4-8 LeToan BIOMASS-update - eorc.jaxa.jp · • Expected launch 2016. Thuy Le Toan, K&C 13, Tokyo,...

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Thuy Le Toan, K&C 13, Tokyo, January 21 2010 biomass TO OBSERVE FOREST BIOMASS FOR A BETTER UNDERSTANDING OF THE CARBON CYCLE

Transcript of 4-8 LeToan BIOMASS-update - eorc.jaxa.jp · • Expected launch 2016. Thuy Le Toan, K&C 13, Tokyo,...

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Thuy Le Toan, K&C 13, Tokyo, January 21 2010

biomass

TO OBSERVE FOREST BIOMASSFOR A BETTER UNDERSTANDING OF THE CARBON CYCLE

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The Third Cycle of Earth ExplorerCore Missions

• Call for ideas issued in 2005• 24 proposals evaluated• 6 Candidate Missions selected in May 2006 for Phase 0

• 3 Candidate Missions selected in January 2009 for Phase A

– BIOMASS: BIOMASS Monitoring Mission for Carbon Assessment– PREMIER: Process Exploration through Measurements of Infrared

and millimeter Emitted Radiation– CoRe-H20: Cold Regions Hydrology High-resolution Observatory

• Final selection mid 2011• Expected launch 2016

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Thuy Le Toan, K&C 13, Tokyo, January 21 2010

Map annual reductions inbiomass globally

Reduce uncertainty in deforestationemissions to a level comparable touncertainty in net ocean flux

Map increases in biomassglobally across missionlifetime

Improve estimates of terrestrialcarbon sinks from regrowth andreforestation

Consistent global maps offorest biomass and height atscale of 100 m

Greatly improve current estimates offorest carbon stocks

ProductObjective

BIOMASS primary science objectivesThe BIOMASS mission addresses the largest single source of uncertainty in the global carbon budget: the terrestrial ecosystem.

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Phase A main activities 2009-2011

1. Improve and further validate biomass and height retrievalalgorithms

2. Flight campaign in regions of high forest biomass density toverify the robustness of the retrieval algorithms

3. Define a post-launch protocol for global validationconsidering different biomes

4. Elaborate potential secondary objectives of the first P-bandmission in space.

5. Further investigate on the use of BIOMASS in carbonmodels

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Retrieval algorithms

Phase 0

! Biomass retrieval using SAR intensities

! Demonstration PolInSAR height retrieval at 30 day interval

! Preliminary works on combined intensity and PolInSAR

Phase A " Further validation in areas with topography and at tropical forests

" Exploit PolInSAR coherences and tomography

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Thuy Le Toan, K&C 13, Tokyo, January 21 2010

Calibration, Ionospheric correction

Retrieval algorithm

Geophysical products

• Forest biomass• Forest height• Forest biomass temporal change• Forest disturbance

Polarimetric radarintensity

PolarimetricInterferometricPhase

Orbit cycle n

Orbit cycle n+1

BIOMASS observation concept

HH HV VV Phase

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Thuy Le Toan, K&C 13, Tokyo, January 21 2010

BioSAR Remingstorp forest, Sweden

HH, VV, HV

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Biomass from Intensity

0 - 1010 - 2020 - 3030 - 4040 - 7070 - 9090 - 120

120 - 160160 - 200200 - 260> 260

0 - 1010 - 2020 - 3030 - 4040 - 7070 - 9090 - 120

120 - 160160 - 200200 - 260> 260

0 - 1010 - 2020 - 3030 - 4040 - 7070 - 9090 - 120

120 - 160160 - 200200 - 260> 260

Biomass (ton/ha)

40

30

20

10

0m

Pol-InSAR height

Height (m)

Intensity + Pol-InSAR

RMSE= 42.28 t ha-1 RMSE= 27.93 t ha-1 RMSE= 11.02 t ha-1RMSE= 42.28 t ha-1 RMSE= 27.93 t ha-1 RMSE= 11.02 t ha-1

