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VALERI MeetingVALERI Meeting10 March 2005, INRA, Avignon, France10 March 2005, INRA, Avignon, France

A new VALERI validation site in North-Western China:A new VALERI validation site in North-Western China:The ‘Shandan’ grasslandThe ‘Shandan’ grassland

Four years of bilateral cooperation between the People’s Republic of China and the Flemish Community in the Four years of bilateral cooperation between the People’s Republic of China and the Flemish Community in the RESPOM projectRESPOM project

F. VeroustraeteF. Veroustraete22, M.G. Ma, M.G. Ma1, 21, 2, J. Bogaert, J. Bogaert1 ,3, 41 ,3, 4, L. Lu, L. Lu1, 21, 2, X. Li , X. Li 11, T. Che, T. Che11, C.L. Huang, C.L. Huang11, Q.H. Dong, Q.H. Dong22 and R. Ceulemansand R. Ceulemans33

11Cold and Arid Regions Environmental and Engineering Research Institute (CAREERI),Cold and Arid Regions Environmental and Engineering Research Institute (CAREERI), Chinese Academy of Sciences (CAS), China.Chinese Academy of Sciences (CAS), China.

22Vito/TAP, Centre for Remote Sensing and Earth Observation Processes, Belgium.Vito/TAP, Centre for Remote Sensing and Earth Observation Processes, Belgium.33University of Antwerp, Department of Biology, Belgium.University of Antwerp, Department of Biology, Belgium.

44Université Libre de Bruxelles, École Interfacultaire de Bioingénieurs, Belgium.Université Libre de Bruxelles, École Interfacultaire de Bioingénieurs, Belgium.

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ContentsContents

The The project. project. The spatial sampling strategy.The spatial sampling strategy. Shandan site description.Shandan site description. The spatial sampling strategy at Shandan.The spatial sampling strategy at Shandan. Field instrumentsField instruments Results – Field measurements – LAIResults – Field measurements – LAI Results – Field measurements – Gap fractionResults – Field measurements – Gap fraction Results – Field measurements – AlbedoResults – Field measurements – Albedo Results – Up-scaling with Landsat ETM+Results – Up-scaling with Landsat ETM+ Results – Aggregation of ETM+ imagery to 1x1 km²Results – Aggregation of ETM+ imagery to 1x1 km² Results – Validation of the MODIS LAI productResults – Validation of the MODIS LAI product Conclusions.Conclusions.

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The projectThe project

The objectives of the The objectives of the project project

To evaluate the absolute accuracy of biophysical products (LAI, To evaluate the absolute accuracy of biophysical products (LAI, ffAPAR, APAR, ffCover) derived with a range of algorithmsCover) derived with a range of algorithms

from large swath from large swath sensors (e.g. AVHRR, POLDER, sensors (e.g. AVHRR, POLDER, VEGETATION, SEAWIFS, MSG, VEGETATION, SEAWIFS, MSG, MERIS, AATSR, MODIS, MERIS, AATSR, MODIS, MISR,…).MISR,…).

To inter-compare products derived from different sensors and To inter-compare products derived from different sensors and algorithms.algorithms.

  For this purpose, the For this purpose, the project develops: project develops:

A network of sites distributed globally.A network of sites distributed globally.A standard methodology designed to directly measure the A standard methodology designed to directly measure the

biophysical biophysical variables of interest at the proper spatial and variables of interest at the proper spatial and temporal scalestemporal scales.

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1.1. Spatial definition of the sampling strategy.Spatial definition of the sampling strategy.

2.2. Site related georeferenced field measurements of LAI, Albedo and Gap fraction.Site related georeferenced field measurements of LAI, Albedo and Gap fraction.

3.3. Up-scaling of field measurements using high resolution Landsat ETM+ imagery.Up-scaling of field measurements using high resolution Landsat ETM+ imagery.

