Seasonal trends of satellite-based evapotranspiration algorithms over a complex ecosystem in East Asia

Hwang, Kyotaek; Choi, Minha

doi:10.1016/j.rse.2013.06.006

Cited by 35 publications

(22 citation statements)

References 77 publications

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“…However, DT shows different sensitivity with the MS-PT algorithm and LE relatively increases up to 3% for DT change of −20%. Overall, LE estimation by the MS-PT algorithm shows the obvious sensitivity orders: In the MS-PT algorithm proposed in this study, R n acquires more highly dependent and this is generally consistent with the previous literature [58,59]. For example, Jang et al [58] considered the sensitivity orders of estimated LE using satellite-based models with R n (±12% change of LE for ±20% change of the variable) > LAI (approximate ±10%) > VPD and T a (less than ±5%) at different land cover types.…”

Section: Sensitivity Analysissupporting

confidence: 90%

“…For example, Jang et al [58] considered the sensitivity orders of estimated LE using satellite-based models with R n (±12% change of LE for ±20% change of the variable) > LAI (approximate ±10%) > VPD and T a (less than ±5%) at different land cover types. Hwang and Choi [59] found the sensitivity orders: R n > LAI > P a for the revised remote sensing-based PM model. Besides R n , the Dependency of NDVI in the MS-PT algorithm is higher in the all flux towers as vegetation amount quantified by vegetation index (NDVI) and LAI affect the vegetation photosynthesis and transpiration [18,56].…”

Section: Sensitivity Analysismentioning

confidence: 99%

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Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping Terrestrial Evapotranspiration

et al. 2014

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Satellite-based vegetation indices (VIs) and Apparent Thermal Inertia (ATI) derived from temperature change provide valuable information for estimating evapotranspiration (LE) and detecting the onset and severity of drought. The modified satellite-based Priestley-Taylor (MS-PT) algorithm that we developed earlier, coupling both VI and ATI, is validated based on observed data from 40 flux towers distributed across the world on all continents. with the Priestley-Taylor-based LE (PT-JPL) algorithm, the MS-PT algorithm improves the LE estimates at most flux tower sites. Importantly, the MS-PT algorithm is also satisfactory in reproducing the inter-annual variability at flux tower sites with at least five years of data. The R 2 between measured and predicted annual LE anomalies is 0.42 (p = 0.02). The MS-PT algorithm is then applied to detect the variations of long-term terrestrial LE over Three-North Shelter Forest Region of China and to monitor global land surface drought. The MS-PT algorithm described here demonstrates the ability to map regional terrestrial LE and identify global soil moisture stress, without requiring precipitation information.

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Section: Sensitivity Analysissupporting

confidence: 90%

Section: Sensitivity Analysismentioning

confidence: 99%

Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping Terrestrial Evapotranspiration

et al. 2014

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“…The contribution of the energy term (Rn or Rs) is the highest in the three LE algorithms because these algorithms are calculated as the sum of the surface energy balance term. Hwang and Choi (2013) found the sensitivity orders: Rn>LAI>Pa for the revised remote sensing-based PM model. Yao et al (2014b) considered the sensitivity orders of estimated LE using the MS-PT algorithm with Rn (±20 % change of LE for ±20 % change of the variable)>NDVI (±10 %)>Ta and DT (less than ±7 %) at different land cover types.…”

Section: Sensitivity Analysis Of Three Satellite-based Le Algorithmsmentioning

confidence: 90%

Evaluation of three satellite-based latent heat flux algorithms over forest ecosystems using eddy covariance data

