Sentinel-2 and

Sentinel-3

Mission

Overview and

Status

Craig Donlon – Sentinel-3 Mission Scientist and Ferran Gascon – Sentinel-2 QC manager and others @ESA IOCCG-21, Santa Monica, USA 1-3rd March 2016

Overview

– What is Copernicus?

– Sentinel-2 mission and status

– Sentinel-3 mission and status

Sentinel-3A OLCI first light Svalbard: 29 Feb 14:07:45-14:09:45 UTC Bands 4, 6 and 7 (of 21) at 490, 560, 620 nm

Spain and Gibraltar 1 March 10:32:48-10:34:48 UTC

California USA 29 Feb 17:44:54-17:46:54 UTC

What is Copernicus?

6

Space Component

In-Situ Data

Services Component

A European response to global needs

What is Copernicus? – Space in Action for You!

• A source of information for policymakers,

industry, scientists, business and the

public

• A European response to global issues:

• manage the environment;

• understand and to mitigate the

effects of climate change;

• ensure civil security

• A user-driven programme of services for

environment and security

• An integrated Earth Observation system

(combining space-based and in-situ data

with Earth System Models)

Components & Competences

Services Component

Space Component

Overall Programme Coordination

Coordinators: Partners:

Service operators

EMCWF

Mercator Ocean

EEA

JRC

EUSC

EMSA snd

FRONTEX

Industries Private

companies

National Space

Agencies

In-situ data are supporting the Space and Services Components

Copernicus Funding

~€ 3.7 B

(from ESA and EU)

~€ 3 B for space

€ 2.3 B

by ESA

€ 0.8 B

by EU (FP7, GIO and Grant)

~€ 0.7 B

for services

Funding for Development Phase until 2013 (c.e.c.):

Funding for Operational Phase as from 2014 (c.e.c.):

€ 4.3 B for the whole programme

(from EU)

Space Component funding (ESA’s entrusted tasks)

€ 3.1 B

Planned Sentinel Schedule

Etna slopes

sentinel-2

Sentinel-2 Mission Overview

• Spacecraft: 2 operating in twin configuration

• Orbit: Sun-synchronous at 786 km (14+3/10 revs per day), with LTDN 10:30 AM

• MultiSpectral Instrument (MSI): operating in pushbroom principle, filter based optical system

• Spectral bands: 13 (VIS–NIR–SWIR spectral domains)

• Spatial resolution: 10m / 20m / 60m

• Swath: 290 km

Sentinel-2 A/B/C/D

Sentinel-2 Second Generation A/B

Sentinel-2 swath & coverage

SPOT5 60 x 60 km2

IRS P6 LISS III 141x141 km2

Landsat ETM+ 180 x 172 km2

High revisit time (5 days at equator) assured by twin satellite observations performed over a very large swath

Geographical Coverage:

• All land masses 56° S bis 83° N incl. major

islands All EU Islands < 20 km off the coast

• All Mediterranean

• Inland waters and all closed seas

Sentinel-2 290 x 290 km2 !!

Satellite and Instrument

• Filter based push broom imager (280 kg, 1 m3)

• Three mirrors silicon carbide telescope, with dichroic beam splitter

• Focal plane arrays: Si CMOS VNIR detectors, HgCdTe SWIR detectors.

• Onboard wavelet compression (divided by 3)

• Integrated video & compression electronics (state of the art wavelet compression)

• Radiometric resolution 12bits

• Daily generated telemetry: 1.4 TB

• Satellite mass: 1200 kg

• Satellite power consumption: 1250 W

• Hydrazine propulsion system (120 kg - including provision for safe mode, debris avoidance and EOL orbit decrease for faster re-entry)

• Accurate AOCS based on multi-head Star Tracker and fiber optic gyro

• X band mission data distribution (520 Mbits/sec)

• Mission data onboard storage: 2.4 Tbits

Satellite MultiSpectral instrument

• Multispectral Instrument: pushbroom with 13 bands in the VNIR and SWIR

• High spatial resolution: 10m, 20m and 60m;

• Wide field of view: 290 km • Duty cycle: average 17 min/orbit, maximum 32 min/orbit • Lifetime: 7.25 years, extendable to 12 years

Sentinel-2 Mission Highlights

• 2 Satellites in twin formation,

• Sun-synchronous orbit at 786 km (14+3/10 revs/day), with LTDN 10:30 AM

• Revisit: 5 days at equator (with 2 satellites) under same viewing conditions;

Sentinel-2A Launch last night!

