INFORM project overview and status

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GEO Inland and Coastal Water Quality - Webinar 25.09.2014

http://www.earthobservations.org/webinar_wq.php

INFORM project overview and

status

Ils Reusen, VITO |

[email protected]

Els Knaeps, VITO |

[email protected]

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Improved monitoring and forecasting

of ecological status of European

INland waters

by combining Future earth

ObseRvation data and Models

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Why focus on inland waters?

• Fishing, recreation, water supply, transport, waste disposal, irrigation, … increased pressures on EU inland waters asks for sustainable water management

• Monitoring of inland water quality required by

– EU Water Framework Directive (2000/60/EC) – EU Habitats Directive (92/43/EEC)

– EU Shellfish Waters Directive (2006/113/EC) – EU Drinking Water Directive (98/83/EC)

– EU Bathing Water Directive (2006/7/EC) – EU Nitrates Directive (91/676/EEC) – EU Urban Waste Water

– ...

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Blueprint to Safeguard Europe's

Water Resources (COM/2012/673)

mentions Copernicus

“THE STATUS OF EU WATERS IS NOT DOING WELL ENOUGH! “

“The Water Information System (WISE) … will benefit from the development of INSPIRE, SEIS and Copernicus and from current water research works under

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Copernicus

• Copernicus = The European Earth Observation Programme

• Copernicus services address six main thematic areas:

» Land Monitoring (operational)

» Marine Monitoring (pre-operational phase) » Atmosphere Monitoring (pre-operational phase) » Emergency Management (operational)

» Security (development phase)

» Climate Change (development phase)

• All are provided free of charge to users • http://www.copernicus.eu

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White Paper

Copernicus Inland Water Services

• Discussion document to extend Copernicus Land Monitoring

Service portfolio with inland water services demonstrated in

FP7 Space projects

• Proposed Copernicus inland water services

» Irrigation Water Abstraction Monitoring and Control Service

» Pan-European Inland Water Quality Monitoring Service

» Water scarcity and drought monitoring and forecasting Services » Inland water quantity monitoring service

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Earth Observation for monitoring

inland waters?

• Today: underutilized

– complexity and variability of these inland waters – lack of adequate analysis methods

– lack of adequate low-cost EO data – lack of uncertainty estimates

Report GEO inland and coastal Water Quality Algorithm Workshop, Washington DC, May 2009:

“There is a lack of appropriate/dedicated satellite sensors for nearshore coastal and inland water quality applications”.

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Earth Observation & biogeochemical

models?

Assimilation of EO products into biogeochemical models allows for analysis of the cause-effect relationships governing a status change, forecast the response to pressures and evaluate different management actions.

“the future lies in the combined utilization of in situ data, remote sensing, and modeling.”

Tiffany A.H. Moisan, Shubha Sathyendranath and Heather A. Bouman (2012). Ocean Color Remote Sensing of Phytoplankton Functional Types, Remote Sensing of Biomass - Principles and Applications, Temilola Fatoyinbo (Ed.), ISBN: 978-953-51-0313-4, InTech, Available from: http://www.intechopen.com/books/remote- sensing-of-biomass-principles-and-applications/remote-sensing-of-marine-phytoplankton-biomass

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EU FP7-SPACE project INFORM

•

Collaborative project - THEME [SPA.2013.1.1-07] [Remote

sensing methods]

• Start date: 1/1/2014

• Duration: 48 months

• 9 beneficiaries from 7 EU Member States

• Requested EU contribution: € 1 991 902. 97

• Grant agreement n° 606865

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To develop novel

user-driven

products

for

inland

water quality

monitoring by using new

innovative

methods integrated into models

which fully exploit

the capabilities of

upcoming Earth Observation

missions (Sentinel-2, Sentinel-3, EnMAP and

PRISMA)

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Sentinel-2

• Sentinel-2A launch readiness: 30 April 2015

• Global revisit time: 5 days with 2 satellites

• MSI (Multi Spectral Instrument)

» 13 spectral bands: 443 nm– 2190 nm (including 3 bands

for atmospheric corrections)

