The document summarizes a project using spaceborne fully polarimetric time-series datasets from Radarsat-2 and ALOS for land cover analysis and monitoring of wetlands. The objectives were to delineate wetlands and map vegetation, identify agricultural practices, and determine water cycles and levels. Ground truth campaigns were conducted including soil moisture and roughness measurements. Initial qualitative analysis of the Radarsat-2 data showed polarimetric descriptors and classifications could distinguish flooded areas with 78-94% accuracy. Optical data from ALOS provided complementary information and 88-99% classification accuracy. Further inversion of parameters like soil moisture from time-series datasets and data fusion of radar and optical data was outlined.

1. SPACEBORNE FULLY POLARIMETRIC TIME-SERIES DATASETS FOR LAND COVER ANALYSIS IETR – UMR CNRS 6164 SAPHIR Team University of Rennes 1 Rennes, France IGARSS – 2010 SAPHIR LETG – UMR CNRS 6554 COSTEL University of Rennes 2 Rennes, France Cécile MARECHAL, Eric POTTIER, Laurence HUBERT-MOY Samuel CORGNE, Sophie ALLAIN, Stéphane MERIC

2. Objectives of the project Radarsat 2 dataset and ALOS images presentation Ground thruth campaigns 1st Qualitative analysis results Outlook and summary Contents

3. Objectives Evaluating Radarsat 2 data: - to delineate wetlands & Map vegetation ; - Identify agricultural practices; - determine watercycle and waterlevels. Evaluate the contribution of both very high resolution optical data and radar data for wetlands delineation and characterization .

4. Regions permanently or seasonaly flooded; Transition area (ecotone): mosaic of ecosystems; Important role in the regulation of water flow, protection of the water quality. Prevention of the reduction and degradation to maintain the diversity of species , habitats (nesting area for migratory birds). In view of the strong dynamic of this environment, a remote sensing multitemporal study is essential to monitor of wetland. Wetlands

5. SOAR – EU Evaluation of RADARSAT-2 quad-pol data for functional assessment of wetlands (Id6842) Polarimetric SAR data analysis Biophysical parameter inversion (soil moisture) Optical data analysis Image geocoding Ground truth campaigns SOAR – EU Project COSTEL SAPHIR

6. The Sougéal Marsh and Mesnil Marsh: Flooded by the rising waters in the Couesnon river; Entirely made up of grazing land ; Protected by the RAMSAR community agreement (the protection of humid biotopes) and also ZNIEFF , ZICO , Natura 2000 , ZPS ; Bird observatory (migrating birds) : it is highly important to maintain the humid nature of this sector from an ornithological point of view . Work Area Pleine Fougeres

7. Objectives of the project Radarsat 2 dataset and ALOS images presentation Ground thruth campaigns 1st Qualitative analysis results Outlook and summary Contents

8. Pleine Fougères – RS2 PolSAR Footprint

9. Pleine Fougères – RS2 PolSAR Quad Pol Fine Mode FQ 23 (44°) Pauli RGB

10. Pleine Fougères – RS2 PolSAR

11. Pleine Fougères – RS2 PolSAR Quad Pol Fine Mode FQ 23 (44°) Pauli RGB

12. SOAR – EU PolSAR Time-series analysis 22 / 02 / 2010 16 / 03 / 2010 11 / 04 / 2010 05 / 05 / 2010     29 / 05 / 2010 22 / 06 / 2010 16 / 07 / 2010 09 / 08 / 2010 02 / 09 / 2010 26 / 09 / 2010 20 / 10 / 2010 13 / 11 / 2010    Pleine Fougères – RS2 PolSAR 12 Images Repeat Time: 24 days

13. Sougeal Le Mesnil Sougeal Le Mesnil Pauli RGB Animation Temporal changes Pleine Fougères – RS2 PolSAR

14. Span 22 / 02 / 10 18 / 03 / 10 11 / 04 / 10 Span 22 / 02 / 10 18 / 03 / 10 22 / 06 / 10 Sougeal Le Mesnil Span Pleine Fougères – RS2 PolSAR Color-composite of the span images: 3 dates

