Atmospheric correction of SeaWiFS imagery for turbid coastal and inland waters

Ruddick, Kevin; Ovidio, Fabrice; Rijkeboer, Machteld

doi:10.1364/ao.39.000897

Cited by 526 publications

(314 citation statements)

References 35 publications

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“…Sentinel2 TOA data was processed using the ACOLITE software (http://odnature.naturalsciences.be/remsem/softwareand-data/acolite) to derive the water-leaving radiance. This software proposes two options for the atmospheric correction (AC): (i) the NIR algorithm based on the assumption of spatial homogeneity of the red/NIR ratio for aerosol and marine reflectance (Ruddick et al, 2000;Vanhellemont and Ruddick, 2014) using Sentinel2 spectral bands at 665 and 865 nm, (ii) and the SWIR algorithm based on the assumption of zero waterleaving reflectance in the SWIR, using Sentinel2 spectral bands at 1,610 and 2,190 nm Ruddick, 2015, 2016). ACOLITE establishes a per-tile aerosol type (or epsilon) as the ratio between the Rayleigh corrected reflectance in the two aerosol correction bands, for pixels where the marine reflectance can be assumed to be zero (i.e., where ρ w (665 nm) <0.005, as defined by Vanhellemont and Ruddick, 2014).…”

Section: Atmospheric Correctionmentioning

confidence: 99%

Shellfish Aquaculture from Space: Potential of Sentinel2 to Monitor Tide-Driven Changes in Turbidity, Chlorophyll Concentration and Oyster Physiological Response at the Scale of an Oyster Farm

2017

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The algorithms of Novoa et al. (2017) and Gons et al. (2005) were recalibrated and applied to Sentinel2 data to retrieve suspended particulate matter (SPM) and chlorophyll a (chl a) concentration in the environmentally and economically important intertidal zones. Sentinel2-derived chl a and SPM concentration distributions were analyzed at the scale of an oyster farm over a variety of tidal conditions. Sentinel2 imagery was then coupled with ecophysiological modeling to analyze the influence of tide-driven chl a and SPM dynamics on oyster clearance and chl consumption rates. Within the studied oyster farming site (Bourgneuf Bay along the French Atlantic coast), chl consumption rate mirrored the changes in chl a concentration during neap tides, whereas oyster clearance and chl consumption rates were both negatively impacted by high SPM concentration during spring tides.

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Section: Atmospheric Correctionmentioning

confidence: 99%

Shellfish Aquaculture from Space: Potential of Sentinel2 to Monitor Tide-Driven Changes in Turbidity, Chlorophyll Concentration and Oyster Physiological Response at the Scale of an Oyster Farm

2017

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“…Four atmospheric corrections were tested to determine the most suitable for the moderately turbid waters of the Rhône River plume: (1) the MUMM [37]; (2) the NIR [38]; (3) the SWIR [39,40] and (4) the NIR-SWIR [36] atmospheric correction algorithms. The MUMM atmospheric correction algorithm is based on the spatial homogeneity of the water-leaving radiances and aerosols ratios (α and ε respectively, see Table 1) between two NIR bands (748 and 869 nm for MODIS sensors) [37]. This assumption is expected to be valid only in moderately turbid waters [18,37,41].…”

Section: Satellite Data Processingmentioning

confidence: 99%

“…The MUMM atmospheric correction algorithm is based on the spatial homogeneity of the water-leaving radiances and aerosols ratios (α and ε respectively, see Table 1) between two NIR bands (748 and 869 nm for MODIS sensors) [37]. This assumption is expected to be valid only in moderately turbid waters [18,37,41]. The NIR and SWIR atmospheric correction algorithms estimate the aerosol reflectance using NIR (748 nm and 869 nm) and SWIR (1240 and 2130 nm) MODIS bands respectively ( Table 1), assuming that the water leaving reflectance is negligible at these wavelengths.…”

Section: Satellite Data Processingmentioning

confidence: 99%

“…The water-leaving reflectance was obtained at the VIS0.6 band after correcting SEVIRI data for (1) atmospheric gas absorption; (2) Rayleigh scattering; (3) scattering by aerosols following the processing detailed in [19,20]. This atmospheric correction algorithm uses an approach similar to the MUMM correction [37] with the red (VIS0.6) and NIR (VIS0.8) bands of SEVIRI (called MUMM-S here after, see details in Table 1). [19] showed that this atmospheric correction is only valid for Rrs values lower than 0.02 sr´1 and 0.0038 sr´1 in the two red and NIR bands respectively.…”

