A methodology for estimation of surface evapotranspiration over large areas using remote sensing observations

Jiang, Lide; Islam, Shafiqul

doi:10.1029/1999gl006049

Cited by 269 publications

(245 citation statements)

References 11 publications

(9 reference statements)

Supporting

Mentioning

235

Contrasting

Unclassified

Order By: Relevance

“…Previous studies have shown that the parameter α PT varies depending upon the differences in meteorological conditions [23]. However, an overall mean value of 1.26 for typically observed atmospheric conditions is well accepted in many studies and it is relatively insensitive to small changes in atmospheric parameters [3,6,8,14,24,25]. Thus, the value of 1.26 is adopted in this study for determining α PT .…”

Section: Priestly-taylor Formula and Its Extensionmentioning

confidence: 99%

“…It is noteworthy that parameter φ, although it looks similar to the α PT , encompasses a wide range evaporative conditions and can take a range of values [8,14]. Jiang and Islam (2001) suggested a two-step interpolation scheme to obtain the φ value using a triangular LST/FVC space [8].…”

Section: Priestly-taylor Formula and Its Extensionmentioning

confidence: 99%

“…Generally, the one-source models utilize the LST/FVC space to interpolate the effective Priestly-Taylor parameter in the Priestly-Taylor formula for calculating EF [3,6,8,14,15], whereas the two-source models use the LST/FVC space to decompose LST into vegetation and soil component temperatures (T v and T s ) and subsequently calculate EF and its vegetation and soil components (EF v and EF s ) [16][17][18]. The one-source models assume land surface as a single uniform layer which produce significant errors when applied to partially vegetated landscapes [18].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Two-Source Model for Estimating Evaporative Fraction (TMEF) Coupling Priestley-Taylor Formula and Two-Stage Trapezoid

Sun

2016

Remote Sensing

View full text Add to dashboard Cite

Remotely sensed land surface temperature and fractional vegetation coverage (LST/FVC) space has been widely used in modeling and partitioning land surface evaporative fraction (EF) which is important in managing water resources. However, most of such models are based on conventional trapezoid and simply determine the wet edge as air temperature (T a ) or the lowest LST value in an image. We develop a new Two-source Model for estimating EF (TMEF) based on a two-stage trapezoid coupling with an extension of the Priestly-Taylor formula. Latent heat flux on the wet edge is calculated with the Priestly-Taylor formula, whereas that on the dry edge is set to 0. The wet and dry edges are then determined by solving radiation budget and energy balance equations. The model was evaluated by comparing with other two models that based on conventional trapezoid (i.e., the Two-source Trapezoid Model for Evapotranspiration (TTME) and a One-source Trapezoid model for EF (OTEF)) in how well they simulate and partition EF using MODIS products and field observations from HiWATER-MUSOEXE in 2012. Results show that the TMEF outperforms the other two models, where EF mean absolute relative deviations are 9.57% (TMEF), 15.03% (TTME), and 30.49% (OTEF).

show abstract

Section: Priestly-taylor Formula and Its Extensionmentioning

confidence: 99%

Section: Priestly-taylor Formula and Its Extensionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Two-Source Model for Estimating Evaporative Fraction (TMEF) Coupling Priestley-Taylor Formula and Two-Stage Trapezoid

Sun

2016

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Widely used algorithms can be divided into four categories: simplified empirical regression methods [5,6], trapezoid or triangle feature space methods [7][8][9], surface energy balance based (single-and dual-source) models [10][11][12][13][14], and the traditional evapotranspiration estimation approaches, for instance the Penman-Monteith equation and Priestley-Taylor equation, combined with remote sensing [4,[15][16][17][18][19]. Efforts have been made using different models mainly based on energy balance equation and taking the evapotranspiration as the residual on way or the other in combination with optical remote sensing, i.e., using land surface temperature (LST) retrieved from thermal infrared bands as the main driving variable [20][21][22], of which some case studies were conducted in the Heihe River basin [9,23,24].…”

Section: Introductionmentioning

confidence: 99%

Monitoring of Evapotranspiration in a Semi-Arid Inland River Basin by Combining Microwave and Optical Remote Sensing Observations