» Spectral resolution: 15 nm– 180 nm

» Spatial resolution: 10 m, 20 m and 60 m

» Swath: 290 km

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Sentinel-3

• Sentinel-3A launch readiness: end of 2015

• 2 day global coverage

• OLCI (Ocean and Land Colour Instrument)

» Swath width: 1270 km, with 5 tilted cameras

» Spatial sampling: 300 m (full resolution mode)

» Spectral range: 21 bands [0.4-1.02] μm

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Normalized OLCI SRFs, bands 1 to 21, plotted versus wavelength [nm] from C. Pelloquin, J. Nieke, SENTINEL-3 OLCI AND SLSTR SIMULATED SPECTRAL RESPONSE FUNCTIONS (S3-TN-ESA-PL-316)

OLCI spectral bands = MERIS heritage+additional bands:

Oa1 (400 nm): aerosol correction, improved water constituents retrieval Oa9 (673,75 nm): improved fluorescence retrieval and smile correction Oa14 (764,375 nm): atmospheric correction

Oa15 (767,5 nm): cloud top pressure, fluorescence over land

Oa20 (940 nm): water vapour absorption, atmospheric/aerosol correction Oa21 (1020 nm): atmospheric/aerosol correction

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EnMAP

» Expected launch date: 2017

» Hyperspectral

» Spectral range from 420 nm to 1000 nm (89 VNIR

bands-8.1 nm FWHM) and from 900 nm to 2450 nm

(155 SWIR bands-12.5 nm FWHM)

» Swath width 30 km

» Spatial resolution of 30 m x 30 m

» Off-nadir (30°) pointing feature for fast target revisit (4

days)

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PRISMA

» Expected launch date: 2017

» Hyperspectral

» Spatial resolution: 20-30 m (Hyp) / 2.5-5 m (PAN)

» Swath width: 30-60 km

» Spectral range: 0.4 - 2.5 µm (Hyp) / 0.4 - 0.7 µm (PAN)

» Continuous coverage of spectral ranges with 10 nm

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http://www.apex-esa.org

APEX airborne hyperspectral imaging sensor for

 Simulation

 Calibration

 Validation

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INFORM consortium

Participant organisation

name

Participant short name Country

VLAAMSE INSTELLING VOOR TECHNOLOGISCH ONDERZOEK N.V.

VITO - Coordinator BELGIUM Ils Reusen, Els Knaeps, Sindy Sterckx, Liesbeth De Keukelaere, Dries

Raymaekers, … CONSIGLIO NAZIONALE

DELLE RICERCHE

CNR ITALY Mariano Bresciani, Claudia Giardino, … EOMAP GmbH & Co.KG EOMAP GERMANY Karin Schenk, Philip

Klinger, Thomas Heege, … THE UNIVERSITY OF

STIRLING

U STIRLING UK Peter Hunter, Andrew Tyler, Evangelos Spyrakos …

INSTITUT ROYAL DES SCIENCES NATURELLES DE BELGIQUE

RBINS BELGIUM Dimitry Van der Zande, Kevin Ruddick, … STICHTING DELTARES Deltares THE NETHERLANDS Miguel Dionisio Pires, … PLYMOUTH MARINE

LABORATORY

PML UK Giorgio Dall’Olmo, Steve Groom + Stefan Simis, … MAGYAR TUDOMANYOS

AKADEMIA OKOLOGIAI KUTATOKOZPONT

MTA OK HUNGARY Matyas Presing, …

KLAIPEDOS UNIVERSITETAS

LITHUANIA Arturas Razinkovas-Baziukas, …

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INFORM Steering Advisory Board

(SAB)

• Members

– Dr. Tiit Kutser, Remote Sensing and Marine Optics Department, Estonian Marine Institute, University of Tartu, Estonia

– Dr. Stewart Bernard, CSIR-NRE (Centre of High Performance Computing), South-Africa

– Dr. Vittorio Brando, CNR-IREA

• Tasks

– To provide recommendations at the SAB01 meeting (January 2014)

– To formulate scientific comments on the INFORM progress and to provide recommendations at SAB02 meeting (Mid-term, January 2016)

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INFORM End-User Advisory Board

