Autonomous atmospheric correction and model based land use ...€¦ · TIGER: ESA/UNESCO initiative with focus: Space – Water – Africa ... CHRIS Mode 3 (only 18 bands) Pixel-wise

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4th ESA CHRIS PROBA Workshop September 19- 21th 2006 No. 1

Autonomous atmospheric correction and model based land use

classification of CHRIS data of the AquiferEx test-sites in Tunisia

Heike Bach, Wolfgang Eder, Silke Begiebing

VISTA GmbHRemote Sensing in Geosiences

www.vista-geo.de

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ESA/ESRIN – AQUIFEREOEP-DUEP-EOPS-SW04-0005

2AQUIFER Project

Remote Sensing for Management of Transboundary Aquifers in Africa

• TIGER Aquifer = demonstrator projectTIGER: ESA/UNESCO initiative with focus: Space – Water – Africa

• ESA Aquifer funded / embedded withinESA – DUE: DATA USER ELEMENT

• UNESCO SASS, UNESCO IHP

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ESA/ESRIN – AQUIFEREOEP-DUEP-EOPS-SW04-0005

3AQUIFER Project

Product and Service Responsibility

“Operational” Products and Services: - PHASE 2 and PHASE 31. Land Use/Land Cover Maps and Change Maps Local Providers/

SCOT-F2. Digital Terrain Models Telespazio -I / GAF-D3. Water Abstraction Estimation JR - A4. Surface Water Extension and Dynamics GAF - D

“Science” Products: - PHASE 35. Refined Land Use Map Product VISTA - D6. Subsidence Monitoring and Assoc. Error Maps Telespazio - I7. Refined Water Abstraction Estimation JR - A8. Water Vegetation Monitoring over entire Aquifer Uni Jena - D9. ETA and Water Balance VISTA - D

AQUIFER-PROJECT WEBSITE: http://www2.gaf.de/Aquifer/

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The AquiferEx Campaign

• In the frame of AQUIFER, an ESA funded airborne campaign “AquiferEx” was conducted

• performed by the German Aerospace Establishment DLR

• 2 test sites in Tunisia were mapped using 2 sensors

• Hyperspectral: AVIS (University of Munich)

• Multifrequent + multipolarimetric Radar: ESAR (DLR).

• Ground Truth was collected by the University of Munich and DLR during the flight campaign

• AquiferEx data will be used for a refined land use / cover map

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Test-sites of AquiferEx

Gabès

Ben Gardane

Tripoli

Tunis

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AVIS acquisition09.11.05(VNIR)

Flight Strips of Airborne CampaignSynchronous satellite acquisitions: ASAR/AP data

Gabès, 28.11.2005 + E-SAR Ben Gardane, 25.11.2005 + AVIS

E-SAR acquis.11.11.05L-Band HH,VH,VV

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Test Site: Ben GardaneSynchronous Satellite acquisitions: CHRIS

Legend

Flight strip

CHRIS NorthAcquisition date:

23.10.2005

CHRIS SouthAcquisition date:

31.10.2005

CHRIS Mode3A, NadirGSD: 17 m

700, 715, 900 nm

Ground Truth points

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Legend

Flight strip

CHRIS EastAcquisition date:01.11.2005

CHRIS WestAcquisition date:09.11.2005

CHRIS Mode3A, Nadir

GSD: 17 m

700, 715, 900 nm

Ground Truth points

Test Site: GabesSynchronous Satellite acquisitions: CHRIS

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Autonomous atmospheric correctionof CHRIS data

• A methodology that uses MODTRAN4 radiative transfer modelling is applied for atmospheric correction

• Acquisition parameters on solar and observation geometry are known from sensor header information

• Parameterisation of aerosol optical thickness (or visibility) and atmospheric water vapour content requires atmospheric data that is often missing (as is the case for the Tunisian test-sites)

• It will be demonstrated how hyperspectral data allow the autonomous retrieval of water vapour from spectral information

• Multidirectional observations further allow the assessment of the adequate atmospheric visibility.

• Thus, a fully autonomous atmospheric correction is possible.

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water vapour factor for Gabès

20

25

30

35

40

45

50

55

60

500 600 700 800 900 1000 1100Wavelength [nm]

Spe

ctra

l Ref

lect

ance

[%]

0.51

1.51.28

Soil spectra retrieved under the assumption of different water vapour factors: 0.5 – 1.0 – 1.5

Determination of Water VapourCHRIS Mode 3 (only 18 bands)

Pixel-wise retrieved water vapourMean = 0.71 Std.dev=0.03

=> Sensor noise dominates due to low variability of water vapour, but scene average derivable

Ben Gardane

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Vegetation spectra retrieved under the assumption of different water vapour factors: 0.5 – 1.0 – 1.5

