4. Test sites - Description Bolzano The test areas in South Tyrol. The pink markers indicate the placement of the manual ground measurement stations , while the green ones of the automatic ground measurement stations

5. COSMO-SkyMed characteristics and Test sites images COSMO-SkyMed Main characteristics Band X – 9.60 GHz Wavelength 3.12 cm Polarization HH, VV, HH-HV, VV-VH Swath 100 km Revisit Time 8 days Radiometric accuracy < 1 dB Acquisition mode Spotlight (Enhanced) Stripmap (Himage, PingPong) ScanSAR (WideRegion, HugeRegion) Geometrical Resolution (ground range, m - azimuth, m) ≤ 1.0 - ≤1.0 Spotlight (Enhanced) ≤ 5.0 - ≤5.0 Stripmap (Himage) ≤ 20.0 - ≤20.0 Stripmap (PingPong) ≤ 30.0 - ≤30.0 ScanSAR (WideRegion) ≤ 100.0 - ≤100.0 ScanSAR (HugeRegion) Test sites Acquisition Technical characteristics test site South Tyrol 1 (Ulten valley) South Tyrol 2 (Brennero) mode Stripmap PingPong Stripmap PingPong Level 1A-SCSB 1A-SCSB swath 30km x 30km 30km x 30km Preferred incidence angle >25° e <35° >25° e <35° image area 30 km x 30 km 30 km x 30 km Number of scene 22 22 look right right orbit asc or desc asc or desc polarization VV, VH VV, VH

6. COSMO-SkyMed data sets List of the acquired COSMO-SkyMed images: in green are indicated the “melting season” data; in black the “winter season” data; in blue the “summer season” (snow free) images. Area Date Mode Polarization Look Side Pass Beam Proc. Level Ulten 20100426 Ping Pong VV/VH Right Ascending 10 1A-SCSB Ulten 20100427 Ping Pong VV/VH Right Ascending 10 1A-SCSB Ulten 20100901 Ping Pong VV/VH Right Ascending 10 1A-SCSB Ulten 20100902 Ping Pong VV/VH Right Ascending 10 1A-SCSB Ulten 20100917 Ping Pong VV/VH Right Ascending 10 1A-SCSB Ulten 20101128 Ping Pong VV/VH Right Ascending 10 1A-SCSB Ulten 20101223 Ping Pong VV/VH Right Ascending 10 1A-SCSB Ulten 20110123 Ping Pong VV/VH Right Ascending 10 1A-SCSB Ulten 20110312 Ping Pong VV/VH Right Ascending 10 1A-SCSB Ulten 20110405 Ping Pong VV/VH Right Ascending 10 1A-SCSB Brenner 20110404 Ping Pong VV/VH Right Descending 11 1A-SCSB Brenner 20110421 Ping Pong VV/VH Right Descending 11 1A-SCSB Brenner 20110424 Ping Pong VV/VH Right Descending 11 1A-SCSB Brenner 20110506 Ping Pong VV/VH Right Descending 11 1A-SCSB Brenner 20110507 Ping Pong VV/VH Right Descending 11 1A-SCSB

8. Detecting snow cover area with SAR images Distribution for “snow” and “ no snow” areas The method derived from Nagler (1996) is based on the difference in backscattering behavior between snow covered and snow free images.

12. Threshold for wet snow classification Distribution of ratio R for different land cover classes Grassland Rocks Forest Threshold for mapping wet snow with CSK Frost (7 × 7) ratio-images in dependence of polarization and land cover Rock (dB) Grassland (dB) VV -2.3 -2.2 VH -1.3 -2.0

15. Preprocessing outputs COSMO-SkyMed geocoded image, March 12 th 2011, VV COSMO-SkyMed geocoded image, March 12 th 2011, VH COSMO-SkyMed -ASI ©– All rights reserved

16. Time series of CSK snow maps: November COSMO-SkyMed November 28 th 2011 MODIS snow line November 26 th 2011 Snow No Snow

17. Time series of CSK snow maps: January COSMO-SkyMed January 23 rd 2011 MODIS snow line January 21 st 2011 Snow No Snow

18. Time series of CSK snow maps: March COSMO-SkyMed March 12 th 2011 LANDSAT March 6 th 20011 Snow No Snow

19. Time series of CSK snow maps: April COSMO-SkyMed April 5 th 2011 LANDSAT April 7 th 20011 Snow No Snow

20. Comparison CSK and Landsat snow cover maps -3.0 dB March 12 th 2011 April 5 th 2011 % NO SNOW - LANDSAT SNOW - LANDSAT NO SNOW - CSK 53.0 2.4 SNOW - CSK 46.9 97.6 % NO SNOW - LANDSAT SNOW - LANDSAT NO SNOW - CSK 70.4 6.3 SNOW - CSK 29.6 93.7 Snow for LANDSAT and CSK No Snow for LANDSAT and CSK Snow only for CSK Snow only for LANDSAT

21. Comparison CSK and Landsat snow cover maps -3.0 dB March 12 th 2011 April 5 th 2011 % NO SNOW - LANDSAT SNOW - LANDSAT NO SNOW - CSK 53.0 2.4 SNOW - CSK 46.9 97.6 % NO SNOW - LANDSAT SNOW - LANDSAT NO SNOW - CSK 70.4 6.3 SNOW - CSK 29.6 93.7 Snow for LANDSAT and CSK No Snow for LANDSAT and CSK Snow only for CSK Snow only for LANDSAT

22. Probability of error in change detection technique Probability of error (in %) of the ratio method versus the change in radar backscatter (in dB) between two dates, for a number of looks N varying between 1 and 256 (from Rignot & van Zyl, 1993). Commission error Omission error

23. Probability of error map No snow Snow < 5% 5% - 10% 10% - 25% 25% - 50% > 50%

24. Comparison between e.m. model simulations and CSK backscattering coefficients By using the IEM model, the main hypothesis is that we are dealing with surface scattering. This hypothesis is verified only the case of wet snow. λ (cm) = 3.1 l (cm) = 5.0 -10.0 ε snow = [1.5-2.1] s (cm) = 0.5 – 1.0

25. Conclusions and future steps The possibility to discriminate wet snow from snow-free areas in COSMO-SkyMed X-band images using a multi-temporal approach was studied in dependence of different key parameters. SCA increases up to 8% when a threshold of -2.3 dB is applied instead of a threshold of -3.0 dB. Analyzing the dependence of the threshold on the reference image showed that the threshold, and hence the classification result, strongly depends on the reference image. An average of suitable reference images is advisable in order to reduce the impact of conditions deriving from a single image. The snow cover maps can be associated to a probability of error map which indicates the level of error in the different areas. Future steps will include: The analysis will be extended to another test area where the CSK acquisitions were in the afternoon. The multi-temporal approach will be extended to VH polarization. A comparison with TERRASARX images is foreseen The problem of the snow cover extension beyond wet snow will be faced.

26. Thank you for the attention! Comments/questions?