An OLCI-based algorithm for semi-empirically partitioning absorption coefficient and estimating chlorophyll a concentration in various turbid case-2 waters

	An OLCI-based algorithm for semi-empirically partitioning absorption coefficient and estimating chlorophyll a concentration in various turbid case-2 waters
	Liu, Ge; Li, Lin; Song, Kaishan; Li, Yunmei; Lyu, Heng; Wen, Zhidan; Fang, Chong; Bi, Shun; Sun, Xiaoping; Wang, Zongming
刊名	REMOTE SENSING OF ENVIRONMENT
	2020
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 (R-rs(lambda)) 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 (a(nw)(665)) into phytoplankton absorption (a(ph)(665)) and yellow matter (a(ym)(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 (b(b)(lambda(0))) at QAA reference band (lambda(0)), 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 R-rs(lambda) and OLCI match-up R-rs(lambda) 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.
内容类型	期刊论文
源URL	[http://159.226.73.51/handle/332005/20085]
专题	中国科学院南京地理与湖泊研究所
推荐引用方式 GB/T 7714	Liu, Ge,Li, Lin,Song, Kaishan,et al. An OLCI-based algorithm for semi-empirically partitioning absorption coefficient and estimating chlorophyll a concentration in various turbid case-2 waters[J]. REMOTE SENSING OF ENVIRONMENT,2020,239.
APA	Liu, Ge.,Li, Lin.,Song, Kaishan.,Li, Yunmei.,Lyu, Heng.,...&Shi, Kun.(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, Ge,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).