Daniel Siegel
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Transcript Daniel Siegel
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)
RnGo E
RnRd + 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