气候变化领域集成服务门户(CCPortal): Distinguishing cyanobacteria from algae in optically complex inland waters using a hyperspectral radiative transfer inversion algorithm

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DOI	10.1016/j.rse.2020.111981
	Distinguishing cyanobacteria from algae in optically complex inland waters using a hyperspectral radiative transfer inversion algorithm
	Matthews M.W.; Bernard S.; Evers-King H.; Robertson Lain L.
发表日期	2020
ISSN	00344257
卷号	248
英文摘要	A hyperspectral inversion algorithm was used to distinguish between cyanobacteria and algal blooms in optically complex inland waters. A framework for the algorithm is presented that incorporates a bio-optical model, a solution for the radiative transfer equation using the EcoLight-S radiative transfer model, and a non-linear optimization procedure. The natural variability in the size of phytoplankton populations was simulated using a two-layered sphere model that generated size-specific inherent optical properties (IOPs). The algorithm effectively determined the type of high-biomass blooms in terms of the relative percentage species composition of cyanobacteria. It also provided statistically significant estimates of population size (as estimated by the effective diameter), chlorophyll-a (chl-a) and phycocyanin pigment concentrations, the phytoplankton absorption coefficient, and the non-algal absorption coefficient. The algorithm framework presented here can in principle be adapted for distinguishing between phytoplankton groups using satellite and in situ remotely sensed reflectance. © 2020 Elsevier Inc.
英文关键词	Algorithm; Bio-optics; Cyanobacteria; Harmful algal blooms; Hyperspectral; Remote sensing
语种	英语
scopus关键词	Nonlinear programming; Optical properties; Phytoplankton; Population statistics; Absorption co-efficient; Non-linear optimization; Phytoplankton absorptions; Pigment concentration; Radiative transfer equations; Radiative transfer model; Species composition; Specific inherent optical properties; Radiative transfer; algal bloom; algorithm; cyanobacterium; optical property; phytoplankton; pigment; remote sensing; satellite data; algae; Cyanobacteria
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/179205
作者单位	CyanoLakes (Pty) Ltd, 22 Midwood Avenue, Bergvliet, Cape Town, 7945, South Africa; Council for Scientific and Industrial Research, 15 Lower Hope Street, Rosebank, Cape Town, 7700, South Africa; EUMETSAT, Eumetsat Allee 1, Darmstadt, D-64295, Germany; Department of Oceanography, University of Cape Town, Rondebosch, Cape Town, 7701, South Africa
推荐引用方式 GB/T 7714	Matthews M.W.,Bernard S.,Evers-King H.,et al. Distinguishing cyanobacteria from algae in optically complex inland waters using a hyperspectral radiative transfer inversion algorithm[J],2020,248.
APA	Matthews M.W.,Bernard S.,Evers-King H.,&Robertson Lain L..(2020).Distinguishing cyanobacteria from algae in optically complex inland waters using a hyperspectral radiative transfer inversion algorithm.Remote Sensing of Environment,248.
MLA	Matthews M.W.,et al."Distinguishing cyanobacteria from algae in optically complex inland waters using a hyperspectral radiative transfer inversion algorithm".Remote Sensing of Environment 248(2020).