Evaluation of Algorithms for the Retrieval of Snow Grain Size from Optical Satellite Data

1. Evaluation of Algorithms for the Retrieval of Snow Grain Size from Optical Satellite Data 8th Circumpolar Symposium on Remote Sensing of Polar Environments, 8-12 June 2004, Chamonix Hans Koren, Jostein Amlien, Rune Solberg, Norwegian Computing Center (NR)

2. Contents • Background • Algorithms • Validations • Future investigations • Conclusion

3. Why studying snow from satellites? • Indications on climate changes • Hydro power production • Floods • Avalanches • Skiing conditions

4. Snow parameters retrievable from satellites? • Snow cover area • Snow depth • Snow temperature • Snow wetness • Snow grain size

5. Reflectance from snowdepends on • wavelength • sun elevation angle • terrain angle • depth and density of the snowpack • snow grain size ( especially infrared light) • impurities ( especially visible light) • liquid water

6. Reflectance as a function of wavelength for different grain sizes

7. WavelengthGrain size 0.86 µm 1.05 µm 1.24 µm 1.7 µm 50 µm 3.3 1.2 0.57 0.19100 µm 4.8 1.8 0.83 0.27200 µm 6.9 2.6 1.2 0.39500 µm 11 4.1 1.9 0.651000 µm 16 5.8 2.6 1.02000 µm 22 8.1 3.7 1.8 Penetration depth in cm

8. Scattering model • Scattering properties of irregularly shaped grains are mimicked by Mie calculations for an ”equivalent sphere” • The grains are not oriented • Mean convex radius as size indicator • Measured grain size not always equivalent to the optical grain size found by scattering models

9. Snow grains

10. Reflectance model NC numerical counts calibration parameters solar irradiance solar zenith angle local slope angle

11. Modelled reflectanceLandsat infrared channels(Bourdelles & Fily 1993)

12. Histograms of snow grain sizesLandsat infrared channels

13. Modelled reflectanceAVIRIS (Li et al. 2001)

14. Histograms of grain sizesAVIRIS

15. Ratio between TM channels Precise slope values are difficult to obtain in mountain areas. Using ratios between channels instead of a single channel minimizes this effect because the slope is independent of the channel. We will use the ratio Rij defined as where TM are the apparent reflectance or the ground reflectance for each channel.

16. Landsat channel ratiosComparison between modeled and measured ratios R24 (a), R45 (b), and R47 (c). The curves are shown for various geometrical conditions. (Fily et al. 1997).

17. TM/ETM+ vs. MODIS • Landsat TM/ETM+: - resolution 30 m - 7 channels - expensive - 1-3 images in 16 days • Terra/Aqua MODIS: - resolution 250 m (SCA) 500 m (SGS) 1000 m (STS) - 36 channels - free - more images each day

18. Grain size index from Landsat ETM+ and MODIS • Landsat R47 channel 4: 0.775 – 0.900 µm channel 7: 2.09 – 2.35 µm • MODIS R27 channel 2: 0.841 – 0.876 µm channel 7: 2.105 – 2.155 µm

19. Grain size index from Landsat 7

21. Snow surface temperature, grain size index, and snow cover area STS SGS SCA 2003.04.22 2003.05.11 2003.05.31

22. | Snow surface temperature and snow grain size index HH-Heimdalshø (1840 m), VF-Valdresflya (1380 m) Precipitation Beito (blue), Skåbu (red)

23. Absorption Feature

24. Scaled Band Area methodNolin & Dozier (2000)

25. Scaled Band Area method

26. Scaled Band Area method

27. Future studies? • Hyperion, hyperspectral data, absorption feature • MODIS, channel 5: 1230 – 1250 nm channel 26: 1360 – 1390 nm

28. Conclusions • Estimation of snow grain size can be obtained from the normalised difference of infrared channels for Landsat TM and ETM+, and MODIS • Further investigations necessary to get calibration parameters for precise grain size estimates • Hyperspectral satellite data can be used to determine grain size from the absorption feature • More studies using other MODIS channels and hyperspectral data