(EUAB)

• Members

– Marc Sas/Boudewijn Decrop, International Marine and Dredging Consultants (IMDC), Belgium – Marco Bartoli, Expert ecologist, University of Parma, Life Sciences Department

– Ute Menke, advisor Network Water, Rijkswaterstaat, the Netherlands

– István Kóbor head of laboratory, Central-Transdanubian Water Directorate, Hungary

– Geoff Phillips/Bill Brierley, Research, Monitoring and Innovation. Environmental Agency (EA) for England & Wales

– Alfred Johny Wüest, EAWAG, aquatic research institute, Switzerland

– Algirdas Stankevičius, Head of the Marine Research Department of the Ministry of Environment, Lithuania = COPERNICUS USER FORUM member

– Thomas Wolf, Environmental Agency of Baden-Wuerttemberg (LUBW), Germany • Tasks

– To provide user requirements for INFORM developments at the EUAB01 (March 2014) and EUAB02 (Mid-term, January 2016)

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European approach

Site Country Characteristic

Lake Balaton Kis Balaton

Hungary Largest shallow lake in Central Europe, meso-oligotrophic

Water Protection System, hypereutrophic

Curonian lagoon Lithuania Hypereutrophic coastal lagoon

Lakes Mantua Italy Small and shallow artificial eutrophic basins

Lagoon of Venice Italy Turbid coastal lagoon

Lake Constance Germany, Switzerland, Austria

Meso-oligotrophic lake

Gironde river France Highly turbid river

Scheldt river Belgium Highly turbid river

Lake Windermere UK Mesotrophic lake

Loch Lomond UK Warm, monomictic basin. Oligotrophic northern basin, mesotrophic southern basin

Loch Leven UK polymictic, nonstratifying and eutrophic shallow lake

Ijsselmeer The Netherlands Eutrophic lake, largest freshwater lake area in Northwestern Europe Markermeer is a turbid lake.

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INFORM concept (detail)

Properties of upcoming EO sensors (Sentinel-2, Sentinel-3, EnMAP, PRISMA)

 Improved spatialresolution

 Increased spectral coverage to shorter and longer wavelengths

 Improved spectral resolution

New/improved products

 Atttenuation and euphotic depth

 TSM and turbidity

 Yellow matter

 Phytoplanktion functional types

 Stratification

 Macrophytes

 Phytoplankton primary production

 Sun-induced chlorofyll fluorescence

Innovative analysis methods and improved atmospheric correction

Improved modelling

End-users

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WP objectives

• WP1 Management (VITO) – Legal management – Financial management – Administrative management • WP2 Scientific coordination (VITO)

– Scientific coordination of the project

• WP3 End-user interaction (CNR)

– To explore the end-user requirements in terms of water quality products – To stimulate project results’ uptake by the end-users and industry

• WP4 Data gathering (VITO)

– To inventory existing data, identify data gaps

– To acquire new (in-situ, APEX hyperspectral and satellite) data » Development Campaign – 2014

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WP objectives

• WP5 Algorithm development and validation (U STIRLING)

– Development and validation of EO products, and estimation of their uncertainty for WP6

» Atmospheric correction (RBINS)

» Attenuation and euphotic depth (RBINS) » TSM and turbidity (VITO)

» Yellow matter (PML)

» Phytoplankton functional types (CNR) » Stratification (EOMAP)

» Macrophytes (CNR)

» Phytoplankton primary production (U STIRLING) » Sun-induced chlorophyll fluorescence (U STIRLING)

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WP objectives

• WP6 EO-model integration (Deltares)

– Integration of Earth Observation (EO) & In-Situ (IS) data and Water Quality (WQ) modelling

• WP7 Demonstration (EOMAP)

– To demonstrate to end-users

» the INFORM prototype algorithms applied to new satellite sensors and » the added value of INFORM EO products for WQ model validation and

forecasting

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WP objectives

• WP8 Dissemination (VITO)

– To disseminate the project objectives, progress and results – To raise the awareness of the INFORM project

– To give recommendations for future satellite missions – To organise a results uptake workshop

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WP3: End-user interaction

(Leader: CNR)

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Kick-off end-user requirements

• EUAB end-user requirements formulated at the

EUAB01 meeting, 20-21 March 2014, Venice:

– General conclusion: the benefits that harmonized MULTI-TEMPORAL AND

SPATIAL information derived from satellite images can give with respect to

the traditional in-situ monitoring techniques based on point measurements was pointed out as the most important improvement compared to their

current practices.