4.4. Aggregation of high resolution validation fields to large swath sensors resolutionAggregation of high resolution validation fields to large swath sensors resolution (1x1 km²) to validate bio- geophysical products from MODIS (VEGETATION upcoming).o validate bio- geophysical products from MODIS (VEGETATION upcoming).

5.5. Evaluation of bio-geophysical product accuracy over an ensemble of Valeri sites and Evaluation of bio-geophysical product accuracy over an ensemble of Valeri sites and campaign dates available (the future).campaign dates available (the future).

The projectThe project

Specific objectives in RESPOMSpecific objectives in RESPOM

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The project core sitesThe project core sites

Valeri core sites Shandan site MODLAND Core sites

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The spatial sampling strategyThe spatial sampling strategy

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The Shandan siteThe Shandan site

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The Shandan site is located in the footprint of the Qilian Mountains where The Shandan site is located in the footprint of the Qilian Mountains where the Heihe river originates. Due to the fertile soil and appropriate climate, the Heihe river originates. Due to the fertile soil and appropriate climate, this grassland became a high quality horse feedlot for over more than 2000 this grassland became a high quality horse feedlot for over more than 2000 years. The yearly mean precipitation level is approximately 150 mm and years. The yearly mean precipitation level is approximately 150 mm and evaporation is 2531 mm. This area belongs to the semi-arid regions in evaporation is 2531 mm. This area belongs to the semi-arid regions in China.China.

The Shandan site is centered at 38.02 °N, 102.25 °E with an elevation of The Shandan site is centered at 38.02 °N, 102.25 °E with an elevation of 2700 m. The field campaign was executed from July 11th to July 15th, 2002. 2700 m. The field campaign was executed from July 11th to July 15th, 2002. The location of the 38 ESU’s is randomly determined and the ESU’s The location of the 38 ESU’s is randomly determined and the ESU’s localized with GPS.localized with GPS.

The vegetation is characterized by a very homogenous semi-arid grassland The vegetation is characterized by a very homogenous semi-arid grassland with a high fractional cover. with a high fractional cover.

The following data were collected: LAI2000 data (LAI, gap fraction), The following data were collected: LAI2000 data (LAI, gap fraction), albedo, TRAC data, soil temperature and vegetation diversity (species albedo, TRAC data, soil temperature and vegetation diversity (species richness).richness).

Shandan site descriptionShandan site description

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The spatial sampling strategy at ShandanThe spatial sampling strategy at Shandan

37 crosses (ESU’s) 37 crosses (ESU’s) Spatial distribution and Spatial distribution and Representation of each cover classRepresentation of each cover class

Few measurement transectsFew measurement transects

3 km

3 km

Landsat ETM+ false-color RGB of Landsat ETM+ false-color RGB of channels 1, 2, and 3 for the Shandan sitechannels 1, 2, and 3 for the Shandan site

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The spatial sampling strategy at ShandanThe spatial sampling strategy at Shandan

TRACTRAC LAI and AlbedoLAI and Albedo

SiteSite

ESU distributionESU distribution

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Field instruments used in the campaignField instruments used in the campaign

PAR AlbedometerPAR Albedometer(Patent pending,Bogaert J.-UA)(Patent pending,Bogaert J.-UA) LAI-2000 (Licor)LAI-2000 (Licor) TRAC (CCRS)TRAC (CCRS)

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0.0

0.5

1.0

1.5

2.0

2.5

3.0

B2

C3

E2

C2

C1

B3

C4

B1 F2 F4 E5

A3

E6

G3

E4 F1 A1

G2

G1

A4

H4

B4

D3

H1

H2

E3 I4 F3 E1

D4

D2

G4 I1 D1 I3 H3

A2 I2

ESU

LA

I

max

min

Average

y = 0.2563x + 0.0625

R2 = 0.6818

0.0

0.1

0.1

0.2

0.2

0.3

0.3

0.4

0.4

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

LAI

STD

EV

Results: LAI field measurements – LAI2000Results: LAI field measurements – LAI2000

