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Space-Time Series of MODIS Snow Cover Products

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Presentation on theme: "Space-Time Series of MODIS Snow Cover Products"— Presentation transcript:

1 Space-Time Series of MODIS Snow Cover Products
Jeff Dozier, James E Frew, Thomas H Painter

2 Topics Spectral reflectance of snow and its variability
Implications for energy balance of snowpack Remote sensing of snow-covered area and albedo Fractional (subpixel) snow cover and grain size from MODIS, every day Time series corrections for clouds, viewing geometry, and other noise Available for use by others for hydrologic models

3 Seasonal solar radiation, Mammoth Mountain

4 Snow is a collection of scattering grains

5 Snow spectral reflectance and absorption coefficient of ice

6 Spectra with MODIS “land” bands

7 MODIS image of Sierra Nevada
EOS Terra MODIS 07 March 2004 MOD09 Surface Reflectance

8 Snow covered-area and grain size – Sierra Nevada (the MODSCAG model)

9 Spectral mixture analysis, generalized
Spectral mixture equation, per pixel Spectral residuals, per pixel RMS error, per pixel MODSCAG spectrally mixes with range of snow endmembers and chooses the result with the least RMS error for that pixel

10 Based on work with AVIRIS: Snow-covered area in the Tokopah Basin (Kaweah River drainage)
21 May 1997 05 May 1997 18 June 1997 20 km

11 Grain size in the Tokopah Basin (Kaweah River drainage)
21 May 1997 05 May 1997 18 June 1997 20 km

12 Analysis of MODIS data for a single day

13 But some days are cloudy

14 Noisy variability caused by look angle, small clouds, vegetation, topography
detail Vegetation causes differences in view angle

15 Variability of snow cover and grain size at a pixel

16 Need to interpolate and smooth to fill the space-time cube
Raw snow cover Interpolated snow cover

17 Time series, Tuolumne basin, Oct 2004 – July 2005

18 Comparison of fractional snow cover with “binary” (pixel snow-covered when f ≥ 0.5)

19 Products available from the Snow Server http://www.snow.ucsb.edu
Fractional snow-covered area, grain size (and contaminants) from daily MODIS images Quality flags for cloud cover, highly oblique viewing Fractional coverage of other endmembers Best estimate of snow-covered area and broadband albedo on that date Extrapolating from previous values to that date and smoothing End-of-season reanalysis of daily snow-covered area and broadband albedo Interpolation, smoothing, comparison with in situ snow pillow data

20 Delivery options (need your opinion)


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