The document discusses using Sentinel-2 satellite data to update the Copernicus High Resolution Layer (HRL) imperviousness degree. Single scene classifications are performed on Sentinel-2 and Landsat-8 images, then fused using Dempster-Shafer theory to create a cloud-free coverage. The method was tested on Prague and Rennes and achieved a Kappa of 0.90 compared to 2012 HRL data. Sentinel-2's abilities like spectral resolution, texture features, and high repetitiveness make it suitable for updating Copernicus products like HRL and Urban Atlas going forward.

1. M O N I T O R I N G U R B A N
A R E A S W I T H S E N T I N E L - 2 .
APPLICATION TO THE UPDATE OF THE
COPERNICUS HIGH RESOLUTION LAYER
IMPERVIOUSNESS DEGREE
October 25t h 2016, Brussels
Antoine Lefebvre
CNES, UMR IRISA
a n t o i n e . l e f e b v r e @ k e r m a p . c o m

2. 70%world population in Cities by 2050

3. Urban!
Changes!
Urban area!
Liu et al. 2010

4. Urban!
Changes!
Liu et al. 2010
Edge expansion!

5. Urban!
Changes!
Liu et al. 2010
Edge expansion!
Outlying!

6. Urban!
Changes!
Liu et al. 2010
Edge expansion!
Outlying!
Infilling!

7. Copernicus!
High!
Resolution!
Layers !
5 Layers including
Imperviousness
Main specifications
Resolution : 20x20m ; 100x100m
Soil sealing degree : 0 – 100%
Seamless European-wide
coverage over 39 EEA countries
Produced for 2006, 2009, 2012
2015 update is going to be
produced

8. Copernicus!
High!
Resolution!
Layers !
5 Layers including
Imperviousness
Main specifications
Resolution : 20x20m ; 100x100m
Soil sealing degree : 0 – 100%
Seamless European-wide
coverage over 39 EEA countries
Produced for 2006, 2009, 2012
2015 update is going to be
produced
How Sentinel-2
can help ?

9. Sentinel-2A!
Launched on 23 June 2015
13 multi-spectral bands
Up to 10m
3 bands in the red-edge
2 bands in the SWIR
Repetitiveness
up to 5 days (with constellation)
Large swath
290 km
(185 km for LANDSAT)

10. Key!
Idea!
t1 t2 t3 t4
- None provides a cloud-
free coverage
- Incomplete :me series
(gaps)
Sen$nel-2 $me series

11. Key!
Idea!
t1 t2 t3 t4
- None provides a cloud-
free coverage
- Incomplete :me series
(gaps)
- How to get an homogeneous
result over Europe ?
- How to do it in an automa6c
and opera6onal way ?
Sen$nel-2 $me series

12. Key!
Idea!
12
t1 t2 t3 t4
1. Single scene
classifica:on

13. Key!
Idea!
13
t1 t2 t3 t4 Sum of overlays
1. Single scene
classifica:on
2. Cloud-free
coverage with sum
of overlays

14. Key!
Idea!
14
t1 t2 t3 t4 Sum of overlays
1. Single scene
classifica:on
2. Cloud-free
coverage with sum
of overlays
3. Combina:on of
classifica:ons with data
fusion technique

15. Study site!
2 Former Urban Areas
- Prague, Czech Republic - 6,900 km2
- Rennes, France 2,500 km2
Sen:nel-2 and Landsat-8 images

16. Method!
SENTINEL-2
SENTINEL-2
LANDSAT-8
LANDSAT-8
1. Data Preparation!

17. All spectral bands + PANTEX texture feature
Classifier
Random Forest
Sampling
Automa:c sampling on Copernicus High
Resolu:on Layer (2012)
Uncertainty es:ma:on
1 - Kappa
Method!
S2 PANTEX S2 image
SENTINEL-2
SENTINEL-2
LANDSAT-8
LANDSAT-8
2. Single Scene!
Classification!

18. Dempster-Shafer
Theory :
- Dealing with
uncertainty
Associa:ve rule:
- Combina:on of
numerous separate
informa:on
- Sen:nel-2,
Landsat-8, … and
some more if
available
Method!
SENTINEL-2
SENTINEL-2
LANDSAT-8
LANDSAT-8
3. Multi-
temporal
fusion!

19. Method!
SENTINEL-2
SENTINEL-2
LANDSAT-8
LANDSAT-8 3. Multi-source!
Fusion!

20. Benefits of multi-temporal data!
Limitation of
commision errors!
Urban areas
Agricultural areas

21. Geometric
accuracy
enhancement!
Urban areas
Imprecise edges
Benefits of multi-source data!

22. Change!
Detection!
Comparison!
HRL 2012- 2015!
KAPPA !
0.90!

23. Copernicus HRL imperviousness
update!
2011 Google Earth 2015 Sen:nel-2 2012-2015
HRL
Change Map
2015
HRL
Imperviousness

24. 2011 Google Earth 2015 Sen:nel-2 2012-2015
HRL
Change Map
2015
HRL
Imperviousness
Copernicus HRL imperviousness
update!

25. Conclusion!
Simple method!
!
- Overcome missing data!
- Provide cloud-free coverage!
- Limited interaction with the user!
- Good accuracy: More overlays,
less uncertainty!
- Multi-source ability!

26. Conclusion!
Simple method!
!
- Overcome missing data!
- Provide cloud-free coverage!
- Limited interaction with the user!
- Good accuracy: More overlays,
less uncertainty!
- Multi-source ability!
Sentinel-2 abilities!
!
- Spectral resolution: cloud
extraction, Land cover
classification!
- Spatial resolution: texture
feature!
- Temporal resolution: high
repetitiveness!

27. Conclusion!
Simple method!
!
- Overcome missing data!
- Provide cloud-free coverage!
- Limited interaction with the user!
- Good accuracy: More overlays,
less uncertainty!
- Multi-source ability!
Sentinel-2 abilities!
!
- Spectral resolution: cloud
extraction, Land cover
classification!
- Spatial resolution: texture
feature!
- Temporal resolution: high
repetitiveness!
Suitable to
Copernicus
Products !
HRL, !
Urban Atlas!
Lefebvre A., Sannier C., Corpetti, T. (2016). Monitoring Urban Areas with Sentinel-2A Data:
Application to the Update of the Copernicus High Resolution Layer Imperviousness
Degree. Remote Sensing, 8(7), 606.

28. Previous!
work!
HRL 2012!
imperviousness!
2,500,000 km2!
SPOT-5!
RapidEye!
IRS-LISS 3!
IRS-AWIFS!
≈7 To!
Lefebvre A., Beaugendre N., Pennec A., Sannier C., Corpetti T. (2013). Using
data fusion to update built-up areas of the 2012 European High-Resolution
Layer Imperviousness. In 33rd EARSeL Symposium. Matera, Italy.

29. Current!
work!
Monitoring urban areas
since 1985
1984 - 2010
à SPOT 1, 2, 3, 4, 5
àLandsat 5, 7
≈ 18,000 images
2015 – 2016
à Landsat 8
à Sentinel-2

30. Z
OUR SERVICES
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