2015

Remote Sensing

110

View full text Add to dashboard Cite

Abstract:As a typical inland river basin, Heihe River basin has been experiencing severe water resource competition between different land cover types, especially in the middle stream and downstream areas. Terrestrial actual evapotranspiration (ETa), including evaporation from soil and water surfaces, evaporation of rainfall interception, transpiration of vegetation canopy and sublimation of snow and glaciers, is an important component of the water cycle in the Heihe River basin. We developed a hybrid remotely sensed ETa estimation model named ETMonitor to estimate the daily actual evapotranspiration of the Heihe River basin for the years 2009-2011 at a spatial resolution of 1 km. The model was forced by a variety of biophysical parameters derived from microwave and optical remote sensing observations. The estimated ETa was evaluated using eddy covariance (EC) flux observations at local scale and compared with the annual precipitation and the MODIS ETa product (MOD16) at regional scale. The spatial distribution and the seasonal variation of the estimated ETa were analyzed. The results indicate that the estimated ETa shows reasonable spatial and temporal patterns with respect to the diverse cold and arid landscapes in the upstream, middle stream and downstream regions, and is useful for various applications to improve the rational allocation of water resources in the Heihe River basin. OPEN ACCESSRemote Sens. 2015, 7 3057

show abstract

“…However, in our study we do not use a set of spectral responses for high resolution pixels, but instead we utilize a sub-sampling kernel retrieved from a high resolution scene that describes quasi-stable radiometric properties of the land surface, namely, the effective emissivity derived from the land cover map type and vegetation index in the form of fractional vegetation cover (FVC). In particular, we assume that estimation of LST high resolution value should be done with taking into account the local effective emissivity high resolution value, but not necessarily with an assumption of the global linear dependency between emissivity and LST like in the PBIM method [20] (subsection 2.2), as suggested by Jiang and Islam [21,22]. Instead, we introduce and estimate a vector of weights that permits more flexible, and adjusted to local conditions, modeling of dependency between emissivity and LST.…”

Section: Introductionmentioning

confidence: 99%

Optimized AVHRR land surface temperature downscaling method for local scale observations: case study for the coastal area of the Gulf of Gdańsk

Chybicki¹,

Łubniewski²

2017

Open Geosciences

View full text Add to dashboard Cite

Satellite imaging systems have known limitations regarding their spatial and temporal resolution. The approaches based on subpixel mapping of the Earth's environment, which rely on combining the data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution, are of considerable interest. The paper presents the downscaling process of the land surface temperature (LST) derived from low resolution imagery acquired by the Advanced Very High Resolution Radiometer (AVHRR), using the inverse technique. The effective emissivity derived from another data source is used as a quantity describing thermal properties of the terrain in higher resolution, and allows the downsampling of low spatial resolution LST images. The authors propose an optimized downscaling method formulated as the inverse problem and show that the proposed approach yields better results than the use of other downsampling methods. The proposed method aims to find estimation of high spatial resolution LST data by minimizing the global error of the downscaling. In particular, for the investigated region of the Gulf of Gdańsk, the RMSE between the AVHRR image downscaled by the proposed method and the Landsat 8 LST reference image was 2.255 ∘ C with correlation coefficient R equal to 0.828 and Bias = 0.557 ∘ C. For comparison, using the PBIM method, it was obtained RMSE = 2.832 ∘ C, R = 0.775 and Bias = 0.997 ∘ C for the same satellite scene. It also has been shown that the obtained results are also good in local scale and can be used for areas much smaller than the entire satellite imagery scene, depicting diverse biophysical conditions. Specifically, for the analyzed set of small sub-datasets of the whole scene, the obtained RSME between the downscaled and reference image was smaller, by approx. 0.53 ∘ C on average, in the case of applying the proposed method than in the case of using the PBIM method.

show abstract

A methodology for estimation of surface evapotranspiration over large areas using remote sensing observations

Cited by 269 publications

References 11 publications

A Two-Source Model for Estimating Evaporative Fraction (TMEF) Coupling Priestley-Taylor Formula and Two-Stage Trapezoid

A Two-Source Model for Estimating Evaporative Fraction (TMEF) Coupling Priestley-Taylor Formula and Two-Stage Trapezoid

Monitoring of Evapotranspiration in a Semi-Arid Inland River Basin by Combining Microwave and Optical Remote Sensing Observations

Optimized AVHRR land surface temperature downscaling method for local scale observations: case study for the coastal area of the Gulf of Gdańsk

Contact Info

Product

Resources

About