RMSE= 42.28 t ha-1 RMSE= 27.93 t ha-1 RMSE= 11.02 t ha-1RMSE= 42.28 t ha-1 RMSE= 27.93 t ha-1 RMSE= 11.02 t ha-1

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SAR Tomography (T-SAR) Algorithm to characterise forest structure using multi-baseline,polarimetric SAR data

Tebaldini, 2009

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Ground Layer - HH Ground Layer - HV

Canopy Layer - HH Canopy layer - HV

0 10 200

1

2

3

4x 10 4

dB0 10 20

0

1

2

3

4x 10 4

dB

Rat

io G

L/C

LTomography from 9 fully polarimetric images (8 baselines)

• HH: backscatter from groundlevel dominates that fromcanopy level by about 10 dB

• Similar results in VV

• HV: Contributions from groundlevel are dominant also

• Local topography• Ground and trunkroughness• Ground – canopyinteractions• Underlying vegetation+branches

Tebaldini & Rocca, 2009

HH HV

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RMSE= 42.28 t ha-1 RMSE= 27.93 t ha-1 RMSE= 11.02 t ha-1RMSE= 42.28 t ha-1 RMSE= 27.93 t ha-1 RMSE= 11.02 t ha-1

HV HV + PolInSAR h HV + PolInSAR h+ Tomo

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Four Four differentdifferent trackstracks

BIOSAR-2: Boreal forests with marked topographyOctober 2008- Kryclan forest, Northern Sweden- ESAR from DLR

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RMSECV = 29 tons/ha

Unsupervised biomass estimates using HV (CESBIO)

Supervised biomass estimates using HV, HH and VV (Chalmers)

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Comparison of estimated and measured biomass from data of heading 132° , with data points restriced to rada r incidence angle of 25° -40°. Left: total above ground biomass, middle: crown biomass, right: stem biomass. The coefficients used in the inversion are derived from data of heading s 42°, 133°, 3 13° et 357°

Retrieval of above ground biomass (crown + stem) using Saatchi et al. 2007 algorithm

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volgéomSNRtemp !!!!! ...=

!"#$%"#&'()*&+,&-,+.&%)/"("0%"120#&("#$%"#&30&(24)

5"#$%"#&67&(24)&6"89""0:);2(3<24)0<

! Rationale

Ratio of Coherence = linked to biomass through temporal and volume decorrelation ?

Use of intensity and interferometric coherence in biomass inversion

Thuy Le Toan, Julien Valteau, Alexandre Couhert, Franck GarestierAugust 2009

! Simulation

! Test on data

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Simulation of the ratio between coherence HV and coherence VV

Hypothesis: Mean attenuation 1 dB/m Same temporal decorrelation HV and VV

G/V ratioof tree canopy

Coherence ratio of forest layer: sensitivity to layer height depends on baseline

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P-band Coherence, Remningstorp forest Temporal interval 0 , 30, 60 daysBaselines: 10 m, 30 m; 50 m, 70 m, 80 m

Ground data: 10 reference stands of 80 m x 80 m

Testing

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Interferometric coherence maps

!!"#$%&'("""""!)"#*+'',(""""))"#+'-(

=)#$;" >/2<"70 m 0 day

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Thuy Le Toan, K&C 13, Tokyo, January 21 2010

30 days, 30 m 30 days, 50 m

0 day, 60 m 0 day, 70 m

In situ biomass (t/ha)

In situ biomass (t/ha)In situ biomass (t/ha)

In situ biomass (t/ha)

Coh

eren

ceH

V /

Coh

eren

ceV

V

Coh

eren

ceH

V /

Coh

eren

ceV

VC

oher

ence

HV

/ C

oher

ence

VV

Coh

eren

ceH

V /

Coh

eren

ceV

V

30 days, 30 m30 days, 30 m 30 days, 50 m30 days, 50 m

0 day, 60 m0 day, 60 m 0 day, 70 m0 day, 70 m

In situ biomass (t/ha)

In situ biomass (t/ha)In situ biomass (t/ha)

In situ biomass (t/ha)

Coh

eren

ceH

V /

Coh

eren

ceV

V

Coh

eren

ceH

V /

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eren

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ence

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/ C

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ence

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Coh

eren

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V /

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In situ biomass (t/ha)