June 23rd 2015

Name High-level Description Production Preservation Strategy

Volume

Level-1B Top-of-atmophere radiances in sensor

geometry

Systematic Long-term ˜27 MB (each 25x23km2)

Level-1C Top-of-atmosphere reflectances in cartographic

geometry

Systematic Long-term ˜500 MB (each 100x100km2)

Level-2A Bottom-of-atmosphere reflectances in cartographic

geometry (prototype product)

On user side* (using

Sentinel-2 Toolbox**)

N/A ˜600 MB (each 100x100km2)

Sentinel-2 Products

*: The possibility of a systematic global production of L2A is currently being explored. **: https://sentinel.esa.int/web/sentinel/toolboxes/sentinel-2

Level-1C / Algorithm

Level-0 Level-0 Consolidated Level-1A Level-1B Level-1C

TELEMETRY ANALYSIS

PRELIMINARY QUICK-LOOK AND CLOUD

MASK GENERATION

DECOMPESSION

SWIR PIXELS REARRANGEMENT

RADIOMETRIC CORRECTIONS

- Inv. on-board equalization,- Dark signal correction,- Blind pixels removal,- Cross-talk correction,- Relative response correction,- Defective/no-data correction,- Deconvolution/Denoising,- Binning of 60m bands.

GEOMETRIC VIEWING MODEL REFINEMENT

- Refining of the viewing model using a global set of reference images,- Registration between VNIR and SWIR focal planes (optional).

RESAMPLING

- Geometry interpolation grid computation,- Resampling (B-splines).

CONVERSION TO REFLECTANCES

PREVIEW IMAGE AND MASKS GENERATION

(defective pixels, cloud & land/water)

algorithms developed in cooperation with

S2 assumption on coastal acquisitions 20 km offshore 280 km swath – lots of data.

https://sentinels.copernicus.eu/web/sentinel/missions/sentinel-2/acquisition-plans

Products Qualification On-going

data quality report on-line athttps://sentinels.copernicus.eu/documents/247904/685

211/Sentinel-2+Data+Quality+Report

Absolute geolocation performances (without geometric refinement) measured over 17 test sites.

Measurements in line with requirements.

Level-1 Products Pre-Qualification

Multi-spectral registration performances measured show that the mean circular error over all band couples and detectors is lower than 0.23 pixel of the coarser band.

Level-1 Products Pre-Qualification

Signal-to-Noise Ratio (SNR) calculated from images of the MSI sun diffuser.

Measured SNR values largely exceeding requirements.

Level-1 Products Pre-Qualification

REQUIREMENTS

S2-MPC RESULTS

SNR@Lref Lref SNR Margin

Band/Unit - W/m2/Sr/μm - %

B01 129 129.0 1016,50 688

B02 154 128.0 201,90 31

B03 168 128.0 228,60 36

B04 142 108.0 214,50 51

B05 117 74.5 238,50 104

B06 89 68.0 206,10 132

B07 105 67.0 208,80 99

B08 174 103.0 208,10 20

B8A 72 52.5 153,10 113

B09 114 9.0 164,70 44

San Francisco Bay

Coastal Monitoring

Algae bloom, Baltic Sea

Venice

breakwater

surface effects

boats

Copernicus Sentinel data 2015, RBINS processing

Courtesy K. Ruddick, D. V.d. Zande, RBINS

Coral Reefs Monitoring

London Wind Turbine Array (E. Channel)

(Quinten Vanhellemont & Kevin Ruddick, RBINS)

490nm native 10m resolution Hartog/Dorre Island, West Australia

Sentinel–3 Mission Overview

Optical Mission Payload

providing

Sea and land color data,

through OLCI (Ocean and

Land Color Instrument)

Sea and land surface

temperature, through the

SLSTR (Sea and Land

Surface Temperature

Radiometer)

• Operational mission in high-inclination, low Earth orbit

• Full performance achieved with 2 satellites in orbit (S-3A,-3B)

In addition, the payload design

will allow

Data continuity of the Vegetation

instrument (on SPOT4/5),

Enhanced fire monitoring

capabilities

Topography Mission Payload

providing

Sea surface topography data,

through a Topo P/L including a Ku-/C-

band Synthetic Aperture Radar

Altimeter (SRAL), a bi-frequency

MicroWave Radiometer (MWR), and

a Precise Orbit Determination

(POD) including

GNSS Receiver

DORIS

Laser Retro-Reflector

Sentinel-3a launch from Plesetsk Cosmodrome 16th February 2016

Sentinel-3a launch from Plesetsk Cosmodrome 16th February 2016

(Credit: Antero Isola)

