F. Baret, S. Garrigues & J. Morissette · 2008-04-17 · F. Baret, S. Garrigues & J ... WGCV-28...

LAND PRODUCT VALIDATIONSUBGROUP REPORT

F. Baret, S. Garrigues & J. Morissette

WGCV-28 Sanya February 2008

WGCV-28 Sanya February 2008 2/25

OutlineOutline

• accomplishments since last WGCV

• relevance to the CEOS/IP or GEO task

• current/future challenge

• requested agency commitments.

WGCV-28 Sanya February 2008 3/25web curator: Jaime Nickeson, NASA GSFC

LPV web site maintenanceLPV web site maintenance

Thanks to Jaime Nickeson and Jeff Morissette


Previous workshopsPrevious workshops1) 7-8 June 2001 LAI Intercomparison

ESA Frascati, Italy2) 23-24 October 2002 Land Product Validation Workshop on Surface Albedo

Boston MA USA3) 16 August 2004 EOS LAI Intercomparison Activity Results

Missoula, MT USA4) 27-28 October 2005 Global Vegetation Continuous Fields Validation Workshop

Brookings, SD USA5) 27-28 April 2005 LPV workshop on albedo

Vienna, Austria6) 7 August 2006 LPV workshop on long-term VI record

Missoula Montana7) 8-10 August 2006 Long term global monitoring using moderate resolution satellites

Missoula Montana8) 23 March 2007 LPV workshop on LAI and fAPAR products

Davos, Switzerland


LAI validation exercise: refinements and outreachLAI validation exercise:

refinements and outreach

• Discussed during Missoula and Davos meetings• 2 papers published

– Weiss, M., F. Baret, S. Garrigues, R. Lacaze, and P. Bicheron. 2007. LAI, fAPAR and fCover CYCLOPES global products derivedfrom VEGETATION. part 2: Validation and comparison withMODIS Collection 4 products. Remote sensing of Environment, 110:317-331.

– Garrigues, S., R. Lacaze, F. Baret, J. Morisette, M. Weiss, J. Nickeson, R. Fernandes, S. Plummer, N. V. Shabanov, R. Myneni, and W. Yang. 2008. Validation and Intercomparison of Global LeafArea Index Products Derived From Remote Sensing Data. Journal of Geophysical Research, accepted.


Products consideredProducts considered

Clumping representation Product name GSD Temporal

Sampling

Algorithm Parameterization

Plant/Shoot Canopy Landscape

Seasonal smoothing

References

CYCLOPES-V3.1 1/112° 10 days RTM 1D (neural network) Global No No Yes No Baret et al., 2007 ECOCLIMAP 1/120° 1 month Empirical (based on NDVI

variations) Vegetation type Yes Yes No No Masson et al., 2003

GLOBCARBON 1/11.2° 1 month Model derived VI-LAI relationship

Vegetation type Yes Yes No Yes Deng et al., 2006

MODIS-C4 1km 8 days Main Alg: RTM 3D ( LUT) Backup: LAI-NDVI empirical relationship

Vegetation type Yes Yes Yes No Knyazikhin et al., 1998;Myneni et al., 2002

CCRS 1km 10 days Empirical VI-LAI relationship

Vegetation type Yes Yes Up to ~1ha Yes Fernandes et al., 2003

Consider 10x10 km² resolution1 month time step


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GrassCropsEvergreen broadleafEvergreen NeedleleafDeciduous BroadleafBare surface

Intercomparison over CEOS-BELMANIP

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GrassCropsEvergreen broadleafConifersDeciduous BroadleafBare surface

397 sites representing the variability over surface types and latitudes

Baret, F. et al., 2006. Evaluation of the representativeness of networks of sites for the global validation and inter-comparison of land biophysical products. Proposition of the CEOS-BELMANIP. IEEE Transactions on Geoscienceand Remote Sensing, 44(7: special issue on global land product validation): 1794-1803.


