Mapping water constituents concentrations in estuaries using MERIS full resolution satellite data

David Doxaran, Marcel Babin

Laboratoire d’Océanographie de Villefranche – UMR 7093 CNRS - FRANCE

In collaboration with:

Jean-Marie Froidefond, Patrice Castaing, Aldo SottolichioDepartment of Geology and Oceanography – UMR 5805 CNRS – FRANCE

Samantha Lavender

Sch. of Earth, Ocean and Environmental Sciences – University of Plymouth - UK

Marie Curie European Reintegration Grant

Contract ERG-RSFLUX n° 14905

(08/2005 – 07/2007)« Combining ocean colour remote sensing and numerical modelling to quantify

suspended matter fluxes in coastal waters. An integrated approach. »

Research project co-financed by the Centre National d’Etudes Spatiales(CNES), involving:David Doxaran, Marcel Babin, Hervé Claustre, Joséphine Ras, Maéva Doron andSimon Bélanger

Laboratoire d’Océanographie de Villefranche – UMR 7093 CNRS - FRANCE

In collaboration with:Jean-Marie Froidefond, patrice Castaing, Aldo Sottolichio

Department of Geology and Oceanography – UMR 5805 CNRS – FRANCESamantha Lavender

Sch. of Earth, Ocean and Environmental Sciences – University of Plymouth - UK

Continuation of:

PhD Fellowship:2000 – 2002 (3 years)

« Remote sensing and numerical modelling of sedimentary fluxes in estuarine waters »

David Doxaran

Department of Geology and Oceanography – UMR 5805 CNRS – France

(Sup. Dr. JM Froidefond and Pr. P. Castaing)

Marie Curie postdoctoral Fellowship (FP5, EVK3-CT-2002-50012):2003 – 2005 (2 years)

« Modelling the inherent optical properties of highly turbid waters. Development of new processing techniques for satellite and airborne sensors data »David Doxaran

Sch. of Earth, Ocean and Environmental Sciences – University of Plymouth - UK

(Sup. Dr. S.J. Lavender)

DG céanographie

Objectives

1) To assess the integrity of recent ocean colour quantification algorithms

Atmospheric corrections over (highly) turbid coastal and estuarine waters

Quantification relationships between remote-sensing reflectance (Rrs) ratios and the concentration of coloured water constituents:

. - Suspended Particulate Matter (SPM)

. - Coloured Dissolved Organic Matter (CDOM)

. - Chlorophyll-a pigments (Chla)

2) To develop an operational monitoring system for estuarine/coastal waters

SPM database (tidal/seasonal SPM movements from ins-situ and remote sensing data)

Integration of in-situ and remote-sensing observations (SPM concentrations) into a 3D . sediment transport model: - calibration

- validation - sedimentary flux calculations

Methods

Study area(s): - Gironde estuary (South-West France)- Tamar estuary (South-West UK)

1) Inherent Optical Properties (IOP) measurements

To know the SPM contribution to the Rrs signal in the visible and near-infrared (NIR)

To model the Rrs signal of turbid waters in the NIR and implement atmospheric codes

2) Match-ups between in-situ and remote sensing measurements

To assess the integrity of atmospheric corrections

To assess the integrity of quantification relationships

3) Integration of in-situ and remote sensing measurements into a 3D model

To consider an integrity factor associated to the SPM observations

To apply of an existing integration technique (in-situ and remote sensing data separately)

Inherent Optical Properties

In-situ measurements of absorption (a) and attenuation (c) coefficients

Use of two Wetlabs ac-9 sensors (10 cm and 25 cm path-lengths)

Coverage of the visible spectral domain (total of 15 wavelengths between 400 and 750 nm)

Comparison with Monte Carlo simulationsWetlabs ac-9 instruments

Planned in-situ measurements:

October/November 2005 in several turbid estuarine waters in Europe

Regularly in the Gironde estuary (tidal and seasonal IOP variations)

SPM quantification relationships

SPM concentration (mg.l-1) SPM concentration (mg.l-1)

SPM concentration (mg.l-1) SPM concentration (mg.l-1)

Gironde (Doxaran et al. 2002a, 2002b, 2003)

Tamar (Doxaran et al. 2004, 2005)

Satellite dataUse of MERIS and MODIS Full Resolution data:

MERIS Band (300 m)

Nr.

