Multivariate DINEOF Reconstruction for Creating Long-Term Cloud-Free Chlorophyll-a Data Records From SeaWiFS and MODIS: A Case Study in Bohai and Yellow Seas, China
Wang, YQ; Gao, ZQ; Liu, DY
发表期刊IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
ISSN1939-1404
2019-05
卷号12期号:5页码:1383-1395
关键词Multisensor data records multivariable data interpolating empirical orthogonal functions (M-DINEOF) reconstruction satellite chlorophyll-a product trend consistency
研究领域Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
DOI10.1109/JSTARS.2019.2908182
产权排序[Wang, Yueqi; Gao, Zhiqiang] Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China; [Liu, Dongyan] East China Normal Univ, State Key Lab Estuarine & Coastal Res, Shanghai 200062, Peoples R China
通讯作者Wang, Yueqi([email protected])
作者部门海岸带信息集成与综合管理实验室
英文摘要A long-term reliable satellite chlorophyll-a (chl-a) data record is essential in understanding the state of ocean biology and quantifying its changes. Creating a long-term data record requires a combination/merger of multiple satellite products into one data record, since the lifetime of any single ocean color sensor is finite. However, because of differences in sensor design, calibration, and retrieval models, apparent cross-mission biases are usually observed between different sensor products. To attain a coherent multisensor chl-a data record, the observed cross-mission biases should be accurately addressed in the data combination/merging schemes. In this study, a multivariable data interpolating empirical orthogonal functions (M-DINEOF) approach was used to create long-term chl-a records by applying the sea-viewing wide field-of-view sensor and moderate resolution imaging spectroradiometer products. Under the assumption that the single-sensor chl-a product is free from spurious temporal artifacts and can be reference time series representing the actual variability of chl-a, the discrepancies of trends derived from different chl-a series were quantitatively evaluated based on statistical t-test and Taylor diagram analyses. Compared with direct concatenation and linear regression methods, the M-DINEOF method more effectively reproduced the main trend patterns observed in reference data series during their overlapped periods. The results highlight the importance of a cross-mission bias correction when combining multisensor satellite data records and suggest that the M-DINEOF reconstruction provides a simple and effective path forward for creating reliable multisensor ocean color records suitable for long-term trend analysis.
文章类型Article
资助机构National Natural Science Foundation of ChinaNational Natural Science Foundation of China [41706134, 41876107] ; NSFC-Shandong [U1706219] ; Aoshan Science and Technology Innovation Program of Qingdao National Laboratory for Marine Science and Technology [2016ASKJ02] ; Strategic Priority Research Program of the Chinese Academy of SciencesChinese Academy of Sciences [XDA11020702] ; basic Special Program of Ministry of Science and Technology [2014FY210600]
收录类别SCI
语种英语
关键词[WOS]SATELLITE OCEAN COLOR ; INTERANNUAL VARIATIONS ; PHYTOPLANKTON BLOOMS ; IN-SITU ; TRENDS ; VARIABILITY ; NORTH ; VIEWS
研究领域[WOS]Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号WOS:000470830400005
引用统计
被引频次:8[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.yic.ac.cn/handle/133337/24944
专题中国科学院海岸带环境过程与生态修复重点实验室_海岸带信息集成与战略规划研究中心
作者单位1.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China;
2.East China Normal Univ, State Key Lab Estuarine & Coastal Res, Shanghai 200062, Peoples R China
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GB/T 7714
Wang, YQ,Gao, ZQ,Liu, DY. Multivariate DINEOF Reconstruction for Creating Long-Term Cloud-Free Chlorophyll-a Data Records From SeaWiFS and MODIS: A Case Study in Bohai and Yellow Seas, China[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2019,12(5):1383-1395.
APA Wang, YQ,Gao, ZQ,&Liu, DY.(2019).Multivariate DINEOF Reconstruction for Creating Long-Term Cloud-Free Chlorophyll-a Data Records From SeaWiFS and MODIS: A Case Study in Bohai and Yellow Seas, China.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,12(5),1383-1395.
MLA Wang, YQ,et al."Multivariate DINEOF Reconstruction for Creating Long-Term Cloud-Free Chlorophyll-a Data Records From SeaWiFS and MODIS: A Case Study in Bohai and Yellow Seas, China".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 12.5(2019):1383-1395.
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