IntercomparisonIntercomparison

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Statistical distribution: large differences between products



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10r2=0.51, RMSE=1.04

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Scatterplots: large differences depending on productsand vegetation type



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Africa (25˚ long. East)



Spatial distribution:Differences in valuesBut Similar patternsexcept in specific areas

maps of differences CCRS-Product over Canada



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4SEVI, USA, Lat=34.35, Lon=−106.69

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4Larzac, France, Lat=43.94, Lon=3.12

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4Gourma, Mali, Lat=15.32, Lon=−1.56

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7Nezer, France, Lat=44.57, Lon=−1.05

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7Thompson, Manitoba, Canada, Lat=56.05, Lon=−98.16

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7Flakaliden, sweden, Lat=64.11, Lon=19.47

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7HARV, USA, Lat=42.53, Lon=−72.17

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7Walker Branch, TN, USA, Lat=35.96, Lon=−84.29

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7Larose2, Canada, Lat=45.38, Lon=−75.17

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Temporal distribution: similar patterns (except ecoclimap)But differences in continuity (smoothness, gaps)

Grassland

Needle leafforest

Deciduousforest


Direct validation: Comparison with ground measurements:bottom-up approach

Direct validation: Comparison with ground measurements:bottom-up approach

High spatial resolutionimage (SPOT/TM/ASTER …)

Individual measurements

Value at the ESU level

Value(s) at the site level

Global validation

Averaging

Transferfunction

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50-100 sites

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Direct Validation: resultsDirect Validation: results

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Decid. Broad. For.Ever. Needle. ForestEver. Broad. ForestCropsGrassMixed Forest (DBF+ENF)


SynthesisSynthesis

Criteria CYCLOPES ECOCLIMAP GLOBCARBON MODIS Global distribution + - + + Spatial consistency + - - + Temporal consistency

Missing data - + + - Interannual and

seasonal cycles + - - +

Magnitude of LAI High values - + + + Low values + + + -

Comparison to in-situ data

+ - - -


LAI Validation: conclusionLAI Validation: conclusion• Methods have been developed and published

• Morisette, J., F. Baret, and 28 co-authors. 2006. Validation of global moderate resolution LAI Products: a framework proposed within the CEOS Land Product Validation subgroup. IEEE Transactions on Geoscience and Remote Sensing, 44:1804-1817.

• Baret, F., J. Morissette, and 7 co-authors. 2006. Evaluation of the representativeness of networks of sites for the global validation and inter-comparison of land biophysical products. Proposition of the CEOS-BELMANIP. IEEE Transactions on Geoscience and Remote Sensing, 44:1794-1803.

• Methods have been applied and results published• Weiss, M., F. Baret, S. Garrigues, R. Lacaze, and P. Bicheron. 2007. LAI, fAPAR and

fCover CYCLOPES global products derived from VEGETATION. Part 2: Validation and comparison with MODIS Collection 4 products. Remote sensing of Environment, 110:317-331.

• Garrigues, S., R. Lacaze, F. Baret, J. Morisette, M. Weiss, J. Nickeson, R. Fernandes, S. Plummer, N. V. Shabanov, R. Myneni, and W. Yang. 2008. Validation and Intercomparison of Global Leaf Area Index Products Derived From Remote Sensing Data. Journal of Geophysical Research, accepted

• But…– Need updates with new products versions : on line validation exercise– Small number of validation sites: continuous increase of number of sites (new

sites and inclusion of processed archive sites) to get closer to stage 3 validation– Very little ‘continuous’ ground LAI measurements: PAR@METER devices– Revise BELMANIP: lack of interpixel homogeneity for some sites– Application to other products: fAPAR


Towards the development of virtualconstellation products

Towards the development of virtualconstellation products

• Objectives:– Development of consistent products from several

sensors to allow simple fusion• Framework:

– GEO/CEOS virtual constellation– GEOLAND_2

• Approach:– Evaluate the performances of neural networks when

trained with several inputs and outputs– Application to CYCLOPES/VEGETATION and MODIS