Yao

Zhang

Zhao³

et al. 2015

Environ Monit Assess

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We have evaluated the performance of three satellite-based latent heat flux (LE) algorithms over forest ecosystems using observed data from 40 flux towers distributed across the world on all continents. These are the revised remote sensing-based Penman-Monteith LE (RRS-PM) algorithm, the modified satellite-based Priestley-Taylor LE (MS-PT) algorithm, and the semi-empirical Penman LE (UMD-SEMI) algorithm. Sensitivity analysis illustrates that both energy and vegetation terms has the highest sensitivity compared with other input variables. The validation results show that three algorithms demonstrate substantial differences in algorithm performance for estimating daily LE variations among five forest ecosystem biomes. Based on the average Nash-Sutcliffe efficiency and root-mean-squared error (RMSE), the MS-PT algorithm has high performance over both deciduous broadleaf forest (DBF) (0.81, 25.4 W/m(2)) and mixed forest (MF) (0.62, 25.3 W/m(2)) sites, the RRS-PM algorithm has high performance over evergreen broadleaf forest (EBF) (0.4, 28.1 W/m(2)) sites, and the UMD-SEMI algorithm has high performance over both deciduous needleleaf forest (DNF) (0.78, 17.1 W/m(2)) and evergreen needleleaf forest (ENF) (0.51, 28.1 W/m(2)) sites. Perhaps the lower uncertainties in the required forcing data for the MS-PT algorithm, the complicated algorithm structure for the RRS-PM algorithm, and the calibrated coefficients of the UMD-SEMI algorithm based on ground-measured data may explain these differences.

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“…A detailed explanation of the sinusoidal model and its estimation of the hydrological parameters can be found in Bisht et al (2005) and Hwang and Choi (2013).…”

Section: Modis Data-setsmentioning

confidence: 99%

“…However, ground-based measurements have limited ability to provide representative values, because the densities of the measurement networks are always sparse (Allen et al 1998;Sumner and Jacobs 2005). To compensate for such limitations, numerous studies have been carried out on the development of remote sensing-based ET models which can provide accurate spatial distributions of ET (Choi et al 2009(Choi et al , 2011Glenn et al 2007;Hwang and Choi 2013;Jang et al 2010Jang et al , 2013Kalma, McVicar, and McCabe 2008;Kim et al 2012;Ryu et al 2012).…”

Section: Introductionmentioning

confidence: 99%

Remote sensing-based evapotranspiration algorithm: a case study of all sky conditions on a regional scale

Sur

Kang

Kim

et al. 2015

GIScience & Remote Sensing

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Accurate estimation of the land surface evapotranspiration (ET) over a heterogeneous ecosystem is important to understand the interaction between the land surface and the atmosphere with practical applications in integrated water resources management. Although numerous studies have been carried out to develop remote sensing technologies which could achieve more accurate prediction of the regional ET distributions, degrees of uncertainty remain due to the high spatiotemporal variability of the hydrometeorological parameters. A revised remote sensing-based Penman-Monteith algorithm under all sky conditions (Revised RS-PM allsky ) is proposed in this study using the MODerate resolution Imaging Spectroradiometer (MODIS) (ET MODIS ), and the model's capability was assessed over the complex topography of the Korean peninsula. The ground measurements taken at two flux sites with different land cover types in 2012 were employed. The results of ET MODIS represented temporal compatibility yielding biases of −0.18 mm day −1 at Seolmacheon (SMC) site and −0.14 mm day −1 at Cheongmicheon Farmland (CFC) site and root mean square error (RMSE) values of 1.42 mm day −1 at SMC site and 1.26 mm day −1 at CFC site. Overall, ET MODIS was verified to have similar error ranges as those of the previous studies conducted over flat and heterogeneous regions. The results suggest that the revised RS-PM algorithms can be applied on a regional scale with heterogeneous topography over long-term periods if handling of the input data is carefully conducted.

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Seasonal trends of satellite-based evapotranspiration algorithms over a complex ecosystem in East Asia

Cited by 35 publications

References 77 publications

Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping Terrestrial Evapotranspiration

Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping Terrestrial Evapotranspiration

Evaluation of three satellite-based latent heat flux algorithms over forest ecosystems using eddy covariance data

Remote sensing-based evapotranspiration algorithm: a case study of all sky conditions on a regional scale

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