– In addition following requirements were formulated:

» TEMPORAL AND SPATIAL RESOLUTION: Monthly temporal

frequency of EO data, with a spatial resolution of 100 m.

Exceptions are TSM, Turbidity and Chl-a maps which are required daily.

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» ACCURACY: Associated information about the quality of pixel

values; robust algorithms with reference to literature or algorithm theoretical basis document (ATBD).

» CONSISTENCY: Consistency between products derived from

different sensors; a robust atmospheric correction with reference to literature or ATBD.

» TAXONOMY: A standardized taxonomy (e.g. parameters names,

measurement units, legend, color code) is received as a prerequisite for a harmonized EU-wide inland water quality monitoring.

» ACCESSIBILITY: Easily accessible data and downloadable

preferably by Web Map Service (WMS); training is requested.

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WP4: Data gathering

(Leader: VITO)

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INFORM Development campaign

-Balaton 2014

• Lake Balaton and Kis Balaton wetland (Hungary)

• Data acquisition window: 7-28 July 2014

• In-situ measurements (optical properties and water

constituents) concurrent with satellite (Landsat8-OLI

and HICO) and airborne hyperspectral (APEX)

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GEO Inland and Coastal Water Quality - Webinar 25.09.2014 Balaton Kis Balaton Lake Balaton Marcali Reservoir Balaton Limnological Institute

Balaton

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Surface area 592 km2

Catchment area 5772 km2

Length 78 km

Mean (max) width 9.1 (15) km Mean (max)

depth

3.2 (11) m

Water volume 1861 million m3

Retention time 3-8 years

Shoreline length 235 km

• Largest lake in central Europe

• Very shallow and well-mixed

• High mineral sediment loads

(dolomitic mineralogy)

• Four distinct basins varying from

mesotrophic to eutrophic

• Kis Balaton is hypertrophic

• Historically high nutrient loads but

recent improvements in water quality

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Quicklooks Landsat8-OLI acquisition

INFORM Development campaign

-Balaton 2014

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Quicklooks HICO acquisition

INFORM Development campaign

-Balaton 2014

Collaboration with Evangelos Spyrakos, U

STIRLING

Data available from NRL – The U.S. Naval Research Laboratory OSU – Oregon State

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APEX acquisitions and in-situ measurements

» 2014-07-19

» 2014-07-25

INFORM Development campaign

-Balaton 2014

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INFORM Development campaign

-Balaton 2014

Date

EO Data acquisition In-situ sampling stations

Comments APEX Landsat-8 HICO USTIR CNR VITO ALL

09/07/2014 X X 3 3

14/07/2014 3 3

15/07/2014

4 4 4 12 Instrument inter-comparison + reference ground targets

16/07/2014 X 4 5 (+3 KB) 4 16 + 6 Kis Balaton macrophyte measurements

17/07/2014 X 4 2 2 8 APEX flights aborted

18/07/2014

X 4 4 (+2 KB) 10 + 3 Kis Balaton macrophyte measurements + reference ground targets

19/07/2014

X 11 11 Water samples taken at 7 stations. Underway transects with radiometers

21/07/2014 X 5 5

24/07/2014 5 5

25/07/2014 X X 6 6

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In-situ optics

• U STIRLING

» Wetlabs AC-S: (size fractioned) spectral absorption and attenuation » Wetlabs Eco-BB3: spectral backscattering

» CTD: temperature, salinity, depth

» Trio Satlantic HYPEROCRs: subsurface irradiance reflectance

» Trio Satlanctic HyperSAS and trio TriOS RAMSES: downwelling irradiance, skylight irradiance, total surface radiance for water-leaving reflectance » (in lab) TriOS OSCAR PSICAM: spectral absorption