Products usedProducts usedNNT

Reflectance (MOD43B4)

LAI (MOD15A2)

Reflectance (CYCL L3a)

LAI (CYCL V3.1) resampling

spatial sampling 3 kmprojection sinusgeometric accuracy 50-140PSF ? ? ?-temporal sampling 16 8 10 10 16Temporal resolution 16 8 30 30 24-40

Red 620-670 610-680NIR 841-876 780-890SWIR 1628-1652 1580-1750Clumping plant/canopy landscape

1920m50 m 140m

MODIS CYCLOPES

1kmsinus

1/112°lat-lon

Original CYCLOPES (V3.1) and MODIS (collection 4) products

Resampling necessary for better consistency of productsFiltering over the 3x3 pixels: >50% good data

Biophysical algorithm diferences for LAI- MODIS: LUT computed from 3D RT model and tuned for 6 biome classes- CYCLOPES: NNT trained from 1D RT model across all classes


Temporal resolutionTemporal resolution

Differences in temporalresolution betweenMODIS and CYCLOPES


Sites samplingSites sampling

• 397 BELMANIPsites

• 2001-2003 period

• Filtering:– 38112 potential observations– only 7572 matches (20%)– 10% ‘outliers’ eliminated

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Consistency between original productsConsistency between original products

OK for reflectances (biaises between 3 to 7 %)

Large scattering for LAI due to products definitionAssumption on architectureand algorithm principles


Neural network training processNeural network training process

MODrhoMODlai0.502 (0.558)

CYCrhoMODlai0.525 (0.609)

MODIS LAI

MODrhoCYClai0.297 (0.305)

CYCrhoCYClai0.119a (0.129b)

CYCLOPES LAIMODIS reflectancesCYCLOPES reflectances

θs

B2

B3

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NormS

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NIRLAI

Four combinations investigated

aRMSE per vegetation class bRMSE all vegetation classes

Good capacity of neural networks to ‘learn’ any algorithm


Satistical distribution across biomesSatistical distribution across biomes

Good consistency when trained with same LAI but different reflectance sourcePoor consistency between CYCLOPES and MODIS original LAI products values


Results: Temporal profilesResults: Temporal profiles

Products behavior depends mainly on the LAI from which it derives


Direct ValidationDirect Validation


Towards virtual constellation products: CONCLUSION

Towards virtual constellation products: CONCLUSION

• Innovative approach allowing easy fusion of observations coming from several sensors

• Importance of the training data base (LAI)• Applies to any product (even albedo!)• No need for absolute reflectance calibration or strong

spectral consistency between sensors: just temporal and spatial stability!

• Application over instantaneous observations (including or not atmosphere)

• Need good geometrical consistency• First implementation in GEOLAND_2 project (EC) for

Long Time Series (as opposed to Near Real Time)• Results published:

– Verger, A., F. Baret, and M. Weiss. 2008. Efficiency of neural networks for consistent calibration of LAI products from input reflectance coming from several sensors: Application to CYCLOPES/VEGETATION and MODIS data. Remote Sensing of Environment, accepted for publication.


Contribution to GEO TasksContribution to GEO TasksSeveral tasks share same contributions from LPV.

Area Task # Task Title Proposition for potential contribution from LPV LPV achievements Contact ReferencesAgriculture AG-06-04 Forest

Mapping and Change Monitoring

1) Recommendations for Evaluation and Accuracy Assessment of Global Land Cover Maps;

2) Proposition of using biophysical products for change detection.

1) LPV with GOFC-GOLD contributed to this task by encouraging coordinated developments and providing the framework for evaluation of Global Land Cover maps. Documents were written that report methodology and results for the validation of land cover maps.