Band centre

(nm) Potential Applications Planned Applications

MODIS Band (250 m)

Nr.

Band centre

(nm)

1 412.5 CDOM, turbidity CDOM (ratio)

2 442.5 Chla absorption maximum

3 490 Chla, other pigments 3 (500 m) 469

4 510 Turbidity, SPM, red tides

5 560 Chla reference, SPM SPM (ratio 1) 3 (500 m) 555

6 620 SPM

7 665 Chla absorption SPM (ratio 2) 1 645

8 681.25 Chla fluorescence

9 705 Atmospheric correction, red edge

CDOM (ratio)

Chla (ratio difference)

10 753.75 Oxygen absorption reference

11 760 Oxygen absorption R-branch

12 775 Aerosols, vegetation

13 865 Aerosols corrections over ocean

SPM (ratio 1)

SPM (ratio 2)

Chla (ratio difference)

2 858

14 890 Water vapour absorption reference

15 900 Water vapour absorption, vegetation

Atmospheric corrections

Clear water technique – Use of dark(est) pixel to remove aerosol effect

e.g. Miller and McKee RSE (2004)1)

Use of radiative transfer code (e.g. 6S) integrating meteorological data

e.g. Doxaran et al. RSE (2002)2)

MERIS ATBD 2.6 - Case 2 Bright Pixel Atmospheric Correction

Moore et al. IJRS (1999)

Lavender et al. CSR (2005)

3)

SPOT image during low river flowperiod (July 1996), mean tides

SPM concentration (mg/l)

Landsat image during high river flow(March 2000), spring tides

SPM concentration (mg/l)

SPOT image - End of high river flowperiod (May 2001), mean tides

SPM concentration (mg/l)

SPOT image – Begin of low river flow period (July 2001), mean tides

SPM concentration (mg/l)

SPOT image - End long low river flowperiod (August 2001), mean tides

SPM concentration (mg/l)

Marie Curie Fellowship

Application to airborne (CASI) data from the Tamar estuary (UK)

Tidal movements of MTZ

ERG - RSFLUX

Test site:

Gironde estuary

Optical measurementscarried out duringregular field campaigns

Match-ups withsatellite data

Assessment ofatmosphericcorrections

Assessment ofquantification relationships

ERG - RSFLUX

In-situ dataFour (+1) autonomousfixed stations

+

Regularonboardoptical data

=

In situ database

Satellite data

- MERIS (1000 m)

- MERIS (300 m)

- MODIS-AQUA (1000 / 250 / 500 m)

- MODIS-TERRA (1000 / 250 / 500 m)

- ASTER (~25 m)

- Hyperion (~25 m)

First results obtainedusing MODIS-AQUA

data

Integration into a 3D sediment transport model

Model:

SiAM3D- Gironde – Developped by IFREMER (DEL/EC – P. LeHir)

- Adapted to the Gironde estuary (Sottolichio et al. (2000)

Method:Vos, R.J., Brummelhuis, P.J.G. and Gerritsen, H., 2000. Integrated data-modelling approach for suspended sediment transport in a regional scale. Coastal Eng., 41: 177-200.

Minimise differences between SPM concentrations observed and calculated by the model by fitting the model pârameters

Objectives:To calibrate and validate the model

To develop an operational monitoring system for estuarine waters:

- Understand sediment transport processes involved

- Quantify then forecast sedimentary fluxes

- Manage human activities (e.g. dredging) shoreline, harbour constructions

Example of satellite data interation into the SiAM3D-Gironde model

First Conclusions - Plans

MERIS + MODIS FR data = great potential to study estuaries

MERIS = multi-spectral data (ATMc,SPM, CDOM, Chla)

but access and repetitivity?

MODIS = easy access, 2 sensors (2 images / day)

but only 2 bands (SPM)

Investigation of IOPs in turbid waters (measurements + simulations)

Assessment of atmospheric corrections

Processing of numerous MERIS / MODIS images for comparison