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Remote sensing of evapotranspiration using automated calibration: development and testing in the state of FloridaUnknown Date (has links)
Thermal remote sensing is a powerful tool for measuring the spatial variability of
evapotranspiration due to the cooling effect of vaporization. The residual method is a
popular technique which calculates evapotranspiration by subtracting sensible heat from
available energy. Estimating sensible heat requires aerodynamic surface temperature
which is difficult to retrieve accurately. Methods such as SEBAL/METRIC correct for
this problem by calibrating the relationship between sensible heat and retrieved surface
temperature. Disadvantage of these calibrations are 1) user must manually identify
extremely dry and wet pixels in image 2) each calibration is only applicable over limited
spatial extent. Producing larger maps is operationally limited due to time required to
manually calibrate multiple spatial extents over multiple days. This dissertation develops
techniques which automatically detect dry and wet pixels. LANDSAT imagery is used
because it resolves dry pixels. Calibrations using 1) only dry pixels and 2) including wet
pixels are developed. Snapshots of retrieved evaporative fraction and actual evapotranspiration are compared to eddy covariance measurements for five study areas in
Florida: 1) Big Cypress 2) Disney Wilderness 3) Everglades 4) near Gainesville, FL. 5)
Kennedy Space Center. The sensitivity of evaporative fraction to temperature, available
energy, roughness length and wind speed is tested. A technique for temporally
interpolating evapotranspiration by fusing LANDSAT and MODIS is developed and
tested.
The automated algorithm is successful at detecting wet and dry pixels (if they
exist). Including wet pixels in calibration and assuming constant atmospheric
conductance significantly improved results for all but Big Cypress and Gainesville.
Evaporative fraction is not very sensitive to instantaneous available energy but it is
sensitive to temperature when wet pixels are included because temperature is required for
estimating wet pixel evapotranspiration. Data fusion techniques only slightly
outperformed linear interpolation. Eddy covariance comparison and temporal
interpolation produced acceptable bias error for most cases suggesting automated
calibration and interpolation could be used to predict monthly or annual ET. Maps
demonstrating spatial patterns of evapotranspiration at field scale were successfully
produced, but only for limited spatial extents. A framework has been established for
producing larger maps by creating a mosaic of smaller individual maps. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection
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