Evaluation of Weighting Average Functions as a Simplification of the Radiative Transfer Simulation in Vertically Inhomogeneous Eutrophic Waters

Current water color remote sensing algorithms typically do not consider the vertical variations of phytoplankton. Ecolight with a radiative transfer program was used to simulate the underwater light field of vertical inhomogeneous waters based on the optical properties of a eutrophic lake (i.e., Lake Chaohu, China). Results showed that the vertical distribution of chlorophyll-a (Chla(z)) can considerably affect spectrum shape and magnitude of apparent optical properties (AOPs), including subsurface remote sensing reflectance in water (rrs(λ, z)) and the diffuse attenuation coefficient (Kx(λ, z)). The vertical variations of Chla(z) changed the spectrum shapes of rrs(λ, z) at the green and red wavelengths with a maximum value at approximately 590 nm, and changed the Kx(λ, z) from blue to red wavelength range with no obvious spectral variation. The difference between rrs(λ, z) at depth z m and its asymptotic value (Δrrs(λ, z)) could reach to ~78% in highly stratified waters. Diffuse attenuation coefficient of downwelling plane irradiance (Kd(λ, z)) had larger vertical variations, especially near water surface, in highly stratified waters. Three weighting average functions performed well in less stratified waters, and the weighting average function proposed by Zaneveld et al., (2005) performed best in highly stratified waters. The total contribution of the first three layers to rrs(λ, 0−) was approximately 90%, but the contribution of each layer in the water column to rrs(λ, 0−) varied with wavelength, vertical distribution of Chla(z) profiles, concentration of suspended particulate inorganic matter (SPIM), and colored dissolved organic matter (CDOM). A simple stratified remote sensing reflectance model considering the vertical distribution of phytoplankton was built based on the contribution of each layer to rrs(λ, 0−).

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Optical properties and retrieving of diffuse attenuation coefficient of the Three Gorges Reservoir by remote sensing

Journal of Lake Sciences ◽

10.18307/2011.0115 ◽

2011 ◽

Vol 23 (1) ◽

pp. 95-103 ◽

Cited By ~ 1

Author(s):

XU Yifan ◽

◽

LI Yunmei ◽

WANG Qiao ◽

LV Heng ◽

...

Keyword(s):

Remote Sensing ◽

Optical Properties ◽

Attenuation Coefficient ◽

Three Gorges Reservoir ◽

Three Gorges ◽

Diffuse Attenuation Coefficient ◽

The Three Gorges Reservoir ◽

The Three Gorges

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Spatio-Temporal Variability in Bio-Optical Properties of the Southern Caspian Sea: A Historic Analysis of Ocean Color Data

Remote Sensing ◽

10.3390/rs12233975 ◽

2020 ◽

Vol 12 (23) ◽

pp. 3975

Author(s):

Bonyad Ahmadi ◽

Mehdi Gholamalifard ◽

Tiit Kutser ◽

Stefano Vignudelli ◽

Andrey Kostianoy

Keyword(s):

Remote Sensing ◽

Optical Properties ◽

Attenuation Coefficient ◽

Temporal Variability ◽

Caspian Sea ◽

Ocean Color ◽

Time Lags ◽

Chl A ◽

Remote Sensing Reflectance ◽

Southern Caspian Sea

Currently, satellite ocean color imageries play an important role in monitoring of water properties in various oceanic, coastal, and inland ecosystems. Although there is a long-time and global archive of such valuable data, no study has comprehensively used these data to assess the changes in the Caspian Sea. Hence, this study assessed the variability of bio-optical properties of the upper-water column in the Southern Caspian Sea (SCS) using the archive of the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) and the Moderate Resolution Imaging Spectroradiometer (MODIS). The images acquired from SeaWiFS (January 1998 to December 2002) and MODIS Aqua (January 2003 to December 2015) satellites were used to investigate the spatial–temporal variability of bio-optical properties including Chlorophyll-a (Chl-a), attenuation coefficient, and remote sensing reflectance, and environmental parameters such as sea surface temperature (SST), wind stress and the El Nino-southern oscillation (ENSO) phenomena at different time lags in the study area. The trend analysis demonstrated an overall increase of 0.3358 mg m−3 in the Chl-a concentration during 1998–2015 (annual increase rate of 0.018 mg m−3 year−1) and four algal blooms and in turn an abnormal increase in Chl-a concentration were occurred in August 2001, September 2005, 2009, and August 2010. The linear model revealed that Chl-a in the northern and middle part of the study area had been influenced by the attenuation coefficient after a one-month lag time. The analysis revealed a sharp decline in Chl-a concentration during 2011–2015 and showed a high correlation with the turbidity and attenuation coefficient in the southern region, while Kd_490nm and remote sensing reflectance did a low one. Generally, Chl-a concentration exhibited a positive correlation with the attenuation coefficient (r = 0.63) and with remote sensing reflectance at the 555 nm (r = 0.111). This study can be used as the basis for predictive modeling to evaluate the changes of water quality and bio-optical indices in the Southern Caspian Sea (SCS).

