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 O c t o b e r 2 5 th 2016, Brussels A n t o i n e L e f e b v r e C N E S, U M R I R I S A a n t o i n e. l e f e b v r e @ k e r m a p. c o m
world population in Cities by 2050
Urban Changes Urban area Liu et al. 2010
Urban Changes Edge expansion Liu et al. 2010
Urban Changes Edge expansion Outlying Liu et al. 2010
Urban Changes Edge expansion Outlying Infilling Liu et al. 2010
5 Layers including Imperviousness Copernicus High Resolution Layers 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
5 Layers including Imperviousness Copernicus High Resolution Layers 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?
Launched on 23 June 2015 Sentinel-2A 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)
t 1 t 2 t 3 t 4 Key Idea Sentinel-2 time series - None provides a cloudfree coverage - Incomplete time series (gaps)
t 1 t 2 t 3 t 4 Key Idea Sentinel-2 time series - None provides a cloudfree coverage - How to get an homogeneous result over Europe? - Incomplete time series (gaps) - How to do it in an automatic and operational way?
t 1 t 2 t 3 t 4 Key Idea 1. Single scene classification 12
t 1 t 2 t 3 t 4 Sum of overlays Key Idea 1. Single scene classification 2. Cloud-free coverage with sum of overlays 13
t 1 t 2 t 3 t 4 Sum of overlays Key Idea 14 1. Single scene classification 2. Cloud-free coverage with sum of overlays 3. Combination of classifications with data fusion technique
Study site 2 Former Urban Areas - Prague, Czech Republic - 6,900 km 2 - Rennes, France 2,500 km 2 Sentinel-2 and Landsat-8 images
SENTINEL-2 Method SENTINEL-2 1. Data Preparation LANDSAT-8 LANDSAT-8
SENTINEL-2 2. Single Scene Classification Method SENTINEL-2 S2 image S2 PANTEX LANDSAT-8 All spectral bands + PANTEX texture feature Classifier Random Forest LANDSAT-8 Sampling Automatic sampling on Copernicus High Resolution Layer (2012) Uncertainty estimation 1 - Kappa
SENTINEL-2 Method SENTINEL-2 3. Multitemporal fusion LANDSAT-8 LANDSAT-8 Dempster-Shafer Theory : - Dealing with uncertainty Associative rule: - Combination of numerous separate information - Sentinel-2, Landsat- 8, and some more if available
SENTINEL-2 Method SENTINEL-2 LANDSAT-8 LANDSAT-8 3. Multi-source Fusion
Benefits of multi-temporal data Limitation of commision errors Urban areas Agricultural areas
Benefits of multi-source data Geometric accuracy enhancement Urban areas Imprecise edges
Change Detection Comparison HRL 2012-2015 KAPPA 0.90
Copernicus HRL imperviousness update 2011 Google Earth 2015 Sentinel-2 2012-2015 HRL Change Map 2015 HRL Imperviousness
Copernicus HRL imperviousness update 2011 Google Earth 2015 Sentinel-2 2012-2015 HRL Change Map 2015 HRL Imperviousness
Conclusion Simple method - Overcome missing data - Provide cloud-free coverage - Limited interaction with the user - Good accuracy: More overlays, less uncertainty - Multi-source ability
Conclusion Simple method Sentinel-2 abilities - Overcome missing data - Provide cloud-free coverage - Limited interaction with the user - Good accuracy: More overlays, less uncertainty - Multi-source ability - Spectral resolution: cloud extraction, Land cover classification - Spatial resolution: texture feature - Temporal resolution: high repetitiveness
Conclusion Simple method Sentinel-2 abilities - Overcome missing data - Provide cloud-free coverage - Limited interaction with the user - Good accuracy: More overlays, less uncertainty - Multi-source ability - 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.
Previous work HRL 2012 imperviousness SPOT-5 RapidEye IRS-LISS 3 2,500,000 km 2 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.
Current work Monitoring urban areas since 1985 1984-2010 SPOT 1, 2, 3, 4, 5 Landsat 5, 7 18,000 images 2015 2016 Landsat 8 Sentinel-2
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