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In-situ optics

• CNR

» Wetlabs AC-9 and Hobi Labs Hydroscat-6: spectral absorption and attenuation

» Cyclops-6 fluorometers: phytoplankton pigments (Chla, PC, PE), CDOM fluorescence (+temperature and depth)

» ASD FieldSpec FR and WISP-3: subsurface irradiance reflectance and remote sensing reflectance

» ASD FieldSpec FR, Spectrascan, WISP-3: macrophytes reflectance

• VITO

» ASD FieldSpec FR: remote sensing reflectance » WetLabs ECO-BB3: spectral backscattering

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Water sample analysis

• Chla, PC, HPLC (pigments), particulate absorption (PABS) +

flow cytometry

• TSM, CDOM, POC, DOC, phytoplankton cell counts

• Primary production

• Particle size distribution, mycosporine-like amino acids

• Macrophytes: dry weight biomass, pigment and nutrient

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Left: CIMEL CE318 - atmospheric measurements

Middle: ASD FieldSpec FR - water reflectance measurements

Right: Wetlabs AC-S, Wetlabs BB3, Wetlabs AC-9, Hobi Labs Hydroscat, Cyclops-6 fluorometers – intercomparison of IOP measurements

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Left: WetLabs AC-S and ECO-BB3 – absorption and backscatter

Middle: HYPERSAS and RAMSES – downwelling irradiance, skylight radiance, total surface radiance

Right: In-situ campaign leader Peter Hunter with Evangelos Spyrakos (U STIRLING)

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Left: Filtering on the USTIR boat for pigments and particulate absorption. Middle: Filtering in the BLI lab for total suspended matter

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WP5: Algorithms

development and validation

(Leader: U STIRLING)

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Leader: RBINS • Rationale

– Major source of uncertainity for EO products

– AC is very challenging for inland waters due e.g. to altitude, land adjacency and complex aerosols

• Objective

– To develop an atmospheric correction algorithm for Sentinel-2,

Sentinel-3 and EnMAP/PRISMA for inland waters taking TOA radiance data and various auxiliary data as input and providing BOA water

reflectance data as output

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SIMEC adjacency correction Sterckx et al., RSE, in press

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Leader: RBINS • Rationale

– Key input for primary production and other ecological models

– Existing algorithms not suited to inland waters and need adaption to hyperspectral sensors

• Objective

– To develop/adapt algorithms for Sentinel-2, EnMAP/PRISMA and APEX taking water reflectance data as input and providing outputs for spectral and PAR diffuse attenuation coefficients (Kd, KdPAR) and euphotic depth (Ze)

WP 5.2: Light attenuation & euphotic

depth

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Leader: VITO • Rationale

– Key measure of water quality; cal/val of sediment transport and other ecosystem models

– Exploit new sensors, especially SWIR bands for high TSM • Objective

– To develop/adapt algorithms for Sentinel-2, EnMAP/PRISMA and APEX taking water reflectance data as input and providing outputs for total suspended matter (TSM) concentration and turbidity (TUR).

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Varying Total Suspended matter concentration (mg/m3)

0.00 0.01 0.02 0.03 0.04 0.05 0.06 400 500 600 700 800 900 1000 1100 1200 Wavelength (nm) R em ote sensin g reflectance 1 10 100 1000 [Credit: RBINS/VITO]

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Leader: PML • Rationale

– YM = sum of absorption by CDOM and non-algal particles – CDOM linked to DOC

– Major influence on short wavelength light availability

– Expoit new hyperspectral data products, including UV region • Objective

– Develop and validate a UV-visible algorithm for yellow matter absorption that decomposes total absorption into pure water, pigments, and yellow substances

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Figure PML? + explanation

Dutch lakes data set 2003-2005

Yellow matter absorption dominant but rarely isolated in UV-A region -> requires decomposition approach

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Leader: CNR • Rationale

– Relative abundance of PFTs (or size classes) important to ecosystem function

– Some toxic bloom-forming species cyanobacteria pose risks to animal and human health – also driver for WFD

• Objective

– To develop/adapt and validate algorithms for Sentinel-2, EnMAP/PRISMA and APEX taking water reflectance data and IOPs as input and providing outputs of Chla, secondary pigments, and size classes.

