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Remote Sensing of Evapotranspiration with MODIS

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Title: Remote Sensing with MODIS Author: Daniel Siegel Last modified by: maidment Created Date: 4/23/2010 1:41:58 AM Document presentation format – PowerPoint PPT presentation

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Title: Remote Sensing of Evapotranspiration with MODIS


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 pixels 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???????Rd ?Ld - ???s?
Rn??Go ???????E
Go ????????????????Rd ?Ld - ???s?
Go Rn?c (1-fc)(?s - ?c)
?s????????? ?c??????????
fc percentage of ground covered by
vegetation
Measured by MODIS
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
(No Transcript)
15
Triangle Method (Jiang and
Islam 2001)
NDVI, soil moisture)
16
(No Transcript)
17
Results
Original Priestly-Taylor Eq
Triangle Method
18
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)
19
(No Transcript)
20
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

21
Results
22
Future Research
  • Removing cloud-contaminaed pixels biases results,
    ignores diffuse radiation
  • Nocturnal transpiration
  • 3K error in in Ts causes 75 error in H
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