Sentinel-3: Satellite Orbit details

S3B has a 180° phase separation on the same orbital plane

1 Repeat Cycle

(27 days)

2 days

Ground Track Patterns

S3-A S3-B

Instrument Swath Patterns

1400 km SLSTR (nadir)

740 km SLSTR (oblique)

1270 km OLCI

SRAL (>2 km) and MWR (20 km)

nadir track

SRAL tracks at the equator:

S3A = 104 km track separation

S3A+B = 52 km separation

SRAL orbit drivers:

• Ground track repeatability,

• Dense spatial sampling

Orbit control requirement:

• Ground track dead-band ±1km

Orbit type

Repeat cycle

LTDN

Average altitude

Inclination

Repeating frozen SSO

27 days (14 + 7/27 orbits/day)

10:00

815 km

98.65°

Sentinel-3 Optical Coverage (2 satellites with 180° phase separation)

OLCI mean revisit time

with 2 satellites

SLSTR nadir-view mean revisit time

with 2 satellites

0.5

2.0

1.0

0.2

Days

Days

S3 OLCI: Technical details

Basic configuration similar to MERIS:

• 5 Camera Optical Sub Assemblies (COSA),

• 5 Focal Plane Assemblies (FPA),

• 5 Video Acquisition Modules (VAM),

• 1 Scrambling Window Assembly (SWA),

• 1 OLCI Electronic Unit (OEU) managing all the instrument functions,

• 1 calibration assembly allowing radiometric and spectral calibration.

Optical layout

Ocean and Land Colour Imager

Compared to MERIS:

• 100% overlap with SLSTR

• More spectral bands (from 15 to 21): 400-1020 nm

• Broader swath: 1270 km

• Full res. 300m acquired systematically for land & ocean

• Improved characterization, e.g. straylight, camera boundary characterization

• Timeliness: 3 hours NRT Level 2 product

Reduced sun glint by camera tilt in west (12.6°)

MERIS Bands λ center Width

Yellow substanace/detrital pigments

412.5 10

Chl. Abs. Max 442.5 10

Chl & other pigments 490 10

Susp. Sediments, red tide 510 10

Chl. Abs. Min 560 10

Suspended sediment 620 10

Chl. Abs, Chl. fluorescence 665 10

Chl. fluorescence peak 681.25 7.5

Chl. fluorescence ref., Atm. Corr. 708.75 10

Vegetation, clouds 753.75 7.5

O2 R-branch abs. 761.25 2.5

O2 P-branch abs. 778.75 15

Atm corr 865 20

Vegetation, H2O vap. Ref. 885 10

H2O vap., Land 900 10

New OLCI bands λ center Width

Aerosol, in-water property 400 15

Fluorescence retrieval 673.75 7.5

Atmospheric parameter 764.375 3.75

Cloud top pressure 767.5 2.5

Atmos./aerosol correction 940 20

Atmos./aerosol correction 1020 40

Multi-sensor time series

Band Set of OLCI in the Visible and the Near Infra-Red

• Higher spectral resolution than all previous sensors: Important for atmospheric correction, complex coastal waters, phytoplankton types

• Consistency with MERIS: facilitates merging (no need to do band-shifting to establish inter-sensor biases)

(After S. Sathyendranath)

55

5

65

9

86

5

SLSTR

Sentinel-3 OLCI Basic Geometry

1270 km

~09:00 LST ~10:30 LST 10:00 LST

FWHM for Oa21 will not be 40nm but 23nm due to optical transmission and detector response. Note, SNR performance remains compliant with large margins. (SNR EoL prediction: 197 vs Spec: 152)

SRD

CDR

(Pelloquin, C. and J. Nieke. 2012, OLCI and SLSTR simulated spectral response function, S3 Calval WS, Oct-2012)

OLCI Normalized Spectral Response

Functions

Same behavior as for MERIS

https://sentinels.copernicus.eu/web/sentinel/technical-guides/sentinel-3-olci/olci-instrument/spectral-response-function-data

OLCI instrument and camera

test & characterisation sequence

S3A-OLCI NEdL and SNR

0

500

1000

1500

2000

1.E-03

1.E-02

1.E-01

1.E+00

1.E+01

1.E+02

1.E+03

350 450 550 650 750 850 950 1050

SNR[-]

L,NEDL[W.m

-².sr-1.µm

-1]

Wavelength[nm]

Lref

NeDLTypical

SNRtypical

S3A-OLCI* SNR shows excellent consistency of intra-camera (different spectral bands, spectra or full and reduced resolution modes), and inter-camera measurements. A good correlation between the test results and the SNR model was established

*Measurements made prior to swap of cameras in June 2015. We expect similar performance for the Flight Model.