Clear-cut increase in standard deviation Clear-cut increase in standard deviation with increasing LAIwith increasing LAI

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Results: Results: LAILAI field measurements - TRAC vs LAI2000ield measurements - TRAC vs LAI2000

Relationship TRAC - LAI-2000

y = 0.7564x + 0.1074

R2 = 0.7397

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.2 0.4 0.6 0.8 1

LAI-2000

TR

AC

LA

Ie

0

0.2

0.4

0.6

0.8

1

1.2

1.4

A1 A2 A3 A4 B1 B3 B4 C1 C2 C3 C4 E1 E3 E4 E5 E6 F1 F3 G1 G2 G3 G4 H1 H2 H3 I4

LAI-2000

Trac_LAIe

Trac_LAI

Comparison between TRAC and LAI-2000 LAI dataComparison between TRAC and LAI-2000 LAI dataelicits a relatively good agreement.elicits a relatively good agreement.

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Results: Field measurements - Gap fraction vs LAIResults: Field measurements - Gap fraction vs LAI

y = -0.3332x - 0.0024

R2 = 0.657

y = -0.4625x + 0.0289

R2 = 0.8201

y = -0.6508x + 0.0468

R2 = 0.8927

y = -0.9354x + 0.0282

R2 = 0.9478

y = -1.3196x - 0.053

R2 = 0.9494

y = -0.7403x + 0.0097

R2 = 0.9931

- 4.5

- 4

- 3.5

- 3

- 2.5

- 2

- 1.5

- 1

- 0.5

0

0.5

0 0.5 1 1.5 2 2.5 3 3.5

LAI

LN(G

ap f

ract

ion)

VZA: 7° VZA: 23° VZA: 38° VZA: 53°

VZA: 68° mean VZA Linear (VZA: 7°) Linear (VZA: 23°)

Linear (VZA: 38°) Linear (VZA: 53°) Linear (VZA: 68°) Linear (mean VZA)

This relationship can be used to estimate gap fraction from LAI

0.5

0.55

0.6

0.65

0.7

0.75

0.8

0.85

0.9

0.95

1

0 20 40 60 80

View zenith angle (°)

R²

LAI2000 sampling

Small zenith angles Small zenith angles are suboptimalare suboptimal

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Results: Albedo field measurementsResults: Albedo field measurements

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

D3

D2

D1

A4

D4

E6

E4

E3

A1

E5

A2

H1

G2

H3

G1

B4 I2 G3 I3 G4 F1 I4 F4 A3

H2

E2

B3

B1 F3 F2 H4

B2

C4

C2 I1 E1

ESU

Alb

edo

max

min

Average

0

0.005

0.01

0.015

0.02

0.025

0.07 0.09 0.11 0.13 0.15 0.17

Albedo

ST

DV

Very weak relationship between standard deviation Very weak relationship between standard deviation and albedo.and albedo.

Probably a linear increase of standard deviation Probably a linear increase of standard deviation with increasing albedo.with increasing albedo.

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Results: Upscaling using VI’s from Landsat ETM+Results: Upscaling using VI’s from Landsat ETM+VI Field LAI measurements Equation R2 Author

NDVI/SR Allometric method NDVI = 0.5724 + 0.0989LAI-0.0114LAI2 + 0.0004LAI3 0.74 Turner et al. (1999)

SR = 2.2282 + 2.5376LAI-0.1576LAI2 0.59

NDVI/SR Allometric method NDVI = 0.0377LAI + 0.607 0.72 Fassnacht et al. (1997)

SR = 0.9357LAI + 3.552 0.71

SR Allometric method SR = 1.92LAI0.583 0.91 Peterson et al. (1987)

SR = 1.92 + 0.532LAI 0.83

NDVI/SR LAI-2000 and TRAC NDVI = 0.032LAI + 0.635 0.42 Chen and Cihlar (1996)

SR = 1.014LAI + 3.637 0.49

SR LAI-2000 and TRAC SR = 1.153LAI + 2.56 0.66 Chen et al. (2002)

