Chen, Jun1,2; Quan, Wenting3; Duan, Hongtao4; Xing, Qianguo5
; Xu, Na6发表期刊IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
ISSN1939-1404
2021
卷号14页码:6596-6607
关键词WaterOptical sensorsAdaptive opticsAbsorptionBackscatterOptical imagingLakesIDASinherent optical propertynatural turbid water
DOI10.1109/JSTARS.2021.3073168
通讯作者Chen, Jun(chenjun@xjtu.edu.cn); Xu, Na(xuna@cma.gov.cn)
英文摘要Being able to accurately estimate inherent optical properties (IOPs) at long time scales is key to comprehending the aquatic biological and biogeochemical responses to long-term global climate change. We employed the near-infrared band and combined it with four "common bands" at visible wavelengths (around 443, 490, 551, and 670 nm) to adjust the IOPs data processing system, IDAS(v2). We applied the IDAS(v2) algorithm further to correct for the residual error in images of turbid waters. We evaluated the performance of the IDAS(v2) algorithm using datasets covering a wide range of natural water types from clear open ocean to turbid coastal and inland waters. Due to the water-leaving signals' sensitivity to the optically significant constituents of highly turbid waters, the near-infrared band was very important for retrieving IOPs from those waters. In our analysis, we found that the IDAS(v2) algorithm provided IOPs data with <28.36% uncertainty for oceanic waters and <37.83% uncertainty for inland waters, which was much more effective than what a quasi-analytical algorithm provided. Moreover, the near-infrared band was better at removing the residual error and partial intermission bias in satellite remote sensing reflectance (R-rs) data because of the strong absorption of pure water. We tested the IDAS(v2) algorithm with numerically simulated and satellite observed data of turbid water. After applying IDAS(v2), the IOPs data were accurately determined from R-rs data contaminated by the residual error. Furthermore, the mean intermission difference between Medium Resolution Spectral Imager 2 and Visible Infrared Imaging Radiometer R-rs data at 443 and 551 nm decreased from 8%-25% to 1%-9%. These results suggest that we can accurately estimate IOPs data for natural waters including naturally clear and turbid waters.
资助机构National Key R&D Program of China; National Natural Science Foundation of China; International Cooperation in Science and Technology Innovation among Governments
收录类别SCI
语种英语
关键词[WOS]DIFFUSE ATTENUATION COEFFICIENT; QUASI-ANALYTICAL ALGORITHM; CHLOROPHYLL-A; ATMOSPHERIC CORRECTION; SEMIANALYTICAL MODEL; COLOR; ABSORPTION; COASTAL; SEA; REFLECTANCE
研究领域[WOS]Engineering; Physical Geography; Remote Sensing; Imaging Science & Photographic Technology
WOS记录号WOS:000673442300018
引用统计
文献类型期刊论文
条目标识符http://ir.yic.ac.cnhttp://ir.yic.ac.cn/handle/133337/29497
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Chen, Jun; Xu, Na作者单位1.Minist Nat Resources, State Key Lab Satellite Ocean Environm Dynam, Inst Oceanog 2, Hangzhou 310012, Peoples R China
2.Xi An Jiao Tong Univ, Sch Human Settlements & Civil Engn, Xian 710049, Peoples R China
3.Meteorol Serv Ctr Agr Remote Sensing & Econ Crop, Xian 71000, Peoples R China
4.Chinese Acad Sci, Key Lab Watershed Geog Sci, Nanjing Inst Geog & Limnol, Nanjing 210008, Peoples R China
5.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China
6.China Meteorol Adm, Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China
推荐引用方式
GB/T 7714Chen, Jun,Quan, Wenting,Duan, Hongtao,et al. An Improved Inherent Optical Properties Data Processing System for Residual Error Correction in Turbid Natural Waters[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2021,14:6596-6607.
APAChen, Jun,Quan, Wenting,Duan, Hongtao,Xing, Qianguo,&Xu, Na.(2021).An Improved Inherent Optical Properties Data Processing System for Residual Error Correction in Turbid Natural Waters.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,14,6596-6607.
MLAChen, Jun,et al."An Improved Inherent Optical Properties Data Processing System for Residual Error Correction in Turbid Natural Waters".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 14(2021):6596-6607.
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