Evapotranspiration Obtained from Remote Sensing Methods

Hatfield, Jerry L.

doi:10.1016/b978-0-12-024302-0.50017-5

Cited by 44 publications

(16 citation statements)

References 42 publications

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“…Various methods for calculating r a have been developed ranging from extremely elementary (a function of wind speed only) to quite rigorous ones (accounting for atmospheric stability, wind speed, surface “aerodynamic” roughness, etc.) [17, 27, 58-60], with the commonly applied one being [61]:

r_{a} = \frac{ln [(z_{a} - d) / z_{o m} - ψ_{1}] ln [(z_{a} - d) / z_{o h} - ψ_{2}]}{k^{2} u},

with neutral stability, ψ = ψ = 0.…”

Section: Overviews Of Remote Sensing-based Evapotranspiration Models mentioning

confidence: 99%

A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data

Tang

Wan

et al. 2009

Sensors

605

345

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An overview of the commonly applied evapotranspiration (ET) models using remotely sensed data is given to provide insight into the estimation of ET on a regional scale from satellite data. Generally, these models vary greatly in inputs, main assumptions and accuracy of results, etc. Besides the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance models, must rely to a certain degree on ground-based auxiliary measurements in order to derive the turbulent heat fluxes on a regional scale. We discuss the main inputs, assumptions, theories, advantages and drawbacks of each model. Moreover, approaches to the extrapolation of instantaneous ET to the daily values are also briefly presented. In the final part, both associated problems and future trends regarding these remotely sensed ET models were analyzed to objectively show the limitations and promising aspects of the estimation of regional ET based on remotely sensed data and ground-based measurements.

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r_{a} = \frac{ln [(z_{a} - d) / z_{o m} - ψ_{1}] ln [(z_{a} - d) / z_{o h} - ψ_{2}]}{k^{2} u},

with neutral stability, ψ = ψ = 0.…”

Section: Overviews Of Remote Sensing-based Evapotranspiration Models mentioning

confidence: 99%

A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data

Tang

Wan

et al. 2009

Sensors

605

345

View full text Add to dashboard Cite

show abstract

“…It costs less than when the same spatial information is obtained with conventional measurements and it is the only approach for ungauged areas where man-made measurements are extremely difficult to conduct [31,56]. Remotely sensed surface temperature can provide a surface measurement from a resolution of a few cm 2 to several km 2 from certain satellites [57]. Remote sensing based evapotranspiration estimation and its development has been reviewed from time to time [40,47,55].…”

Section: Introductionmentioning

confidence: 99%

Evapotranspiration Estimation with Remote Sensing and Various Surface Energy Balance Algorithms—A Review

2014

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Abstract:With the advent of new satellite technology, the radiative energy exchanges between Sun, Earth, and space may now be quantified accurately. Nevertheless, much less is known about the magnitude of the energy flows within the climate system and at the Earth's surface, which cannot be directly measured by satellites. This review surveys the basic theories, observational methods, and different surface energy balance algorithms for estimating evapotranspiration (ET) from landscapes and regions with remotely sensed surface temperatures, and highlights uncertainties and limitations associated with those estimation methods. Although some of these algorithms were built up for specific land covers like irrigation areas only, methods developed for other disciplines like hydrology and meteorology, are also reviewed, where continuous estimates in space and in time are needed. Temporal and spatial scaling issues associated with the use of thermal remote sensing for estimating evapotranspiration are also discussed. A review of these different satellite based remote sensing approaches is presented. The main physical bases and assumptions of these algorithms are also discussed. Some results are shown for the estimation of evapotranspiration on a rice paddy of Chiayi Plain in Taiwan using remote sensing data.

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“…1986). Hatfield (1983) reviewed several approaches based on the calculation of evaporation as the difference between the net radiation and the sensible heat flux, expressed in terms of a diffusion equation. There are serious disadvantages to this method, however, including the difficulty of measuring the surface temperature accurately and establishing the value of the diffusion coefficient (e.g.…”

Section: Scaling and Process At The Land Surfacementioning

confidence: 99%

Atmospheric physiography and meteoronomical modelling: the future role of geographers in understanding climate

Henderson‐Sellers

1989

Australian Geographer

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Evapotranspiration Obtained from Remote Sensing Methods

Cited by 44 publications

References 42 publications

A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data

A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data

Evapotranspiration Estimation with Remote Sensing and Various Surface Energy Balance Algorithms—A Review

Atmospheric physiography and meteoronomical modelling: the future role of geographers in understanding climate

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