Coh

eren

ceH

V / C

oher

ence

VV

In situ biomass (t/ha)

Coh

eren

ceH

V / C

oher

ence

VV

In situ biomass (t/ha)

Coh

eren

ceH

V / C

oher

ence

VV

Ratio of HV coherence / coherence VVvs in situ biomass

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The Bayesian approach

theo

meas

DD

R =

Where R is random variable representing sources of random noise

D meas is measurement (HV, HH andcoherence ratio)

D theo is theoretical values of D given B

)(BfDtheo =

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Thuy Le Toan, K&C 13, Tokyo, January 21 2010

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Bayesian inversion of biomass

HV HV and coh HV/coh VV Map of the difference

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Flight campaigns

Phase 0

BIOSAR-I : Remningstorp, Sweden, March -May2007To test 0, 30, 60 day repeat PolInSAR

BIOSAR-2: Kryclan, Sweden, October 2008To validate methods on forests with strong topograhy

Phase A

TropiSAR: French Guiana, August 2009

Candidate experiments:Ground based radar over forest in F. GuianaFlight campaign in Gabon

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Nouragues

Arbocel

Rochambeau

Kaw

Paracou

TROPISAR test sites

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Ground data collection: Paracou -Arbocel

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Lidar data : Paracou

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Ground data collection: Nouragues

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N

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MARAIS DE KAW - VOL 5 -

VH

HH

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Forest biomass: essential in carbon budgetcalculation and poorly known.

BIOMASS Primary objectives:• Map forest biomass worldwide.• ! Monitor deforestation.

• ! Monitor forest regrowth and afforestation.

Large impact on the calculation of the carbonbudget of terrestrial ecosystems

Question: can we also use biomassmeasurements to improve process basedmodels aimed at calculating forest carbonfluxes?

The use of biomass measurements in carbon models

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Biomass density estimates by models

LPJ

SDGVM

ORCHIDEE

Schaphoff et al., 2009

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Siberia Transect

Need to reconsider the models to ingest the actual biomass

Schaphoff et al., 2009

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In situ Biomassmeasurements compiled inMalhi et al. 2007223 sites in Amazonia

Integration of biomass data in the dynamic vegetation model ORCHIDEE

N. Delbart, N. Viovy, P. Ciais, and T. Le Toan , EGU 2009

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Simulated biomass: realistic simulations, except for very dryforests (underestimation) or very wet forests (overestimation).

Respect climatic gradients, not local heterogeneity# modelneeds improvement

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Thuy Le Toan, K&C 13, Tokyo, January 21 2010User Consultation Meeting, Lisbon, Portugal, 20-21 January 2009 biomass 35

Mission architecture overviewGROUND SEGMENT

Flight Operations Segment1 TT&C Station (Kiruna), S-Band

Flight Operation Control Center (ESOC)

USER SEGMENTCarbon cycle modellers/Research Centres

Payload Data Ground Segment1 Science Data Acquisition Station (Svalbard)Processing and Archiving Element (ESRIN)

Auxiliary DataLand cover maps

Digital Elevation ModelsORBIT

Sun-synchronous,local time 05:00, 640 km,27 to 39-day repeat cycle

SPACE SEGMENTSingle Spacecraft, 1200 - 2600 kg,

800 - 1200WPayload: P-band SAR

5 year lifetime

LAUNCHERSoyuz/Vega

BIOMASS Mission

Elements

SUBJECTTerrestrial carbon stock/carbon fluxes

by measurement of forest biomass

CO2

C

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Thuy Le Toan, K&C 13, Tokyo, January 21 2010User Consultation Meeting, Lisbon, Portugal, 20-21 January 2009 biomass 36

Satellite configurations

Mass 1200-2600 kg Power 800-1200 WData storage 400-700 Gb Data Downlink 260-290 Mb/s

Concept 1

Concept 2

Concept 3

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Stowed configurationsin launcher fairings

Concept 1 in Soyuz Concept 2 in Soyuz Concept 3 in Vega