关键词: chlorophyll-a concentration ; NIR-red algorithms ; blue-green algorithms ; Asian lakes ; accuracy assessment
刊名: REMOTE SENSING
发表日期: 2014-04-01
DOI: 10.3390/rs6043492
卷: 6, 期:4, 页:3492-3510
收录类别: SCI
文章类型: Article
部门归属: [Yu, Gongliang; Li, Renhui] Chinese Acad Sci, Inst Hydrobiol, Key Lab Algal Biol, Wuhan 430072, Hubei, Peoples R China; [Yang, Wei] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China; [Yu, Gongliang; Matsushita, Bunkei; Oyama, Yoichi; Fukushima, Takehiko] Univ Tsukuba, Grad Sch Life & Environm Sci, Tsukuba, Ibaraki 3058572, Japan
WOS标题词: Science & Technology ; Technology
资助者: 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
类目[WOS]: Remote Sensing
研究领域[WOS]: Remote Sensing
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.
关键词[WOS]: TURBID PRODUCTIVE WATERS ; DISSOLVED ORGANIC-MATTER ; SEMIANALYTICAL MODEL ; EUTROPHIC LAKE ; CHINA ; KASUMIGAURA ; DIANCHI ; TAIHU ; COLOR ; CDOM
语种: 英语
WOS记录号: WOS:000336746900044
ISSN号: 2072-4292
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.ihb.ac.cn/handle/342005/20107
Appears in Collections:藻类生物学及应用研究中心_期刊论文

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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
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