Remote sensing reflectance anomalies in the ocean

被引:12
|
作者
Huot, Yannick [1 ]
Antoine, David [2 ,3 ,4 ]
机构
[1] Univ Sherbrooke, Ctr Applicat & Rech Teledetect, Dept Geomat Appl, Sherbrooke, PQ J1K 2R1, Canada
[2] Curtin Univ, Dept Phys Astron & Med Radiat Sci, Remote Sensing & Satellite Res Grp, GPO Box U1987, Perth, WA 6845, Australia
[3] Univ Paris 06, Sorbonne Univ, F-06238 Villefranche Sur Mer, France
[4] CNRS, Lab Oceanog Villefranche, F-06238 Villefranche Sur Mer, France
基金
加拿大自然科学与工程研究理事会;
关键词
Remote sensing reflectance; Anomalies; Ocean color; Remote sensing; INHERENT OPTICAL-PROPERTIES; PARTICULATE ORGANIC-CARBON; BAND-RATIO ALGORITHMS; CASE-1; WATERS; GLOBAL DISTRIBUTION; CHLOROPHYLL CONCENTRATION; PARTICLE BACKSCATTERING; THEORETICAL DERIVATION; SIZE STRUCTURE; PURE SEAWATER;
D O I
10.1016/j.rse.2016.06.002
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Small spectral differences from the mean remote sensing reflectance (Rrs) of the ocean - anomalies - can provide unique environmental information from ocean color satellite data. First, we describe the average relationship between three input spectral bands and an output band by developing a look-up table (WT) based on the fully normalized Rrs from the MODIS AQUA sensor. By dividing the Rrs measured at the output wavelength by the prediction from the LUT, we obtain several anomalies depending on the combination of input and output bands. None of these anomalies are correlated with chlorophyll concentration on the global scale. Some anomalies are strongly correlated with previously described data products (e.g., CDOM index, backscattering coefficients from semi-analytical inversion models), but others are not correlated with any product currently distributed by NASA. In the latter case, new information about oceanic optical properties is extracted from the ocean color spectra, which allows identification of water masses that was otherwise impossible with standard ocean color products. It was not possible, in some cases, to identify the optical source of this information, which may be spatially and temporally variable. We also show that by removing the main source of variability, the anomalies show interesting potential to identify subtle shifts in sensor response in satellite time series. (C) 2016 Elsevier Inc. All rights reserved.
引用
收藏
页码:101 / 111
页数:11
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