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Remote Sensing of Snow Cover

Remote Sensing of Snow Cover. with slides from Jeff Dozier, Tom Painter. Topics in Remote Sensing of Snow. Optics of Snow and Ice Remote Sensing Principles Applications Operational Remote Sensing. FUNDAMENTALS OF REMOTE SENSING. Energy source Atmospheric interactions Target interactions

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Remote Sensing of Snow Cover

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  1. Remote Sensing of Snow Cover with slides from Jeff Dozier, Tom Painter

  2. Topics in Remote Sensing of Snow • Optics of Snow and Ice • Remote Sensing Principles • Applications • Operational Remote Sensing

  3. FUNDAMENTALS OF REMOTE SENSING • Energy source • Atmospheric interactions • Target interactions • Sensor records energy • Transmission to receiving station • Interpretation • Application

  4. Gamma Rays X rays Ultra-violet(UV) Visible (400 - 700nm) Near Infrared (NIR) Infrared (IR) Microwaves Weather radar Television, FM radio Short wave radio The EM Spectrum 10-1nm 1 nm 10-2mm 10-1mm 1 mm 10 mm 100 mm 1 mm 1 cm 10 cm 1 m 102m Violet Blue Green Yellow Orange Red

  5. C = l v, where c is speed of light, l is wavelength (m), And v is frequency (cycles per second, Hz)

  6. WAVELENGTHS WE CAN USE MOST EFFECTIVELY

  7. PIXELS: Minimum sampling area

  8. EM Wavelengths for Snow • Snow on the ground • Visible, near infrared, infrared • Microwave • Falling snow • Long microwave, i.e., weather radar • K (l = 1cm) • X (l = 3 cm) • C (l = 5 cm) • S (l = 10 cm)

  9. Different Impacts in Different Regions of the Spectrum • Visible, near-infrared, and infrared • Independent scattering • Weak polarization • Scalar radiative transfer • Penetration near surface only • ~½ m in blue, few mm in NIR and IR • Small dielectric contrast between ice and water • Microwave and millimeter wavelength • Extinction per unit volume • Polarized signal • Vector radiative transfer • Large penetration in dry snow, many m • Effects of microstructure and stratigraphy • Small penetration in wet snow • Large dielectric contrast between ice and water

  10. Visible, Near IR, IR

  11. Solar Radiation Instrument records temperature brightness at certain wavelengths

  12. 0.05 mm 0.2 mm 0.5 mm 1.0 mm 100 80 60 reflectance (%) 40 20 0 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 wavelength (mm) Snow Spectral Reflectance

  13. RADIATION CHOICES • Absorbed • Reflected • Transmitted

  14. General reflectance curves from Klein, Hall and Riggs, 1998: Hydrological Processes, 12, 1723 - 1744 with sources from Clark et al. (1993); Salisbury and D'Aria (1992, 1994); Salisbury et al. (1994)

  15. Refractive Index of Light (m) • m = n + ik • The “real” part is n • Spectral variation of n is small • Little variation of n between ice and liquid

  16. Attenuation Coefficient • Attenuation coefficient is the imaginary part of the index of refraction • A measure of how likely a photon is to be absorbed • Little difference between ice and liquid • Varies over 7 orders of magnitude from 0.4 to 2.5 uM

  17. ADVANCED VERY HIGH RESOLUTION RADIOMETER (AVHRR) • 2,400 km swath • Orbits earth 14 times per day, 833 km height • 1 kilometer pixel size • Spectral range • Band 1: 0.58-0.68 uM • Band 2: 0.72-1.00 uM • Band 3: 3.55-3.93 uM • Band 4: 10.5-11.5 uM

  18. Snow Measurement • Satellite Hydrology Program AVHRR and GOES Imaging Channels

  19. Snow Measurement • Remote Sensing of Snow Cover (NOAA 16)

  20. Snow Measurement • NOAA-15 1.6 Micron Channel

  21. Mapping of snow extent • Subpixel problem • “Snow mapping” should estimate fraction of pixel covered • Cloud cover • Visible/near-infrared sensors cannot see through clouds • Active microwave can, at resolution consistent with topography

  22. Analysis of Mixed Pixels • Assuming linear mixing, the spectrum of a pixel is the area-weighted average of the spectra of the “end-members” • For all wavelengths l, • Solve for fn

  23. Subpixel Resolution Snow Mapping from AVHRR May 26, 1995 (AVHRR has 1.1 km spatial resolution, 5 spectral bands)

  24. 1 2 3 4 5 AVHRR Fractional SCA Algorithm Execute Sub-pixel snow cover algorithm using reflectance Bands 1,2,3 Scene Evaluation: Degree of Cloud Cover over Study Basins Snow Map Algorithm Output: Mixed clouds, high reflective bare ground, and Sub-pixel snow cover Execute Atmospheric Corrections, Conversion to engineering units AVHRR Bands AVHRR (HRPT FORMAT) Pre-Processed at UCSB [NOAA-12,14,16] Thermal Mask Build Thermal Mask Build Cloud Masks using several spectral-based tests Geographic Mask Application of Cloud, Thermal, and Geographic masks to raw AVTREE output Composite Cloud Mask Masked Fractional SCA Map

