气候变化领域集成服务门户(CCPortal): 150 shades of green: Using the full spectrum of remote sensing reflectance to elucidate color shifts in the ocean

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DOI	10.1016/j.rse.2020.111900
	150 shades of green: Using the full spectrum of remote sensing reflectance to elucidate color shifts in the ocean
	Vandermeulen R.A.; Mannino A.; Craig S.E.; Werdell P.J.
发表日期	2020
ISSN	00344257
卷号	247
英文摘要	This article proposes a simple and intuitive classification system by which to define full spectral remote sensing reflectance (Rrs(λ)) data with a quantitative output that enables a more manageable handling of spectral information for aquatic science applications. The weighted harmonic mean of the Rrs(λ) wavelengths outputs an Apparent Visible Wavelength (in units of nanometers), representing a one-dimensional geophysical metric of color that is inherently correlated to spectral shape. This dimensionality reduction of spectral information combined with the output along a continuum of wavelength values offers a robust and user-friendly means to describe and analyze spectral Rrs(λ) in terms of spatial and temporal trends and variability. The uncertainty in the algorithm's estimation of spectral shape is demonstrated on a global scale, in addition to the utility of the algorithm to discern spectral-spatial-temporal trends in the ocean, on a per-pixel basis for the entire 22 year continuous ocean color (SeaWiFS and MODIS-Aqua) time-series. This technique can be applied to datasets of varying multi- and hyper-spectral resolutions, providing continuity between heritage and future satellite sensors, and further enabling an effective means of elucidating similarities or differences in complex spectral signatures within the constraints of two dimensions. This straightforward means of conceptualizing multi-dimensional variability can help maximize the potential of the spectral information embedded in remote sensing data. © 2020 The Author(s)
英文关键词	HICO; MODIS; Ocean color; Optical water types; Remote sensing reflectance; SeaWiFS; Spectral classification; Spectral shape; Spectral-spatial-temporal variability; VIIRS
语种	英语
scopus关键词	Classification (of information); Color; Dimensionality reduction; Reflection; Classification system; Remote sensing data; Remote-sensing reflectance; Spatial and temporal trends; Spectral information; Spectral signature; Visible wavelengths; Weighted harmonic means; Remote sensing; algorithm; ocean color; remote sensing; satellite data; satellite sensor; spectral reflectance; spectral resolution; spectrum; wavelet analysis
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/179261
作者单位	Science Systems and Applications, Inc., Lanham, MD 20706, United States; NASA Goddard Space Flight Center, Greenbelt, MD 20771, United States; University Space Research Association, Columbia, MD 21046, United States
推荐引用方式 GB/T 7714	Vandermeulen R.A.,Mannino A.,Craig S.E.,et al. 150 shades of green: Using the full spectrum of remote sensing reflectance to elucidate color shifts in the ocean[J],2020,247.
APA	Vandermeulen R.A.,Mannino A.,Craig S.E.,&Werdell P.J..(2020).150 shades of green: Using the full spectrum of remote sensing reflectance to elucidate color shifts in the ocean.Remote Sensing of Environment,247.
MLA	Vandermeulen R.A.,et al."150 shades of green: Using the full spectrum of remote sensing reflectance to elucidate color shifts in the ocean".Remote Sensing of Environment 247(2020).