SN

R

OLCI: UV exposure and Hemi-reflectance stability (S3-RP-CSL-OLCI-09035)

OLCI and SLSTR diffuser material

OLCI and SLSTR diffuser material:

• Same material for OLCI and SLSTR flat

panel diffusers

• Zenith Polymer®, an optical PTFE

• Produced by SphereOptics/ElringKlinger AG,

Germany

• Production process according to “Space-

Grade conditions” i.e., cleanness is closely

monitored (e.g., PTFE raw material (powder)

bake out at 24hrs, <1mbar, 95deg)

• Environmental conditions (thermal cycling,

UV exposure, Radiation, ageing) were

verified in a delta-qualification.

• Strict contamination control during AIV.

• All values are within requirements and

within budget. Estimated total duration of sun illumination for OLCI diffusers over mission lifetime

OLCI spectral calibration

3 absorption peaks are proposed for nominal spectral calibration

Erbium-doped

Zenith 8%

« pink diffuser »

40 50 60 70 80 90

100

350 450 550 650 750 850 950 1050 1150 Wavelength (nm)

Refl

ecti

vit

y (

%)

Peak @409 nm

40

50

60

70

80

90

100

400 404 408 412 416 420 Wavelength (nm)

Refl

ecti

vit

y (

%)

Peak @ 522 nm

30 40 50 60 70 80 90

100

515 520 525 530 535 Wavelength (nm)

Refl

ecti

vit

y (

%)

Peak @ 800 nm

30 40 50 60 70 80 90

100

790 795 800 805 810 Wavelength (nm)

Refl

ecti

vit

y (

%)

3 other peaks optional: 490 nm, 658 nm, 975 nm. MERIS absorption bands

Within OLCI a maximum of 3 peaks each with 15 spectral lines can be used.

Better Characterisation than for MERIS

In addition, sample core products will be released to all users as early as possible for familiarisation

today

Core products availability

Data provided to commissioning phase teams

Reference sets of core products released to validation team/ expert users

Level 1 pre-qualified core product release. Gradual ramp-up of operations and progressive release of level 2 pre-qualified core products

ESA & EUMETSAT SHARE OPERATIONS

EU Copernicus Regulation: full, open and free data policy, defining responsibilities for ESA and EUMETSAT and overall financial envelope

Dedicated EU-ESA and EU-EUMETSAT Copernicus agreements

Operational Core Products - full technical documentation at https://sentinel.esa.int

– The operational core products description (including ATBD) is available at:

http://sentinel.esa.int

Open and Free data access policy

https://sentinels.copernicus.eu https://scihub.copernicus.eu/

Sentinel Data – Online Access

– ESA Data Hub Software (DHuS) provides an open source Web Interface

– Users can set scripts to automatically download data

Online data access at: scihub.copernicus.eu

52

Scientific Toolboxes Sentinel 3 Toolbox

Sentinel-3 Toolbox:

• Visualisation & processing of Sentinel-3 OLCI and SLSTR

data and other optical data

• Uncertainty visualization and exploitation

• Remote in-situ database access

• Synergistic use of OLCI and SLSTR

• Various OLCI and SLSTR data processors

http://step.esa.int/

Application Modes

PC, notebook, tablet

I Interactive Exploration

SNAP gpt:_

SNAP Engine

II

PC, notebook server

bulk / NRT processing

cluster, cloud

III EO data

processing centre

SNAP gpt:_

SNAP Engine:_

IV Cloud Exploitation

Platform

PC, notebook, tablet

ESA Sentinel Satellite Smartphone App

Important Dates: Deadline for abstract submission 16 October 2015 Notification of Acceptances End January 2016 Issue of Preliminary Programme February 2016 Opening of Registration February 2016 Release of the Final Programme at the symposium Submission of Full Papers at the symposium

