Using High-Resolution Airborne Data to Evaluate MERIS Atmospheric Correction and Intra-Pixel Variability in Nearshore Turbid Waters

Morgane Larnicol,Patrick Launeau,Pierre Gernez

doi:10.3390/rs10020274

Abstract

The implementation of accurate atmospheric correction is a prerequisite for satellite observation and water quality monitoring in coastal areas. The potential of the fast-line-of-sight atmospheric analysis of spectral hypercubes (FLAASH) was investigated here for the medium resolution imaging spectrometer (MERIS). As the comparison between discrete field sampling points and macro-scale satellite pixels is subject to spatial biases associated with small-scale spatial patchiness in the turbid and highly dynamic nearshore zone, an alternative approach was proposed here using high spatial resolution (1 m) airborne hyperspectral images as radiometric truthing references. While FLAASH was not optimal for moderately turbid offshore waters (suspended particulate matter (SPM) concentration < 50 g∙m−3), it yields satisfactory results in the 50–1500 g∙m−3 range, where MERIS standard atmospheric correction was subject to significant biases and failures. Due to the significant intra-pixel variability of SPM distribution in highly turbid areas, the acquisition of high resolution airborne images should be considered as a consistent strategy for the validation of medium resolution satellite remote sensing in the spatially heterogeneous and optically diverse nearshore waters.

Highlights

The monitoring of seawater constituents such as suspended particulate matter (SPM) and chlorophyll-a (Chl-a), a proxy of micro-algae, is crucial in estuaries and bays as their spatio-temporal variability is one of the main drivers of the functioning of coastal ecosystems [1]
One prerequisite for the remote sensing of in-water colored constituents is the accurate computation of surface reflectance from the top-of-atmosphere (TOA) satellite acquisition, and the accuracy of satellite observation strongly depends on the atmospheric correction (AC)
The averaged spectrum is typical of mud covered by a biofilm of benthic microalgae with a trough near 675 nm resulting from the red absorption by chlorophyll-a [42]

Summary

Introduction

The monitoring of seawater constituents such as suspended particulate matter (SPM) and chlorophyll-a (Chl-a), a proxy of micro-algae, is crucial in estuaries and bays as their spatio-temporal variability is one of the main drivers of the functioning of coastal ecosystems [1]. SPM concentration can be derived from satellite observation of the water-leaving reflectance, ρw(λ), over a variety of spatio-temporal scales in coastal ecosystems [3,4]. One prerequisite for the remote sensing of in-water colored constituents is the accurate computation of surface reflectance from the top-of-atmosphere (TOA) satellite acquisition, and the accuracy of satellite observation strongly depends on the atmospheric correction (AC). The top-of-atmosphere radiance, LTOA(λ), detected by a satellite sensor is converted into. Where ρTOA(λ) is the TOA reflectance, LTOA(λ) is the radiance measured by the sensor, E0(λ) is the solar spectral irradiance at TOA, and cosθ is the cosine of the sun zenith angle, θ. The water-leaving reflectance, ρw(λ), is derived by solving the so-called radiative transfer equation: ρTOA(λ) = ρr(λ) + ρa(λ) + ρra(λ) + ρg(λ) + t·ρw(λ)

Methods

Results

Conclusion