Section: Satellite Data Processingmentioning

confidence: 99%

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Potential of High Spatial and Temporal Ocean Color Satellite Data to Study the Dynamics of Suspended Particles in a Micro-Tidal River Plume

et al. 2016

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Ocean color satellite sensors are powerful tools to study and monitor the dynamics of suspended particulate matter (SPM) discharged by rivers in coastal waters. In this study, we test the capabilities of Landsat-8/Operational Land Imager (OLI), AQUA&TERRA/Moderate Resolution Imaging Spectroradiometer (MODIS) and MSG-3/Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensors in terms of spectral, spatial and temporal resolutions to (i) estimate the seawater reflectance signal and then SPM concentrations and (ii) monitor the dynamics of SPM in the Rhône River plume characterized by moderately turbid surface waters in a micro-tidal sea. Consistent remote-sensing reflectance (Rrs) values are retrieved in the red spectral bands of these four satellite sensors (median relative difference less than~16% in turbid waters). By applying a regional algorithm developed from in situ data, these Rrs are used to estimate SPM concentrations in the Rhône river plume. The spatial resolution of OLI provides a detailed mapping of the SPM concentration from the downstream part of the river itself to the plume offshore limits with well defined small-scale turbidity features. Despite the low temporal resolution of OLI, this should allow to better understand the transport of terrestrial particles from rivers to the coastal ocean. These details are partly lost using MODIS coarser resolutions data but SPM concentration estimations are consistent, with an accuracy of about 1 to 3 g¨m´3 in the river mouth and plume for spatial resolutions from 250 m to 1 km. The MODIS temporal resolution (2 images per day) allows to capture the daily to monthly dynamics of the river plume. However, despite its micro-tidal environment, the Rhône River plume shows significant short-term (hourly) variations, mainly controlled by wind and regional circulation, that MODIS temporal resolution failed to capture. On the contrary, the high temporal resolution of SEVIRI makes it a powerful tool to study this hourly river plume dynamics. However, its coarse resolution prevents the monitoring of SPM concentration variations in the river mouth where SPM concentration variability can reach 20 g¨m´3 inside the SEVIRI pixel. Its spatial resolution is nevertheless sufficient to reproduce the plume shape and retrieve SPM concentrations in a valid range, taking into account an underestimation of about 15%-20% based on comparisons with other sensors and in situ data. Finally, the capabilities, advantages and limits of these satellite sensors are discussed in the light of the spatial and temporal resolution improvements provided by the new and future generation

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“…Title: Understanding and managing complex transnational river -sea systems: problems and opportunities in the Danube -Black Sea waters, particle scattering dominates the red spectrum confounding the accurate atmospheric correction of satellite data and the retrieval of phytoplankton absorption and pigment concentrations in these wavelengths (Dekker et al, 1997;Lavender et al, 2005;Ruddick et al, 2000;Morel & Bélanger, 2006).…”

Section: Special Issue Science Of the Total Environmentmentioning

confidence: 99%

Developments in Earth observation for the assessment and monitoring of inland, transitional, coastal and shelf-sea waters

Tyler

Hunter

Spyrakos

et al. 2016

Science of The Total Environment

130

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The Earth's surface waters are a fundamental resource and encompass a broad range of ecosystems that are core to global biogeochemical cycling and food and energy production.Despite this, the Earth's surface waters are impacted by multiple natural and anthropogenic pressures and drivers of environmental change. The complex interaction between physical, chemical and biological processes in surface waters poses significant challenges for in situ monitoring and assessment and often limits our ability to adequately capture the dynamics of aquatic systems and our understanding of their status, functioning and response to pressures. Here we explore the opportunities that Earth observation (EO) has to offer to basin-scale monitoring of water quality over the surface water continuum comprising inland, transition and coastal water bodies, with a particular focus on the Danube and Black Sea region. This review summarises the technological advances in EO and the opportunities that the next generation satellites offer for water quality monitoring. We provide an overview of algorithms for the retrieval of water quality parameters and demonstrate how such models have been used for the assessment and monitoring of inland, transitional, coastal and shelfsea systems. Further, we argue that very few studies have investigated the connectivity between these systems especially in large river-sea systems such as the Danube-Black Sea. Subsequently, we describe current capability in operational processing of archive and near real-time satellite data. We conclude that while the operational use of satellites for the assessment and monitoring of surface waters is still developing for inland and coastal waters and more work is required on the development and validation of remote sensing algorithms for these optically complex waters, the potential that these data streams offer for developing an improved, potentially paradigm-shifting understanding of physical and biogeochemical processes across large scale river-sea continuum including the Danube-Black Sea is considerable.

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Atmospheric correction of SeaWiFS imagery for turbid coastal and inland waters

Cited by 526 publications

References 35 publications

Shellfish Aquaculture from Space: Potential of Sentinel2 to Monitor Tide-Driven Changes in Turbidity, Chlorophyll Concentration and Oyster Physiological Response at the Scale of an Oyster Farm

Shellfish Aquaculture from Space: Potential of Sentinel2 to Monitor Tide-Driven Changes in Turbidity, Chlorophyll Concentration and Oyster Physiological Response at the Scale of an Oyster Farm

Potential of High Spatial and Temporal Ocean Color Satellite Data to Study the Dynamics of Suspended Particles in a Micro-Tidal River Plume

Developments in Earth observation for the assessment and monitoring of inland, transitional, coastal and shelf-sea waters

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