Satellite estimates of evapotranspiration on the 100-m pixel scale
Norman, J.M.; Daniel, L.C.; Diak, G.R.; Twine, T.E.; Kustas, W.P.; French, A.N.; Schmugge, T.J.
Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International
Volume 4, Issue , 2000 Page(s):1483 - 1485 vol.4
Digital Object Identifier 10.1109/IGARSS.2000.857247
Summary:Estimating crop evapotranspiration (Et) from satellite
observations has proven to be challenging task, because the single
“snapshot” images routinely obtained from
high-spatial-resolution satellites do not provide enough temporal
information. A new two-step approach (called disaggregated-ALEXI or
DisALEXI) has been developed to combine the high temporal resolution of
GOES with the high spatial resolution of Landsat to estimate crop Et on
the 20-100-m scale without using any local observations. The first step
uses surface brightness-temperature-change measurements about four hours
apart in the morning from the GOES satellite to estimate average Et on
the scale of about 5 km with an algorithm known as ALEXI. The second
step disaggregates the GOES 5-km Et estimates by using
high-spatial-resolution images of vegetation-index and surface
temperature, such as from aircraft or Landsat, to produce 30-m maps of
crop Et. Preliminary evaluations suggest that crop remote Et estimates
agree within 15 to 50% of surface measurements, where the 50% error is
on a small flux (150 W m-2). The DisALEXI approach will be
useful for adjusting parameters or updating calibrations of
high-spatial-resolution models used for management decisions in
precision farming, because no local measurements are necessary, and
spatial patterns will be determined with high precision even if the
absolute accuracy may only be 30%
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