2) To be discussed and tested

Alan H. Strahler, Philippe Mayaux, LPV chair

1, 2, 3, 4

Agriculture AG-07-01 Improving Measurements of Biomass

1) provide accuracy evaluation of inputs to vegetation productivity models

2) provide recommendations for accuracy assessment of productivity, gross primary production and biomass

1) Biophysical variables such as LAI and fAPAR are key inputs to vegetation productivity models. LPV has been focusing on those variables, by (i) proposing a clear and consensus definition of these variables, (ii) describing departure of available products from the main definition, (iii) developed of a methodological framework for accuracy assessment of products, and (iiii). Results on evaluation of medium spatial resolution LAI products accuracy from ground measurements and intercomparison between available products.

2) Discussions started at Global Vegetation Monitoring meeting (Missoula 2006) and papers published in IEEE TGARS validation special issue.

LPV Chair, Sebastien Garrigues

5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15

16, 17Climate CL-06-02 Key Climate

Data from Satellite Systems

Climate CL-06-03 Key terrestrial observations for Cli tData

ManagementDA-06-02 GEOSS

Quality Assurance Strategy

1) Provide a strategy and methods for quality assessment of land cover (with GOFC-GOLD) fire and biophysical products derived from satellite observations.

2) Maintain easy access to key information for the validation LPV.

3) Organizes meetings to define and discuss the methods and share results with the community.

1) A strategy has been defined for the validation of higher level products: land cover (with GOFC-GOLD) and fire and LAI and fAPAR biophysical products. Results show that stage 2 of the validation is achieved, but stage 3 (quantitative accuracy assessment representative of global conditions) is not yet reached.2) A web site is set up providing information on validation activities. Articles in peer reviewed journal have been published with results based on methods proposed within LPV.3) Workshops have been organized to define and discuss the methods and share results with the community.

LPV chair 2, 6, 7

21, 5, 8,9, 10, 11, 12, 13, 14, 15

21 22 23 18 5Data Management

DA-06-04 Data, Metadata and Products Harmonisation

1) Provide strategy for harmonization of global land cover mapping

2) Provide a strategy for harmonization through intercomparison of homologous biophysical products

1) A strategy for harmonization of global land cover has been defined, allowing intercomparison of classifications and maps.

2) A strategy for intercomparing biophysical products has been proposed. Preliminary results are available for LAI and fAPAR.

Martin HeroldLPV chair

2

5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15Data

ManagementDA-07-02 Global Land

Cover1) Recommendations for Evaluation and Accuracy Assessment of Global Land Cover Maps;

2) Proposition of using biophysical products for change detection.




1, 2, 3, 4

Data Management

DA-07-03 Virtual Constellations

1) Propose a strategy for intercomparison of products derived from several sensors.2) Propose methods for merging products coming from several sensors3) Evaluate benefit of using virtual constellation products4) Define minimum requirements for inter-operability of sensors

1) A strategy for intercomparison of products was proposed with application to biophysical variables (LAI, fAPAR)2) Simple solutions proposed for merging products coming from similar sensors3) Early evaluation for albedo and BRDF products4) Not yet achieved

LPV Chair 5, 6, 7, 8

24, 25

24, 25

Disasters DI-06-09 Use of Satellites for Risk Management

1) Propose a strategy for intercomparison of products derived from several sensors.2) Propose methods for merging products coming from several sensors3) Evaluate benefit of using virtual constellation products4) Define minimum requirements for inter-operability of sensors

1) A strategy for intercomparison of products was proposed with application to biophysical variables (LAI, fAPAR)2) Simple solutions proposed for merging products coming from similar sensors3) Early evaluation for albedo and BRDF products4) Not yet achieved

LPV Chair 5, 6, 7, 8

24, 25

24, 25

Ecosystems EC-06-01 Integrated Global Carbon Observation (IGCO)

1) Provide uncertainties on products used to scale up local observations to region and scale

1) Uncertainties available for few products required in the scaling up process: land cover, albedo, LAI and fAPAR

LPV Chair 21, 5, 8,9, 10, 11, 12, 13, 14, 15

Ecosystems EC-06-02 Ecosystem Classification

1) Propose recommendations for Evaluation and Accuracy Assessment of Global Land Cover Maps;

2) Propose to use biophysical products for change detection.