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Optical properties of Finnish lakes estimated with simple bio-optical models and water quality monitoring data

Hydrology Research ◽

10.2166/nh.2006.0014 ◽

2006 ◽

Vol 37 (2) ◽

pp. 183-204 ◽

Cited By ~ 14

Author(s):

Kari Kallio

Keyword(s):

Remote Sensing ◽

Water Quality ◽

Optical Properties ◽

Chlorophyll A ◽

Attenuation Coefficient ◽

Secchi Depth ◽

Reflectance Spectra ◽

Optical Data ◽

Diffuse Attenuation Coefficient ◽

Sensing Applications

The aim of this study was to estimate the distributions of spectral diffuse attenuation coefficient, attenuation depth and subsurface reflectance of Finnish lakes. In addition, the optimum empirical water quality interpretation algorithms employing reflectance ratios were investigated for the needs of remote sensing. Estimations of the optical properties were based on simple optical models and measured concentrations of optically active substances (the sum of chlorophyll a and phaeophytin a, total suspended solids and coloured dissolved organic matter (CDOM)) at 1670 monitoring stations representing 1113 lakes. The models were parameterized using optical data from 10 lakes. The mean diffuse attenuation coefficient in PAR was 3.5 m−1 and the location of the maximum attenuation depth was in the range 564–714 nm. The simulated reflectance spectra showed a shift of the maximum value to longer wavelengths as trophic status changed from oligotrophic to hyper-eutrophic. High CDOM concentrations decrease the estimation accuracy of chlorophyll a from reflectance spectra using empirical algorithms, particularly in oligotrophic lakes. The models described can be used in studying light availability for photosynthesis at different depths, in the simulation of water temperatures, in estimating how different management alternatives affect light attenuation and Secchi depth, and in various remote sensing applications.

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Water remote sensing reflectance from radiative transfer simulations on a global scale of Inherent Optical Properties

10.5194/essd-2018-5 ◽

2018 ◽

Author(s):

Lena Kritten ◽

Rene Preusker ◽

Carsten Brockmann ◽

Tonio Fincke ◽

Sampsa Koponen ◽

...

Keyword(s):

Remote Sensing ◽

Optical Properties ◽

Radiative Transfer ◽

Spectral Response ◽

Pure Water ◽

Atmospheric Correction ◽

Ocean Colour ◽

Inherent Optical Properties ◽

Remote Sensing Reflectance ◽

Water Constituents

Abstract. The remote-sensing reflectance (Rrs) is in someway an artificial unit, that is constructed in order to contain the spectral colour information of the water body, but to be hardly influenced by the atmosphere above. In ocean colour remotesensing it is the measure to define the optical properties of the water/water constituents. Rrs is the ratio of water-leaving radiance and down-welling irradiance. It is derived from top-of-atmosphere radiance/reflectance measurements through atmospheric correction. A database with Rrs from radiative 5 transfer simulations is capable to serve as a forward model for the retrieval of water constituents. For the present database the Rrs is simulated in dependency of inherent optical properties (IOPs) representing pure water with different salinities and 5 water constituents (Chlorophyll-a-pigment, Detritus, CDOM (coloured dissolved organic matter), a "big" and a "small" scatterer) in a global range of concentrations. The interpolation points for each IOP were chosen in order to reproduce the entire functional relationship between this particular IOP and the corresponding Rrs. The IOPs are varied independently. The data is available for 9 solar, 9 viewing zenith and 25 azimuth angles. The spectral resolution of the data is 1nm, which allows the convolution to any ocean colour sensors’ spectral response function. The data is produced with the radiative transfer code MOMO (Matrix Operator Model), which simulates the full radiative transfer in atmosphere and ocean. The code is hosted at the institute of space sciences at Freie Universität Berlin and is not publicly available. The look-up table (LUT) is available at: doi:10.1594/WDCC/LUT_for_WDC_I (Kritten et al., 2017).

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