Themes: Atmosphere, Oceanography, Cryosphere, Land, Hazards, Climate and Meteorology, Solid Earth/Geodesy, Near-Earth Environment, Methodologies and Products, Open Science 2.0

http://lps16.esa.int

PRAGUE 09-13 MAY 2016

Main Objective: Presentation of Exploitation Results based on ESA Earth Observation Measurements

Thank You – any Questions

Contact: Craig.Donlon@esa.int

Sentinel-3 Toolbox

• Ingesting Sentinel-3 OLCI and SLSTR

• Ingesting MERIS, AATSR, ATSR, MODIS, SeaWiFS, VIIRS, Proba-V, SPOT-VGT, Landsat TM, etc.

• Basic functions: band maths, statistical analysis, spectrum analysis, geometric tools …

• Uncertainty information exploitation

– OLCI and SLSTR error variables

– Various visualisation modes (blending and overlays)

– Propagation build into band-maths (Standard Combined Uncertainty, GUM 95)

• Remote in-situ database access tool (MERMAID for MERIS/OLCI)

• OLCI / SLSTR / SYN Data Processors

– OLCI/SLSTR collocation tool

– Pixel classification (cloud screening)

– Atmospheric correction and in-water processing (FLH-MCI, C2R, CoastColour, FuB,..)

– SST & LST processing

– Land thematic processing (fAPAR)

• Commissioning phase support tools

– OLCI/SLSTR collocation accuracy assessment (L1C product)

– SLSTR PDU stitching tool

A study to improve the retrieval of water products in extreme scattering and absorbing coastal (and inland) waters, focus on S3 (primarily) and S2

ESA SEOM - Case2 Extreme Waters

?

?

?

?

? ?

?

Problems to be addressed: • Atmospheric correction in turbid

waters

• CHL retrieval in high non-algae

particle as well asd high CDOM

loaded waters

• Identification of water conditions,

and selection of appropriate

algorithm(s) for extreme ranges

of water constituent

concentrations

• Large variability of SIOPs

Relevance/Applications: Water quality, Primary Production and C fixation, sediment transport, dredging +

dumping, organic C from rivers, eutrophication, Rrver engineering

Team:

Approach Radiative transfer simulations, in-situ data from selected extreme water sites

Atmospheric correction

• comparing & improving three different approaches (C2RCC - NN, polymer, NIR/SWIR)

• exploiting new bands of S3 (O-400nm, O-1020nm, SLSTR-SWIR)

• study applicability to S2 MSI

In-water algorithms

• comparing & adapting candidate algorithms (spectrum inversion, semi-analytical, regression)

• exploiting O-400nm band for absorbing waters and O-1020nm band for scattering

Prototyping and validation

• match-ups and decorrelation analysis

• list of demonstration sites, linked to local PIs

• S3 OLCI & SLSTR in 2016

Link with international activities: IOCCG WGs, international science support team, ESA OC CCI, GEO Comm. Practice, …

Duration: April 2015 – March 2017

C2X Project:

Marine Primary Production:

Model Parameters from Space

(MAPPS)

T.Jackson, H.Bouman, S.Sathyendranath, T.Platt, F.Melin

contributors and details available at

www.global-maps.org/data New database on

photosynthesis irradiance

parameters from across the

globe, which will be

published and made

accessible through ESSD.

Inter-model comparison and model

improvement and optimisation

Objective: improve estimates of Marine Primary Production through the production of

remote-sensing data based estimates of phytoplankton photosynthesis-

irradiance parameters.

Global satellite products of photosynthesis-

irradiance parameters

Demonstration products should be available soon

Example of model at SST of 22oC SST CHL PAR

Objective: produce an uncertainty-characterised, inter-sensor bias-corrected, merged time series of ocean-colour products for climate research, and engage with users

V2 of the merged time series (SeaWiFS, MERIS and MODIS-A) released in March 2015.

Specific aims of this version 2.0 release:

• improves the in situ database used for uncertainty characterisation

• optimizes the uncertainty generation for the CCI data

• improves consistency in many areas, including unifying the binning/mapping processing

• improves bias correction, able to respond to temporal variation (primarily seasonal)

• incorporates an improved cloud mask for MERIS

• benefits from a more automated quality assurance process

• extends the time series to the end of 2013

• refreshes the input datasets to the latest versions

Relative error in V2 Chl based on bias. Red vertical line: GCOS requirement for accuracy

May 2010 bias, log_10 Chl

May 2010 RMSD, log_10 Chl

Ocean-Colour Component of ESA’s Climate Change Initiative

OC-CCI: Improved coverage in many under-sampled regions

OC-CCI:Future Plans

• Incorporate VIIRS into the time series

• Extend time series to 2015+

• Prepare for Sentinel-3 • Improve Case-2

products

Acknowledgements ESA and OC-CCI thank the many members of the ocean-colour community who helped in many ways: validation data, participation in user consultation; feedback on products. A special thanks to NASA for their continued help and support.

