Fibre Optic Remote Sensing for In Situ Measurement of Marine Optical Properties

Author(s):  
J. Snow ◽  
I. MacKay ◽  
B. Paton ◽  
A. Herman
2016 ◽  
Vol 119 (16) ◽  
pp. 165305 ◽  
Author(s):  
Brian J. Simonds ◽  
Sudhajit Misra ◽  
Naba Paudel ◽  
Koen Vandewal ◽  
Alberto Salleo ◽  
...  

2020 ◽  
Vol 12 (13) ◽  
pp. 2172 ◽  
Author(s):  
Juliana Tavora ◽  
Emmanuel Boss ◽  
David Doxaran ◽  
Paul Hill

Suspended Particulate Matter (SPM) is a major constituent in coastal waters, involved in processes such as light attenuation, pollutant propagation, and waterways blockage. The spatial distribution of SPM is an indicator of deposition and erosion patterns in estuaries and coastal zones and a necessary input to estimate the material fluxes from the land through rivers to the sea. In-situ methods to estimate SPM provide limited spatial data in comparison to the coverage that can be obtained remotely. Ocean color remote sensing complements field measurements by providing estimates of the spatial distributions of surface SPM concentration in natural waters, with high spatial and temporal resolution. Existing methods to obtain SPM from remote sensing vary between purely empirical ones to those that are based on radiative transfer theory together with empirical inputs regarding the optical properties of SPM. Most algorithms use a single satellite band that is switched to other bands for different ranges of turbidity. The necessity to switch bands is due to the saturation of reflectance as SPM concentration increases. Here we propose a multi-band approach for SPM retrievals that also provides an estimate of uncertainty, where the latter is based on both uncertainties in reflectance and in the assumed optical properties of SPM. The approach proposed is general and can be applied to any ocean color sensor or in-situ radiometer system with red and near-infra-red bands. We apply it to six globally distributed in-situ datasets of spectral water reflectance and SPM measurements over a wide range of SPM concentrations collected in estuaries and coastal environments (the focus regions of our study). Results show good performance for SPM retrieval at all ranges of concentration. As with all algorithms, better performance may be achieved by constraining empirical assumptions to specific environments. To demonstrate the flexibility of the algorithm we apply it to a remote sensing scene from an environment with highly variable sediment concentrations.


2014 ◽  
Vol 119 (6) ◽  
pp. 3093-3106 ◽  
Author(s):  
Aihui Wang ◽  
Michael Barlage ◽  
Xubin Zeng ◽  
Clara Sophie Draper

Author(s):  
Wiwin Ambarwulan ◽  
Widiatmaka ◽  
Syarif Budhiman

The  paper  describes inherent optical properties  (IOP)  of  the  Berau  coastal  waters  derived from in  situ measurements  and Medium  Resolution  Imaging  Spectrometer  (MERIS) satellite  data. Field  measurements  of optical  water,  total  suspended  matter  (TSM), and  chlorophyll-a  (Chl-a) concentrations were carried out during the dry season of 2007. During this periode, only four MERISdata were  coincided with in  situ measurements on 31 August  2007. The MERIS  top-of-atmosphere radiances were atmospherically corrected using the MODTRAN radiative transfer model. The in situ optical  measurement  have  been  processed  into apparent optical properties  (AOP) and sub  surface irradiance. The remote sensing reflectance of in situ measurement as well as MERIS data were inverted into  the  IOP  using quasi-analytical algorithm  (QAA).  The  result  indicated  that coefficient  of determination (R 2) of backscattering coefficients of suspended particles (bbp) increased with increasing wavelength,  however  the  R2 of  absorption  spectra  of  phytoplankton  (aph)  decreased  with  increasing wavelength.


2021 ◽  
Author(s):  
Meloë S. F. Kacenelenbogen ◽  
Qian Tan ◽  
Sharon P. Burton ◽  
Otto P. Hasekamp ◽  
Karl D. Froyd ◽  
...  

Abstract. Improvements in air quality and Earth’s climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine surface network aerosol composition measurements are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (AMTs e.g., clean marine, dust, polluted continental). However, these AMTs are subjectively defined, might often be misclassified and are hard to relate to the critical parameters that need to be refined in models. In this paper, we derive AMTs that are more directly related to sources and hence to speciation. They are defined, characterized, and derived using simultaneous in situ gas-phase, chemical and optical instruments on the same aircraft during the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS, US, summer of 2013). First, we prescribe well-informed AMTs that display distinct aerosol chemical and optical signatures to act as a training AMT dataset. These in situ observations reduce the errors and ambiguities in the selection of the AMT training dataset. We also investigate the relative skill of various combinations of aerosol optical properties to define AMTs and how much these optical properties can capture dominant aerosol speciation. We find distinct optical signatures for biomass burning (from agricultural or wildfires), biogenic and dust-influence AMTs. Useful aerosol optical properties to characterize these signatures are the extinction angstrom exponent (EAE), the single scattering albedo, the difference of single scattering albedo in two wavelengths, the absorption coefficient, the absorption angstrom exponent (AAE), and the real part of the refractive index (RRI). We find that all four AMTs studied when prescribed using mostly airborne in situ gas measurements, can be successfully extracted from at least three combinations of airborne in situ aerosol optical properties (e.g., EAE, AAE and RRI) over the US during SEAC4RS. However, we find that the optically based classifications for BB from agricultural fires and polluted dust include a large percentage of misclassifications that limit the usefulness of results relating to those classes. The technique and results presented in this study are suitable to develop a representative, robust and diverse source-based AMT database. This database could then be used for widespread retrievals of AMTs using existing and future remote sensing suborbital instruments/networks. Ultimately, it has the potential to provide a much broader observational aerosol data set to evaluate chemical transport and air quality models than is currently available by direct in situ measurements. This study illustrates how essential it is to explore existing airborne datasets to bridge chemical and optical signatures of different AMTs, before the implementation of future spaceborne missions (e.g., the next generation of Earth Observing System (EOS) satellites addressing Aerosol, Cloud, Convection and Precipitation (ACCP) designated observables).


2018 ◽  
Vol 10 (10) ◽  
pp. 1655 ◽  
Author(s):  
Nariane Bernardo ◽  
Enner Alcântara ◽  
Fernanda Watanabe ◽  
Thanan Rodrigues ◽  
Alisson Carmo ◽  
...  

The quality control of remote sensing reflectance (Rrs) is a challenging task in remote sensing applications, mainly in the retrieval of accurate in situ measurements carried out in optically complex aquatic systems. One of the main challenges is related to glint effect into the in situ measurements. Our study evaluates four different methods to reduce the glint effect from the Rrs spectra collected in cascade reservoirs with widely differing optical properties. The first (i) method adopts a constant coefficient for skylight correction (ρ) for any geometry viewing of in situ measurements and wind speed lower than 5 m·s−1; (ii) the second uses a look-up-table with variable ρ values accordingly to viewing geometry acquisition and wind speed; (iii) the third method is based on hyperspectral optimization to produce a spectral glint correction, and (iv) computes ρ as a function of wind speed. The glint effect corrected Rrs spectra were assessed using HydroLight simulations. The results showed that using the glint correction with spectral ρ achieved the lowest errors, however, in a Colored Dissolved Organic Matter (CDOM) dominated environment with no remarkable chlorophyll-a concentrations, the best method was the second. Besides, the results with spectral glint correction reduced almost 30% of errors.


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