mapping water constituents concentrations in estuaries...
TRANSCRIPT
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