15. Pleine Fougères – ALOS PRISM 14 March 2010

16. Pleine Fougères – ALOS PRISM 14 March 2010 ALOS

17. Pleine Fougères – ALOS AVNIR 14 March 2010 ALOS

18. Pleine Fougères – ALOS AVNIR 14 March 2010 ALOS

19. Objectives of the project Radarsat 2 dataset and ALOS images presentation Ground thruth campaigns 1st Qualitative analysis results Outlook and summary Contents

20. Ground Truth Campaigns Soil moisture measurement with Time Domain Reflectometer

21. Ground Truth Campaigns Measurement points Differential GPS localisation Watershed Transect GPS Geocoded Images

22. Ground Truth Campaigns

23. Watershed Transect Ground Truth Campaigns Terrestrial LIDAR Roughness estimation

24. Ground Truth Campaigns Fully polarimetric scattering measurements POSAR scatterometer system Compare with Radarsat-2 measurements Calibrate data inversion algorithms Validate physical parameter retrieval

25. Ground Truth Campaigns Set up 5 Trihedral Calibrators (Differential GPS localisation) Assess Radarsat-2 calibration Validate the geocoding procedure

26. Objectives of the project Radarsat 2 dataset and ALOS images presentation Ground thruth campaigns 1st Qualitative analysis results Outlook and summary Contents

27. Radarsat-2 Pre-Processing Data Extract [ T3 ] Post-Processing Methodology Polarimetric Decomposition Theorems Polarimetric descriptor sensitive to the Temporal Variability of the marsh flooded areas 1st Qualitative analysis Pauli RGB RADARSAT 2 H A 

28. Entropy Entropy Coeff. Of Variation Sougeal Le Mesnil Sougeal Sougeal Le Mesnil Le Mesnil POLSAR Descriptor

29. Radarsat-2 Pre-Processing Data Extract [ T3 ] Post-Processing Methodology Supervised Classification ML – Wishart Classification procedure 1st Qualitative analysis Pauli RGB ML - Wishart RADARSAT 2

30. Urban area Open water Flooded area Grassland Land Low chlorofilian activity Forest Medium chlorofilian activity Supervised ML – Wishart Classification Confusion matrix: 78% to 94% of good classification POLSAR Classification

31. Radarsat-2 Pre-Processing Data Extract [ T3 ] Post-Processing Methodology GeoCoding T3 Matrix 46 G.C.P rms: 0.9 pix Pauli RGB ML - Wishart 1st Qualitative analysis RADARSAT 2

32. GeoCoding Radarsat-2 (Slant Range) ALOS – AVNIR (Ground Range) POLSAR Geocoding

33. Urban area Open water Flooded area Grassland Land Low chlorofilian activity Forest Medium chlorofilian activity Supervised ML – Wishart Classification Radarsat-2 POLSAR Classification

34. Urban area Open water Flooded area Grassland Land Low chlorofilian activity Forest Medium chlorofilian activity Supervised Classification ALOS – AVNIR (4 bands) Optical Classification Confusion matrix: 88% to 99% of good classification

35. RADAR – OPTICAL Complementary Information DATA FUSION (?) Outlook 14 March 2010 16 March 2010

36. Outlook: Data inversion for parameter retrieval ( soil moisture - roughness ) from Radarsat-2 time-series datasets; - Cross Validation using ground truth campaigns (soil moisture + roughness measurements); - Data fusion : radar & optical data Summary More case studies will contribute to an improved understanding of useful Polarimetric SAR analysis techniques. First results very promissive : These results show the potential of polarimetric SAR data for mapping land use & land cover and monitor wetland areas.

37. Acknowledgments Cécile Frédéric Jean Sébastien

38. Q uestions ? HH…VV… HV … VH