SR Ceptometer SR = 3.1196 + 5857log(LAI) 0.97 Spanner et al. (1994)

NDVI/SR LAI-2000 NDVI = 1.2383/(1/LAI + 0.9061)-0.3348 0.87 Gong et al. (1995)

SR = 0.96/(1/LAI-0.066) + 0.987 0.88

NDVI Allometric method LAI = 33.99NDVI-121 0.75 Curran et al. (1992)

SR Allometric method SR = 0.614LAI + 1.23 0.82 Running et al. (1986)

NDVI Allometric method NDVI = 0.03LAI + 0.6 0.32 Nemani et al. (1993)

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y = 0.021x1.9301

R2 = 0.54; RMSE=0.20

0

0.2

0.4

0.6

0.8

1

1.2

2.0 3.0 4.0 5.0 6.0 7.0 8.0

SR

LA

I

y = 0.0067e6.4841x

R2 = 0.53; RMSE=0.24

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0.4 0.5 0.6 0.7 0.8

NDVI

LA

I

Results: Upscaling using VI’s from Landsat ETM+Results: Upscaling using VI’s from Landsat ETM+

y = 0.1283x2.5536

R2 = 0.67; RMSE=0.18

0

0.2

0.4

0.6

0.8

1

1.2

0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2

SAVI

LAI

NDVI: R² = 0.53; RMSE = 0.24NDVI: R² = 0.53; RMSE = 0.24SR: R² = 0.54; RMSE = 0.20SR: R² = 0.54; RMSE = 0.20SAVI: R² = 0.67; RMSE = 0.18SAVI: R² = 0.67; RMSE = 0.18

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Results: Upscaling using Landsat ETM+ NDVIResults: Upscaling using Landsat ETM+ NDVI

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Results: Upscaling LAI using ETM+ SAVIResults: Upscaling LAI using ETM+ SAVIy = 0.1283x2.5536

R2 = 0.67; RMSE=0.18

0

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1

1.2

0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2

SAVI

LA

I

Transfer function

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Results: Upscaling Gap fraction using ETM+ NDVIResults: Upscaling Gap fraction using ETM+ NDVI

y = -2.8242x2 + 2.6995x + 0.2754

R2 = 0.9999

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0.5

0.6

0.7

0.8

0.9

1

0.5 0.6 0.7 0.8 0.9

NDVI

Gap

fr.

Transfer function

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Results: Upscaling Albedo using ETM+ NDVIResults: Upscaling Albedo using ETM+ NDVIy = -0.1413x + 0.2089

R2 = 0.3692; RMSE=0.0137

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0.08

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0.16

0.18

0.4 0.5 0.6 0.7 0.8

NDVI

Alb

edo

Transfer function

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Results: Aggregation of ETM+ LAI HR to 1x1km²Results: Aggregation of ETM+ LAI HR to 1x1km²

Pixel frequency at the 30x30 m² Pixel frequency at the 30x30 m² scale is different for each ESU.scale is different for each ESU.

To aggregate, the mean value of To aggregate, the mean value of the pixel distribution was the pixel distribution was

selected as a first proxy for the selected as a first proxy for the pixel value at the 1x1 km² scale.pixel value at the 1x1 km² scale.

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Results: Aggregation of ETM+ LAI HR to 1x1km²Results: Aggregation of ETM+ LAI HR to 1x1km²

Aggregated 1x1 km² Aggregated 1x1 km² LAI data from ETM+ LAI data from ETM+

NDVI data NDVI data using mean valuesusing mean values

Aggregated 1x1 km² Aggregated 1x1 km² LAI data from ETM+ LAI data from ETM+

SR data SR data using mean valuesusing mean values

Aggregated 1x1 km² Aggregated 1x1 km² LAI data from ETM+ LAI data from ETM+

SAVI data SAVI data using mean valuesusing mean values

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Results: Validation of MODIS LAI productResults: Validation of MODIS LAI product

y = 0.9042x + 0.7713

R2 = 0.4491

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1.2

1.5

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Aggregated LAI from ETM+ NDVI data

