气候变化领域集成服务门户(CCPortal): An OLCI-based algorithm for semi-empirically partitioning absorption coefficient and estimating chlorophyll a concentration in various turbid case-2 waters

CCPortal

DOI	10.1016/j.rse.2020.111648
	An OLCI-based algorithm for semi-empirically partitioning absorption coefficient and estimating chlorophyll a concentration in various turbid case-2 waters
	Liu G.; Li L.; Song K.; Li Y.; Lyu H.; Wen Z.; Fang C.; Bi S.; Sun X.; Wang Z.; Cao Z.; Shang Y.; Yu G.; Zheng Z.; Huang C.; Xu Y.; Shi K.
发表日期	2020
ISSN	00344257
卷号	239
英文摘要	Accurate remote assessment of phytoplankton chlorophyll-a (Chla) concentration in turbid case-2 waters is a challenge, owing largely to terrestrial substances (such as minerals and humus) that are optically significant but do not co-vary with phytoplankton. Here, we propose an improved Quasi-Analytical Algorithm (QAA) (denoted as TC2) for retrieving Chla concentrations from remote sensing reflectance (Rrs(λ)) which can be applied to Sentinel-3 Ocean and Land Colour Instrument (OLCI) images in turbid case-2 waters. TC2 has two main extensions when compared with QAA. First, TC2 makes an additional assumption to separate the total non-water absorption at 665 nm (anw(665)) into phytoplankton absorption (aph(665)) and yellow matter (aym(665)), which is the sum of colored dissolved matter (CDOM) and detritus. Second, for selecting the position of the near-infrared (NIR) band which is used to estimate the signal of total backscattering coefficient (bb(λ0)) at QAA reference band (λ0), we take into account the assumption that the absorption of pure water should be dominant at this band, as well as the impact of the signal-to-noise ratio (SNR) in the NIR band on the Chla concentration estimating model. When applied to in situ Rrs(λ) and OLCI match-up Rrs(λ) data in this study, TC2 provided more accurate Chla estimation than previous Cha concentration retrieval algorithms for turbid case-2 waters. TC2 has the potential for use as a simple and effective algorithm for monitoring Chla concentrations in the turbid case-2 waters at a global scale from space. © 2020 Elsevier Inc.
英文关键词	Chla concentrations; OLCI; Turbid case-2 waters; Yellow matter
语种	英语
scopus关键词	Backscattering; Chlorophyll; Image enhancement; Infrared devices; Phytoplankton; Remote sensing; Signal to noise ratio; Soils; Backscattering coefficients; Chlorophyll-a concentration; OLCI; Phytoplankton absorptions; Phytoplankton chlorophyll; Quasi-analytical algorithms; Remote-sensing reflectance; Yellow matter; Water absorption; absorption coefficient; algorithm; chlorophyll a; concentration (composition); dissolved matter; partitioning; phytoplankton; remote sensing; signal-to-noise ratio
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179444
作者单位	The Northeast Institute of Geography and Agricultural Ecology, Chinese Academy of Sciences, Changchun, Jilin 130102, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing, Jiangsu 210023, China; Yangzhou Environmental Monitoring Center Station, Yangzhou, Jiangsu 225007, China; Department of Earth Sciences, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, United States; Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, Jiangsu 210008, China; Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei 430072, China; State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, Jiangsu 210029, China
推荐引用方式 GB/T 7714	Liu G.,Li L.,Song K.,et al. An OLCI-based algorithm for semi-empirically partitioning absorption coefficient and estimating chlorophyll a concentration in various turbid case-2 waters[J],2020,239.
APA	Liu G..,Li L..,Song K..,Li Y..,Lyu H..,...&Shi K..(2020).An OLCI-based algorithm for semi-empirically partitioning absorption coefficient and estimating chlorophyll a concentration in various turbid case-2 waters.Remote Sensing of Environment,239.
MLA	Liu G.,et al."An OLCI-based algorithm for semi-empirically partitioning absorption coefficient and estimating chlorophyll a concentration in various turbid case-2 waters".Remote Sensing of Environment 239(2020).