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Remote Sensing of Evapotranspiration with MODIS

Remote Sensing of Evapotranspiration with MODIS. Daniel Siegel. What is MODIS?. Moderate-Resolution Imaging Spectroradiometer Launched in 1999 aboard the EOS AM (Terra); EOS PM (Aqua) followed in 2002 Monitors 36 spectral bands between 0.4  m and 14.4  m Images entire Earth

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Remote Sensing of Evapotranspiration with MODIS

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  1. Remote Sensing of Evapotranspiration with MODIS Daniel Siegel

  2. What is MODIS? • Moderate-Resolution Imaging Spectroradiometer • Launched in 1999 aboard the EOS AM (Terra); EOS PM (Aqua) followed in 2002 • Monitors 36 spectral bands between 0.4 m and 14.4 m • Images entire Earth every 1-2 days at 1 km resolution

  3. Why use MODIS? • ASTER and Landsat have 60 m resolution but available once a month at best • Geostationary satellites capture data with 15 min frequency but 5 km resolution

  4. Relevent MODIS Products • MOD11 - Surface temperature and emissivity • MOD43 - Albedo • MOD15 - Leaf Area Index (LAI) • MOD13 - NDVI • Mod07 - Atmospheric stability; temperature and vapor pressure at 20 vertical levels • MOD03 - Lattitude, longitude, ground elevation, solar zenith angle, satellite zenith angle and azimuth angle

  5. NDVI First measured by the original Landsat in 1972 Measurement of a pixel’s “greenness”

  6. Accessing MODIS Data • Level 1 and Atmosphere Archive and Distribution System (LAADS) • Warehouse Inventory Search Tool (WIST) submits orders via EOS ClearingHouse (ECHO) • HDF can interface with C, Fortran, Perl, MATLAB, IDL or Mathmatica

  7. WIST

  8. Surface Energy Balance System (Su 2002) RnGo E RnRd + Ld - s Go Rd + Ld - s Go = Rn[c + (1-fc)(s - c)] s c = Measured by MODIS fc = percentage of ground covered by vegetation = Variables

  9. Calculating H = cannot be measured remotely

  10. z0m and z0h Can vary by several orders of magnitude Using LAI and wind speed, z0m can be calculated as a function of canopy height following Massman (1997) Wind speed Zoh = zom/exp(kB-1)

  11. Limiting Cases Hdry = Rn - Go Constraining the result between these values decreases the uncertainty considerably

  12. Summary: Local Variables Rd - Measured with a radiation sensor Ld - Stephen-Boltzman equation using air temp Wind speed and canopy height must be measured on site

  13. Results

  14. Triangle Method (Jiang and Islam 2001) NDVI, soil moisture)

  15. Results Original Priestly-Taylor Eq Triangle Method

  16. Complementary Model (Venturini & Islam 2007) From Priestly-Taylor ET + ETpot = 2Etwet (Bouchet 1963) From Penman Uses temp profile as surrogate for humidity deficit EF = ET / (Rn-G)

  17. Benefits of Isolating EF • Rn is a large source of error because of atmospheric interference and cloud cover • Generally constant during daytime • Useful for mapping drought conditions

  18. Results

  19. Future Research • Removing cloud-contaminaed pixels biases results, ignores diffuse radiation • Nocturnal transpiration • 3°K error in in Ts causes 75% error in H

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