MO

DIS

LA

I

y = 0.8368x + 0.8209R2 = 0.4362

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0.6

0.9

1.2

1.5

0 0.3 0.6 0.9 1.2 1.5

Aggregated LAI from ETM+ SR data

MO

DIS

LA

Iy = 0.7084x + 0.9009

R2 = 0.2708

0

0.3

0.6

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1.5

0 0.3 0.6 0.9 1.2 1.5

Aggregated LAI from ETM+ SAVI data

MO

DIS

LA

I

Validation of MODIS Validation of MODIS LAI data with LAI data with

aggregated LAI data aggregated LAI data from ETM+ NDVIfrom ETM+ NDVI

Validation of MODIS Validation of MODIS LAI data with LAI data with

aggregated LAI data aggregated LAI data from ETM+ SRfrom ETM+ SR

Validation of MODIS Validation of MODIS LAI data with LAI data with

aggregated LAI data aggregated LAI data from ETM+ SAVIfrom ETM+ SAVI

Best fit (highest R²), best slope (closest to 1) Best fit (highest R²), best slope (closest to 1) and smallest intercept (systematic bias)and smallest intercept (systematic bias)

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The complete The complete procedure has been applied at the Shandan site in procedure has been applied at the Shandan site in

Northwestern China. The Shandan site is very suitable since its vegetation is a Northwestern China. The Shandan site is very suitable since its vegetation is a

homegeneous grasslandhomegeneous grassland..

Three bio- geophysical variable fields have been produced for validation purposes, e.i., Three bio- geophysical variable fields have been produced for validation purposes, e.i.,

LAI, gap fraction and albedoLAI, gap fraction and albedo..

SAVI SAVI seems to be the best of three VI’s to perform up-scaling. Nevertheless, the seems to be the best of three VI’s to perform up-scaling. Nevertheless, the

aggregated 1x1 km², obtained with aggregated 1x1 km², obtained with NDVI based up-scalingNDVI based up-scaling, elicits the best results in the , elicits the best results in the

MODIS LAI product validation.MODIS LAI product validation.

The comparison between LAI measurements with the LAI-2000 and TRAC is The comparison between LAI measurements with the LAI-2000 and TRAC is

satisfactory. However, LAI-2000 measurements are of beter quality.satisfactory. However, LAI-2000 measurements are of beter quality.

Suboptimal samplingSuboptimal sampling is observed for the between 10 and 30 cm high grassland Shandan is observed for the between 10 and 30 cm high grassland Shandan

site, when small view zenith angles are selected with the LAI-2000.site, when small view zenith angles are selected with the LAI-2000.

The MODIS LAI product elicits a The MODIS LAI product elicits a systematic biassystematic bias with higher LAI values. A plausible with higher LAI values. A plausible

reason can be s.o.p.reason can be s.o.p.

How about,…. conclusionsHow about,…. conclusions

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30-

40cm

5cm

LAI-2000LAI-2000

Conclusions: Suboptimal LAI samplingConclusions: Suboptimal LAI sampling

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0.95

1

0 20 40 60 80

View zenith angle (°)

R²

LAI2000 sampling

Small zenith angles are Small zenith angles are suboptimalsuboptimal when the when the vegetation has a low height.vegetation has a low height.

In that case the effective In that case the effective LAI LAI will be will be underestimatedunderestimated.. This can explain the This can explain the higher MODIS LAIhigher MODIS LAI with with

respect to the up-scaled field measurements.respect to the up-scaled field measurements. It should be investigated whether the It should be investigated whether the elimination elimination

of the smallest view zenith anglesof the smallest view zenith angles gives better gives better validation results, or the application of DHP.validation results, or the application of DHP.

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Shandan’s flowersShandan’s flowers

are grateful for your attentionare grateful for your attention