Determination of Water VapourCHRIS Mode 1 (64 bands)

water vapour factor

0

10

20

30

40

50

60

70

80

90

100

700 750 800 850 900 950 1000 1050 1100

Wavelength [nm]

Spec

tral R

efle

ctan

ce [%

]

0.510.651.5

=> Influence of land surface properties very low; vegetation water separable

Pixel-wise retrieved water vapourMean = 0.65 Std.dev=0.04

Baasdorf

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The Soil-Leaf-Canopy (SLC) reflectance model simulates the BRDF of a soil using the CHRIS acquisition specifications:

0

20

40

60

80

400 500 600 700 800 900 1000 1100

Wavelength [nm]

Spec

tral R

efle

ctan

ce [%

]

Forward 55°Forward 36°NadirBackward 36°Backward 55°

Concept: Varying the visibility in the atmospheric correction, the most similar CHRIS spectra are selected.

Determination of Visibility

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Multiangular soil spectra retrieved under the assumption of different atmospheric visibilities


Visibility = 5km

0

10

20

30

40

50

60

70

80

400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100

Wavelength [nm]

Spec

tral

Ref

lect

ance

[%]

Forw. 55 Forw. 36 NadirBackw. 36 Backw. 55

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Visibility = 10km

0

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20

30

40

50

60

70

80

400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100

Wavelength [nm]

Spec

tral

Ref

lect

ance

[%]


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Visibility = 23km

0

10

20

30

40

50

60

70

80

400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100

Wavelength [nm]

Spec

tral

Ref

lect

ance

[%]


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Visibility = 40km

0

10

20

30

40

50

60

70

80

400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100

Wavelength [nm]

Spec

tral

Ref

lect

ance

[%]


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Visibility selected with BRDF similar to model results avoiding zero reflectance in the visible;

Example Result : VisibilityBen Gardane 23.10.2005


23 km40 km

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0

5

10

15

20

25

30

35

40

45

50

400 450 500 550 600 650 700 750 800 850 900Wavelength [nm]

Spec

tral

Ref

lect

ance

[%]

Spectrometer (11.11.)maxminAVIS (11.11.)CHRIS ( 9.11.)

Validation of atmospheric correctionSensor comparison for Gabès

Spectrometer & AVIS compared to CHRIS; harvested field

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Validation of atmospheric correctionSensor comparison for Gabès

Spectrometer & AVIS compared to CHRIS; alfalfa field

0

10

20

30

40

50

60

70

400 450 500 550 600 650 700 750 800 850 900Wavelength [nm]

Spec

tral

Ref

lect

ance

[%]

Spectrometer (11.11.)maxminAVIS (11.11.)CHRIS (9.11.)

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Parameter retrieval using SLC model inversion techniques

0

10

20

30

40

50

60

400 500 600 700 800 900 1000 1100

Wavelength [nm]

Spec

tral R

efle

ctan

ce [%

]

LAI=0LAI=0.5LAI=1LAI=1.5LAI=2

The Soil-Leaf-Canopy (SLC) reflectance model simulates a set of possible soil background and vegetation combinations and selects the soil and LAI where RMS deviation to CHRIS observation is minimum. Sample SLC results:

Vegetation on dry, bright soil Vegetation on wet, dark soil

0

10

20

30

40

50

60

400 500 600 700 800 900 1000 1100

Wavelength [nm]

Spec

tral R

efle

ctan

ce [%

]

LAI=0LAI=0.5LAI=1LAI=1.5LAI=2

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Input Images Gabès to be classified

VIS (bands 1- 4- 9) Red Edge (bands 9-11-16)

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SLC model inversion resultsdry soilhigh iron soilwetsoillimestonewater

LAI0.6 – 0.80.8 – 1.21.2 – 1.41.4 – 1.6> 1.6

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Separation of vegetated areas under irrigation or under dry conditions

Remark: Just one moment in time!

Irrigated

Non irrigated

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Model based classification resultSoil background

Vegetationcharacteristics

Agricultural management

LAI0.6 – 0.80.8 – 1.21.2 – 1.41.4 – 1.6> 1.6

dry soilhigh iron soilwetsoil

Irrigated

Non irrigated

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Conclusions• Based solely on radiative transfer model techniques for the

atmosphere (MODTRAN) and the land surface (SLC), it is possible to derive

– the atmospheric properties (water vapour and visibility) needed for reflectance calibration

– Bio-geo-physical parameters of the land surface that can be translated in an advanced classification

• Multiangular CHRIS data in full spectral mode are most suitable for this task.

• The developed model based approach showed promising results, but is only a very first step.

• Planned satellite sensors like ENMAP will allow to further develop, enhance and apply the presented methodology.

Documents

Autonomous atmospheric correction and model based land use ...€¦ · TIGER: ESA/UNESCO initiative with focus: Space – Water – Africa ... CHRIS Mode 3 (only 18 bands) Pixel-wise