  25. Landsat Thematic Mapper (TM) • 30 m spatial resolution • 185 km FOV • Spectral resolution • 0.45-0.52 μm • 0.52-0.60 μm • 0.63-0.69 μm • 0.76-0.90 μm • 1.55-1.75 μm • 10.4-12.5 μm • 2.08-2.35 μm • 16 day repeat pass

  26. Sept 2, 1993(snow in cirques only) Feb 9, 1994(after big winter storm) Apr 14, 1994(snow line 2400-3000 m) Subpixel Resolution Snow Mapping from Landsat Thematic Mapper (Rosenthal & Dozier, Water Resour. Res., 1996)

  27. snow ice rock/veg Discrimination between Snow and Glacier Ice, Ötztal Alps Landsat TM, Aug 24, 1989

  28. AVIRIS CONCEPT • 224 different detectors • 380-2500 nm range • 10 nm wavelength • 20-meter pixel size • Flight line 11-km wide • Flies on ER-2 • Forerunner of MODIS

  29. AVIRIS spectra

  30. Spectra of Mixed Pixels

  31. Subpixel Resolution Snow Mapping from AVIRIS (Painter et al., Remote Sens. Environ., 1998)

  32. GRAIN SIZE FROM SPACE

  33. EOS Terra MODIS • Image Earth’s surface every 1 to 2 days • 36 spectral bands covering VIS, NIR, thermal • 1 km spatial resolution (29 bands) • 500 m spatial resolution (5 bands) • 250 m spatial resolution (2 bands) • 2330 km swath

  34. Snow Water Equivalent • SWE is usually more relevant than SCA, especially for alpine terrain • Gamma radiation is successful over flat terrain • Passive and active microwave are used • Density, wetness, layers, etc. and vegetation affect radar signal, making problem more difficult

  35. SWE from Gamma • There is a natural emission of Gamma from the soil (water and soil matrix) • Measurement of Gamma to estimate soil moisture • Difference in winter Gamma measurement and pre-snow measurement – extinction of Gamma yields SWE • PROBLEM: currently only Airborne measurements (NOAA-NOHRSC)

  36. Snow Measurement • Airborne Snow Survey Program

  37. Snow Measurement • Airborne SWE Measurement Theory • Airborne SWE measurements are made using the following relationship: Where: C and C0 = Uncollided terrestrial gamma count rates over snow and dry, snow-free soil, M and M0 = Percent soil moisture over snow and dry, snow-free soil, A = Radiation attenuation coefficient in water, (cm2/g)

  38. Snow Measurement • Airborne SWE: Accuracy and Bias Airborne measurements include ice and standing water that ground measurements generally miss. RMS Agricultural Areas: 0.81 cm RMS Forested Areas: 2.31 cm

  39. Airborne Snow Survey Products

  40. Microwave Wavelengths

  41. Frequency Variation for Dielectric Function and Extinction Properties • Variation in dielectric properties of ice and water at microwave wavelengths • Different albedo and penetration depth for wet vs. dry snow, varying with microwave wavelength • NOTE: typically satellite microwave radiation defined by its frequency (and not wavelength)

  42. Dielectric Properties of Snow • Propagation and absorption of microwaves and radar in snow are a function of their dielectric constant • Instrumentation: Denoth Meter, Finnish Snow Fork, TDR • e = m2 and also has a real and an imaginary component

  43. (1) (2) (3) (4) (5) (6) Modeling electromagnetic scattering and absorption Snow Soil

  44. Volume Scattering • Volume scattering is the multiple “bounces” radar may take inside the medium • Volume scattering may decrease or increase image brightness • In snow, volume scattering is a function of density

  45. SURFACE ROUGHNESS • Refers to the average height variations of the surface (snow) relative to a smooth plane • Generally on the order of cms • Varies with wavelength and incidence angle

  46. SURFACE ROUGHNESS • A surface is “smooth” if surface height variations small relative to wavelength • Smooth surface much of energy goes away from sensor, appears dark • Rough surface has a lot of back scatter, appears lighter

  47. MICROWAVES WORK 24/7 • Penetrate through cloud cover, haze, dust, and all but the heaviest rain • Not scattered by the atmosphere like optical wavelengths • Work at night!

  48. ALL OBJECTS EMIT MICROWAVE ENERGY • Emitted by atmosphere • Reflected from surface • Emitted from surface • Transmitted from the subsurface through snow • DRY SNOW: attenuates subsurface energy • WET SNOW: becomes an emission source

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