1, 2, 3, 4

Ecosystems EC-06-07 Regional Networks for Ecos stems

1) Development of validation of products for the monitoring of ecosystems at regional level

1) LPV developed a strategy for validation of land cover and biophysical products. Early results are available for land cover and LAI, fAPAR and albedo

LPV ChairA. StrahlerP. Mayaux

1, 2, 3,4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15

Ecosystems EC-07-01 Global Ecosystem Observation and Monitoring Network

1) Contribute to provide a global classification of ecosystems

2) Contribute to develop a global sampling scheme for ecosystem characterization and monitoring

3) Propose methods to up-scale local ground measurements to larger spatial domains

1) LPV with GOFC-GOLD contributed to this objective by encouraging coordinated development of consistent land cover mapping.2) LPV has proposed a global network of sites that samples vegetation types and conditions. It is based on existing thematic networks such as AERONET or FLUXNET and sites where ground measurements are collected for the direct validation of medium resolution biophysical products. Agencies agreed to provide extracts of medium resolution products they are in charge.3) In the framework of the validation of medium resolution products, up-scaling methods have been developped to extend over larger spatial domains a set of local ground measurements and qualify the spatial sampling used. These methods are based on high spatial resolution images

LPV chair 1, 2, 4

7

6, 26, 9, 10, 11, 12

Weather WE-06-02 Space-based Global Observing System for Weather

1) Provide accuracy statements for Essential Climate Variables (ECVs) as defined in the GCOS Implementation Plan for the terrestrial domain. Emphasis on land cover, Albedo, LAI, fAPAR, Fire and soil moisture products from medium resolution sensors.

2) Propose strategies to exploit in a consistent way historical satellite archive and derive long time series of products.

1) LPV with GOFC-GOLD contributed to validate global land cover maps. Similarly, LPV contributed in the validation of LAI, fAPAR and fire products.

2) LPV proposed strategies to build consistent long time series of biophysical variables

LPV chair 18, 8

20

LPV chair1) Provide accuracy statements for Essential Climate Variables (ECVs) as defined in the GCOS Implementation Plan for the terrestrial domain. Emphasis on land cover, Albedo, LAI, fAPAR, Fire and soil moisture products from medium resolution sensors.

2) Propose strategies to exploit in a consistent way historical satellite archive and derive long time series of products.

1) LPV with GOFC-GOLD contributed to validate global land cover maps. Similarly, LPV contributed in the validation of LAI, fAPAR and fire products.

2) LPV proposed strategies to build consistent long time series of biophysical variables

18, 8

20


Planed activitiesPlaned activities• Future meeting

– Albedo meeting AGU fall 2008– Soil moisture (SMOS) TBD– Temporal signature in remote sensing. January 2010??

• fAPAR products validation• Continue collecting ground validation• Test and exploit PAR@METER devices for

continuous fAPAR/LAI monitoring• Products PSF characterization• On line validation (CALVAL portal)• Populate calval portal (definitions, best practices)


RecommendationsRecommendations• Monitoring progress of previous recommandations

– Recommend agencies to support the continuity and expansion of product validation activities to be able to quantify the associated uncertainties and allow fusion between similar products

– Encourage agencies to prepare subsets of data/products for global product intercomparison activity as described by CEOS/WGCV/LPV

• Need more consistency in geometrical formats (grid/projection/datum)

• Need ressources for implementation of the ‘on linevalidation tool’ in the CAL/VAL portal

F. Baret, S. Garrigues & J. Morissette · 2008-04-17 · F. Baret, S. Garrigues & J ... WGCV-28...

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Transcript of F. Baret, S. Garrigues & J. Morissette · 2008-04-17 · F. Baret, S. Garrigues & J ... WGCV-28...