GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use...

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GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use Mapping Erik de Badts

Transcript of GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use...

Page 1: GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use Mapping Erik de Badts.

GLC2000: British Isles and Northwest Europe

An Evaluation of the SPOT Vegetation Sensor for Land Use Mapping

Erik de Badts

Page 2: GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use Mapping Erik de Badts.

Flowchart

S p line F un c tion H A N T S

V a lida tion

C la ss if ica tion

R e g ion a liza tion

C lo udR e m o va l

W in d ow D efin it iona n d P ro jec tion

Page 3: GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use Mapping Erik de Badts.

Window Definition

Page 4: GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use Mapping Erik de Badts.

Window Definition

• Comparison with NOAA-AVHRR

• PELCOM

Page 5: GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use Mapping Erik de Badts.

Cloud Removal

Spline Function

• Define “Cloudy” Pixels

• Preservation of Original

Pixel Values

• Extrapolations in Beginning

and Ending of Time Series

HANTS (Harmonic

Analysis of Time

Series)

•Lost of Original Pixel Value

•Smoothed Time Series

•No Objective Rules

Page 6: GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use Mapping Erik de Badts.

HANTS Algorithm Explained

0

0.2

0.4

0.6

0.8

1 6 11 16 21 26 31 36

Decade (1996)

ND

VI (

-)

measuredrejectedHANTS

-0.4

-0.2

0

0.2

0.4

0 9 18 27 36

Decade (1996)

ND

VI (

-)

frequency = 0 (average)frequency = 1 (annual cycle)frequency = 2 (6 months cycle)

Original cloud affected and reconstructed cloudfree NDVI time series profile of one pixel

The Fourier components from which the cloudfree NDVI time series profile is reconstructed

Page 7: GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use Mapping Erik de Badts.

Conclusion Cloud Removal

Spline Original HANTS

•Higher Values in Filled Gaps

•Wider Data Range: Extremes

Page 8: GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use Mapping Erik de Badts.

Regionalization

•Improvement Discrimination Process on Difficult Classes

•Misclassification Due to Spectral Confusion Reduces

Page 9: GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use Mapping Erik de Badts.

Classification

• Masks

– Water Bodies

– Urban Areas

– Wetlands

• Classification: Treegrowing with CART (Salford

Systems)

– Forests: Red Wavelengths

– NDVI

• CART

– No Undesired “Mixed” Classes

– Statistical Prove on Separability

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Classification

Page 11: GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use Mapping Erik de Badts.

Validation

Accuracy Changewith

Reliability Changewith

PELCOM PELCOMArable Land 78.8% +1,0% 55.6% +23.5%

Pasture 58.7% +7.7% 49.7% +27.8%

NaturalGrassland

15.4% ---- 64.0% ----

DeciduousForest

17.1% -32.7% 27.7% +31.3%

EvergreenForest

45.6% +4.8% 38.0% +145.2%

Mixed Forest 17.1% +13.2% 15.1% +93.6%

Shrubs 57.2% +14.6% 59.6% +18.3%

Wetlands 44.7% +16.6% 15.6% +60.0%

Total Forest 55.3% +6.3% 53.9% +128.4%

•CORINE

–PELCOM

•FOA-Statistics

Page 12: GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use Mapping Erik de Badts.

Validation

•Geometrical Distortion of NOAA: Shift Towards the

Southeast

•Push Broom Wisk Broom

Page 13: GLC2000: British Isles and Northwest Europe An Evaluation of the SPOT Vegetation Sensor for Land Use Mapping Erik de Badts.

Conclusion

• HANTS : Best Way to Obtain a Cloudfree Time Series

• Treegrowing is a Consistent Method for Classification

• Few Improvement Compared to PELCOM (+1.5%)

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NDVI Changes in 2000