Institutional Repository of Key Laboratory of Coastal Zone Environmental Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences (KLCEP)
| Application of a generalized additive model (GAM) for estimating chlorophyll-a concentration from MODIS data in the Bohai and Yellow Seas, China | |
Wang, Yueqi1; Liu, Dongyan1,2 ; Tang, DanLing3
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| 发表期刊 | INTERNATIONAL JOURNAL OF REMOTE SENSING
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| ISSN | 0143-1161 |
| 2017 | |
| 卷号 | 38期号:3页码:639-661 |
| DOI | 10.1080/01431161.2016.1268733 |
| 英文摘要 | In optically complex waters, it is important to evaluate the accuracy of the standard satellite chlorophyll-a (chl-a) concentration algorithms, and to develop accurate algorithms for monitoring the dynamics of chl-a concentration. In this study, the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite remote-sensing reflectance and concurrent in situ measured chl-a (20102013) were used to evaluate the standard OC3M algorithm (ocean chlorophyll-a three-band algorithm for MODIS) and Graver-Siegel-Maritorena model version 1 (GSM01) algorithm for estimating chl-a concentration in the Bohai and Yellow Seas (BYS). The results showed that the chl-a algorithms of OC3M and GSM01 with global default parameters presented poor performance in the BYS (the mean absolute percentage difference (MAPD) and coefficient of determination (R-2) of OC3M are 222.27% and 0.25, respectively; the MAPD and R-2 of GSM01 are 118.08% and 0.07, respectively). A novel statistical algorithm based on the generalized additive model (GAM) was developed, with the aim of improving the satellite-derived chl-a accuracy. The GAM algorithm was established using the in situ measured chl-a concentration as the output variable, and the MODIS above water remote-sensing reflectance (visible bands at 412, 443, 469, 488, 531, 547, 555, 645, 667, and 678 nm) and bathymetry (water depth) as input variables. The MAPD and R-2 calculated between the GAM and the in situ chl-a concentration are 39.96% and 0.67, respectively. The results suggest that the GAM algorithm can yield a superior performance in deriving chl-a concentrations relative to the standard OC3M and GSM01 algorithms in the BYS. |
| 文章类型 | Article |
| 资助机构 | National Natural Science Foundation of China(41376121) ; Chinese Academy of Sciences(XDA11020405) ; Natural Science Foundation of Shandong Province(JQ201414) |
| 收录类别 | SCI |
| 语种 | 英语 |
| 关键词[WOS] | OCEAN COLOR PRODUCTS ; INHERENT OPTICAL-PROPERTIES ; ATMOSPHERIC CORRECTION ; IMAGING SPECTROMETER ; SUSPENDED-SEDIMENT ; COASTAL WATERS ; CHESAPEAKE BAY ; INFRARED BANDS ; GLOBAL-SCALE ; MERIS |
| 研究领域[WOS] | Remote Sensing ; Imaging Science & Photographic Technology |
| WOS记录号 | WOS:000390870600002 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.yic.ac.cn/handle/133337/19234 |
| 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_海岸带环境过程实验室 |
| 作者单位 | 1.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Key Lab Coastal Zone Environm Proc & Ecol Remedia, Yantai, Shandong, Peoples R China 2.East China Normal Univ, State Key Lab Estuarine & Coastal Res, Shanghai, Peoples R China 3.Chinese Acad Sci, South China Sea Inst Oceanol, State Key Lab Trop Oceanog, Res Ctr Remote Sensing Marine Ecol & Environm, Guangzhou, Guangdong, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Yueqi,Liu, Dongyan,Tang, DanLing. Application of a generalized additive model (GAM) for estimating chlorophyll-a concentration from MODIS data in the Bohai and Yellow Seas, China[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2017,38(3):639-661. |
| APA | Wang, Yueqi,Liu, Dongyan,&Tang, DanLing.(2017).Application of a generalized additive model (GAM) for estimating chlorophyll-a concentration from MODIS data in the Bohai and Yellow Seas, China.INTERNATIONAL JOURNAL OF REMOTE SENSING,38(3),639-661. |
| MLA | Wang, Yueqi,et al."Application of a generalized additive model (GAM) for estimating chlorophyll-a concentration from MODIS data in the Bohai and Yellow Seas, China".INTERNATIONAL JOURNAL OF REMOTE SENSING 38.3(2017):639-661. |
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