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
every 1-2 days at 1 km
resolution
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
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
NDVI
First measured by the
original Landsat in 1972
Measurement of a
pixel’s “greenness”
RIR  Rred
NDVI 
RIR  Rred
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
WIST
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
= Variables
fc = percentage
of ground covered
by vegetation
Calculating H
= cannot be measured remotely
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)
Zoh = zom/exp(kB-1)
Wind speed
Limiting Cases
Hdry = Rn - Go
Constraining the result between these values
decreases the uncertainty considerably
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
Results
Triangle Method
(Jiang and Islam 2001)

 
E  (Rn  G)

   

 min  0

max 

  f ( NDVI, soil moisture)


des
 f (Ta )
dT T Ta
Results
Triangle Method
Original Priestly-Taylor Eq
Complementary Model
From Priestly-Taylor 2007)
ET + ETpot = 2Etwet
(Venturini & Islam
(Bouchet 1963)
From Penman
Uses temp profile as surrogate
for humidity deficit
EF = ET / (Rn-G)
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
Results
Future Research
Removing cloud-contaminaed pixels
biases results, ignores diffuse radiation
Nocturnal transpiration
3°K error in in Ts causes 75% error in
H