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Chl-a

PE PC

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PC in Esthwaite Water (UK) mapped using airborne AISA hyperspectral data

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Leader: EOMAP • Rationale

– Lakes often have pronounced vertical gradients in dissolved and particulate material due to stratification

– Currently, methods provide no information on depth distribution • Objective

– Feasibility study to derive information about vertical gradients of TSM using various satellite sensors.

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GEO Inland and Coastal Water Quality - Webinar 25.09.2014 Shallow view 250m Deep view 500m MODIS 08.08.2012 MODIS 250m channels 640-850 nm MODIS 500m channels 455-850 nm

MODIS 500 m channels “look” deeper than MODIS 250 m due to the incorporation of shorter

wavelengths

Applicable also to other sensors with different band combinations

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Leader: CNR • Rationale

– Macrophytes fulfill important functional roles in lake ecosystems – Biological quality element under EU WFD

– High spatial variability and coexistence of different species require high spatial resolution imagery

• Objective

– To develop/adapt classification approach for mapping different groups of macrophyte (emerged and submerged) and evaluate the biomass and health status by applications dedicated indices to aquatic vegetation

based on specific endmembers collected in the field and wavelet analysis.

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[Credit: CNR-IREA]

Mantua lake system, Water Adjusted Vegetation Index (WAVI) map derived from APEX data for September 2011 (left). Spectral response of different aquatic vegetation types and groups derived from APEX (right). (Villa et al., 2014).

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[Credit: CNR-IREA]

MULTITEMPORAL ASSESSMENT OF MACROPHYTES USING AQUATIC VEGETATION INDICES

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Leader: USTIRLING • Rationale

– C-fixation by phytoplankton is a key contributor to lake ecosystem energetics

– Tightly coupled to meteorology, climate and the catchment – Model developed for ocean waters, but not tested in lakes • Objective

– To develop a prototype model for the estimation of phytoplankton primary production in lakes from EO data.

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Tilstone et al. (2009) Deep Sea Res. 56: 918-930

Empirical

VGPM

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Leader: U STIRLING • Rationale

– Estimation of chlorophyll is problematic in lakes at low concentrations, especially in presence of high CDOM

– Fluorescence signal at 681nm might provide more accurate chlorophyll estimates

– Variability in relationship with chlorophyll related to physiology (photocompensation)

• Objective

– To undertake an evaluation of algorithms for the retrieval of chlorophyll fluorescence and concentration in lakes and explore relations with

phytoplankton physiology

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[Gons et al 2008]

Chlorophyll-a in the Great Lakes derived from SICF peak at 685 nm.

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WP6: EO-model integration

(Leader: Deltares)

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Delft3D: tool for effect chain

analyses

Physical parameters Transports (SPM, ..) Water quality Ecology Fish, Birds

other user functions, etc.

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• Delft3D-FLOW

– Hydrodynamics

• Delft3D-SED

– Suspended particulate matter (SPM)

• Delft3D-WAQ

– Origin of water and residence time

• Delft3D-ECO (BLOOM)

– Nutrients and primary production model

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BLOOM

• BLOOM is a multi-species phytoplankton model

• Competition between phytoplankton types is the guiding

principle in BLOOM

• BLOOM selects the optimum composition based on the

ratio of the net growth rate and the requirements for each

environmental resource

• Trade-off principle between growth and requirement:

– Relatively high potential growth rates may compensate

a relatively large requirement hence opportunistic

species win when light is high, efficient species win

when there is little light

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More information and news

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Thank you

For more information:

http://www.copernicus-inform.eu Contact:

[email protected]

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GEO Inland and Coastal Water Quality - Webinar 25.09.2014 INFORM KO+SAB01 meeting, 23-24 January 2014, VITO, Mol, Belgium INFORM EUAB01 meeting, 20-21 March 2014, CNR, Venice, Italy

http://www.earthobservations.org/webinar_wq.php

Land Monitoring

Marine Monitoring

Atmosphere Monitoring

Emergency Management

Security

Climate Change

http://www.copernicus.eu