Match-up in situ observations, per optical class

Bias in log_10 chlorophyll, per optical class

RMSD in log_10 chlorophyll, per optical class

OC-CCI: Improved uncertainty characterisation in V2 compared with V1

800

400

0

Processing step Version 1 Version 2

Input datasets

Latest versions available prior to release in 2013

Latest versions available prior to release in 2015

Atmospheric correction

MERIS: POLYMER V2

MERIS: Improved POLYMER V3

In situ database Initial version Extended version with substantial increase in match-ups with satellite data

Binning

Beam Binner for MERIS; L2Gen for SeaWiFS and MODIS- A

Beam Binner for all sensors, improving consistency in this step

Bias correction Static correction per pixel Improved bias correction; accounts for seasonal variation in bias

Cloud masking

Initial version of Idepix used for MERIS; : L2gen for SeaWiFS and MODIS-A

Improved cloud mask (Idepix 2.0) for MERIS; no change for SeaWiFS and MODIS-A: L2gen

Uncertainty generation

Underlying optical classification based on in situ database on Rrs

Optical classification custom generated for OC-CCI Version 2 satellite data

Uncertainty characterisation

Based on initial optical classification and initial in situ database

Benefited from OC-CCI-data-based optical classification, and improved in situ database

Quality Assurance Initial version, less automated More automated quality assurance process

Time series Sep 1997 to Dec 2012 Sep 1997 to Dec 2013

OC-CCI: Second version released in early 2015

Version 3 scheduled for release imminently

OC-CCI: Work continues

In situ database Match-up validation Uncertainty characterisation

Trends

Data assimilation into ecosystem models

Pools of Carbon in the Ocean Project: Rationale

• At the interface between marine ecosystem and climate models and Earth Observation is the carbon-to-chlorophyll ratio, which is a highly variable quantity.

• In 2010, GEO produced a “Carbon Strategy Report”. In response, the CEOS produced a document on “Carbon from Space” (CEOS, 2014). Both GEO and CEOS Reports highlight the importance of carbon products.

Main focus of POCO: Particulate Pools

• Total Particulate Carbon

• Particulate Organic Carbon

• Phytoplankton Carbon

Bigger pool Smaller pool

Measure-ments more difficult

More data Less data

Objectives • explore the potential of remote sensing for detecting particulate

carbon pools in the ocean • compare with models • focus on climate studies

Scientific Achievements: • Algorithm selection: 10 Carbon

algorithms reviewed and assessed

• In situ database: ~36,000 POC data points assembled

• Model/carbon data interaction: Data assimilation and comparison of MIT model with EO

• Uncertainty quantification: ~3,600 POC match-up points

• Some initial sresults on this slide

Dutckiewitz et al . (2015)

POC (in situ) (mg m-3) PO

C S

tram

ski e

t al

. 20

08

(m

g m

-3)

Nu

mb

er o

f M

atch

-up

s

POC, In Situ Stramski et al. 2008

OC-CCI Chl-a mg m-3 POC Stramski et al. 2008 Behrenfeld et al. 2005 Sathyendranath et al. 2009

Phytoplankton Carbon mg m-3 Phytoplankton Carbon Mg m-3

Website: www.oceancarbon.net Twitter (@ESA_POCO)

Colour and Light in the ocean from Earth Observation (CLEO) workshop

6-8 Sep 2016 ESA /ESRIN Frascati, Italy

The workshop is sponsored through selected SEOM projects, including: • Pools of Carbon in the Ocean • Photosynthetically Active Radiation and

Primary Production • Extreme Case-2 Waters Additional partner projects of ESA are: • Marine Photosynthesis Parameters from

Space • Ocean Colour Climate Change Initiative • Synergistic Exploitation of Hyper-and

Multispectral Sentinel-Measurements to Determine Phytoplankton Functional Types

http://congrexprojects.com/2016-events/cleo Please participate and help make workshop a success