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 Sottolichio Department 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 and Simon 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 FRANCE Samantha Lavender Sch. of Earth, Ocean and Environmental Sciences University of Plymouth - UK
Continuation of: D G céanographie 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)
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 simulations Wetlabs 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 Gironde (Doxaran et al. 2002a, 2002b, 2003) SPM concentration (mg.l -1 ) SPM concentration (mg.l -1 ) SPM concentration (mg.l -1 ) SPM concentration (mg.l -1 ) Tamar (Doxaran et al. 2004, 2005)
Satellite data Use of MERIS and MODIS Full Resolution data: MERIS Band (300 m) Nr. Band centre (nm) Potential Applications Planned Applications 1 412.5 CDOM, turbidity CDOM (ratio) 2 442.5 Chla absorption maximum MODIS Band (250 m) Nr. Band centre (nm) 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 10 753.75 11 760 Atmospheric correction, red edge Oxygen absorption reference Oxygen absorption R- branch 12 775 Aerosols, vegetation CDOM (ratio) Chla (ratio difference) SPM (ratio 1) 13 865 Aerosols corrections over ocean SPM (ratio 2) 2 858 Chla (ratio difference) 14 890 Water vapour absorption reference 15 900 Water vapour absorption, vegetation
Atmospheric corrections 1) Clear water technique Use of dark(est) pixel to remove aerosol effect e.g. Miller and McKee RSE (2004) 2) Use of radiative transfer code (e.g. 6S) integrating meteorological data e.g. Doxaran et al. RSE (2002) 3) MERIS ATBD 2.6 - Case 2 Bright Pixel Atmospheric Correction Moore et al. IJRS (1999) Lavender et al. CSR (2005)
SPOT image during low river flow period (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 flow period (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 flow period (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 measurements carried out during regular field campaigns Match-ups with satellite data Assessment of atmospheric corrections Assessment of quantification relationships
ERG - RSFLUX In-situ data Four (+1) autonomous fixed stations + Regular onboard optical 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 obtained using MODIS-AQUA data
Integration into a 3D sediment transport model Model: SiAM3D- Gironde Developped by IFREMER (DEL/EC P. LeHir) Method: - Adapted to the Gironde estuary (Sottolichio et al. (2000) 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