Chen, Jun1,2; He, Xianqiang2; Liu, Zhongli1; Xu, Na3; Ma, Lingling4; Xing, Qianguo5
; Hu, Xiuqing3; Pan, Delu2发表期刊REMOTE SENSING OF ENVIRONMENT
ISSN0034-4257
2020-09-01
卷号246页码:22
关键词Ocean colorInherent optical propertiesCross-calibrationMERSI II
DOI10.1016/j.rse.2020.111895
通讯作者Pan, Delu(pandelu@sio.org.cn)
英文摘要Synchronous observations with similar illumination-observation and meteorological conditions are critical components of cross-calibration analysis. This study outlines data quality control criteria for obtaining the stable synchronous data needed for developing and evaluating a cross-calibration algorithm. With image data from the Visible Infrared Imaging Radiometer (VIIRS) and Medium Resolution Spectral Imager II (MERSI II), we developed a cross-calibration algorithm using 35 image pairs of four ocean gyres, and we evaluated the data using 11 image pairs of the global ocean. We found that our new algorithm provided well-calibrated MERSI II reflectance at the top-of-atmosphere. The coefficients of determination (R-2) were greater than 0.89, and the mean absolute percent difference (MAPD) varied from 1.13% to 8.37% in the visible bands, which was significantly superior to an algorithm developed from a data set constrained by existing data quality controls. When the satellite data were preprocessed with the new cross-calibration algorithm, the MERSI II instrument provided inter-mission remote sensing reflectance for the North Pacific Gyre that was consistent with the VIIRS instrument. Furthermore, we derived consistent estimates of remote sensing reflectance and backscattering coefficients (b(b)) from VIIRS and the cross-calibrated MERSI II reflectance data for four typically turbid coastal waters. The VIIRS bb coastal images had special distribution patterns, such as tongue-shaped plumes and mesoscale eddies, which accurately reappeared in the MERSI II images. The inter-mission MAPD values varied from 16%-24% for the coastal waters. This uncertainty level was much lower than the bb data quantified from the original MERSI II data with no cross-calibration. Our results suggest that our data quality control criteria provide good quality synchronous data for cross-calibration analysis. MERSI II could provide good ocean color products for oceanic communications after cross-calibration, even though the radiance calibration for the original MERSI II reflectance data are imperfect.
资助机构National Key R&D Program of China; Shan'xi Key Research and Development Program; Fundamental Research Funds for the Central Universities; Strategic Priority Research Program of the Chinese Academy of Sciences; Bureau of International Co-operation Chinese Academy of Sciences; National Natural Science Foundation of China
收录类别SCI
语种英语
关键词[WOS]RESOLUTION IMAGING SPECTRORADIOMETER; INHERENT OPTICAL-PROPERTIES; ZONE COLOR SCANNER; ATMOSPHERIC CORRECTION; RADIOMETRIC CALIBRATION; SEMIANALYTICAL MODEL; TURBID COASTAL; CHLOROPHYLL-A; SEAWIFS; SEA
研究领域[WOS]Environmental Sciences & Ecology; Remote Sensing; Imaging Science & Photographic Technology
WOS记录号WOS:000537691800035
引用统计被引频次：11[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.cnhttp://ir.yic.ac.cn/handle/133337/28725
专题中科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
中科院海岸带环境过程与生态修复重点实验室
通讯作者Pan, Delu作者单位1.Xi An Jiao Tong Univ, Sch Human Settlements & Civil Engn, Xian 710049, Peoples R China
2.Minist Nat Resources, State Key Lab Satellite Ocean Environm Dynam, Inst Oceanog 2, Hangzhou 310012, Peoples R China
3.China Meteorol Adm, Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China
4.Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Quantitat Remote Sensing Informat Technol, Beijing 100094, Peoples R China
5.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China
推荐引用方式
GB/T 7714Chen, Jun,He, Xianqiang,Liu, Zhongli,et al. An approach to cross-calibrating multi-mission satellite data for the open ocean[J]. REMOTE SENSING OF ENVIRONMENT,2020,246:22.
APAChen, Jun.,He, Xianqiang.,Liu, Zhongli.,Xu, Na.,Ma, Lingling.,...&Pan, Delu.(2020).An approach to cross-calibrating multi-mission satellite data for the open ocean.REMOTE SENSING OF ENVIRONMENT,246,22.
MLAChen, Jun,et al."An approach to cross-calibrating multi-mission satellite data for the open ocean".REMOTE SENSING OF ENVIRONMENT 246(2020):22.
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