Impact of the Spatial Domain Size on the Performance  of the Ts-VI Triangle Method in Terrestrial Evapotranspiration Estimation

Tian, Jing; Su, Haijun; Sun, Xiaomin; Chen, Shaohui; He, Honglin; Zhao, Lu

doi:10.3390/rs5041998

Cited by 31 publications

(26 citation statements)

References 24 publications

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“…Traditionally, traditional TIMs are only applicable to homogeneous surfaces (Carlson, 2007;Petropoulos et al, 2009;Zhang, 2009). Moreover, a recent study from Tian et al (2013) indicated that the variation of the spatial domain size would directly lead to the deviation of ET estimates. This created difficulty for traditional TIMs to couple with other pixel-based models.…”

Section: Advantages Of Etemlmentioning

confidence: 99%

“…(4) It is difficult to couple TIMS with other models. Tian et al (2013) indicated that different dry/wet edges determined in the VFC/LST trapezoid space directly led to the deviation of ET estimates due to the variation of the spatial domain size. This domain-dependent problem led to difficulty with this type of model being coupled with other pixel-based models.…”

Section: Introductionmentioning

confidence: 99%

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An enhanced two-source evapotranspiration model for land (ETEML): Algorithm and evaluation

Yang

Zhang

et al. 2015

Remote Sensing of Environment

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Satellite remote sensing provides a promising way to estimate regional evapotranspiration (ET) in a spatially distributed manner. In this study, an enhanced two-source evapotranspiration model for land (ETEML) is proposed based on a trapezoid framework of the vegetation fractional cover and land surface temperature (VFC/LST) space. In ETEML, a VFC/LST trapezoid space is theoretically defined for each pixel, and a pixel-wise mixed surface temperature decomposition method is proposed. ETEML is based on a two-source scheme, and the crop water stress index (CWSI) concept is applied to parameterize the soil evaporation and the vegetation transpiration separately. The proposed model was applied to the Soil Moisture-Atmosphere Coupling Experiment (SMACEX) site in central Iowa, USA. Evaluation with a remotely sensed dataset from Landsat was carried out to assess the performance of ETEML. Compared with the tower observations, the mean absolute deviation (MAD) and the root mean square deviation (RMSD) for the ETEML estimated latent heat flux (LE) are, respectively, 49 W/m 2 and 59 W/m 2 , comparable to retrieval accuracies published in other studies. Comparison between ETEML and variations on a simpler trapezoid interpolation model (TIM1 and TIM2) indicates that ETEML reduces the subjectivity and uncertainties involved in TIM1 and TIM2. Overall, the results suggest that ETEML is promising and can expand the application of the trapezoid framework-based ET modeling approaches to heterogeneous surfaces.

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Section: Advantages Of Etemlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An enhanced two-source evapotranspiration model for land (ETEML): Algorithm and evaluation

Yang

Zhang

et al. 2015

Remote Sensing of Environment

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“…• empirical methods that involve the use of statistically-derived relationships between ET and vegetation indices such as the normalized difference vegetation index (NDVI) or the enhanced vegetation index (EVI) [20][21][22][23][24][25], • residual methods of surface energy balance (single-and dual-source models) [8,26] which include the Surface Energy Balance Algorithm over Land (SEBAL) [27,28], Surface Energy Balance System (SEBS) [8,29,30] and Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) [6,31,32], • physically-based methods that involve the application of the combination of Penman-Monteith [7,33,34] and Priestley-Taylor types of equations [35][36][37][38][39], and • Data assimilation methods adjoined to the heat diffusion equation [40] and through the radiometric surface temperature sequences [41].…”

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confidence: 99%

Validation of Global Evapotranspiration Product (MOD16) using Flux Tower Data in the African Savanna, South Africa

et al. 2014

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Globally, water is an important resource required for the survival of human beings. Water is a scarce resource in the semi-arid environments, including South Africa. In South Africa, several studies have quantified evapotranspiration (ET) in different ecosystems at a local scale. Accurate spatially explicit information on ET is rare in the country mainly due to lack of appropriate tools. In recent years, a remote sensing ET product from the MODerate Resolution Imaging Spectrometer (MOD16) has been developed. However, its accuracy is not known in South African ecosystems. The objective of this study was to validate the MOD16 ET product using data from two eddy covariance flux towers, namely; Skukuza and Malopeni installed in a savanna and woodland ecosystem within the Kruger National Park, South Africa. Eight day cumulative ET data from the flux towers was calculated to coincide with the eight day MOD16 products over a period of 10 years from 2000 to 2010. The Skukuza flux tower results showed inconsistent comparisons with MOD16 ET. The Malopeni site achieved a poorer comparison with MOD16 ET compared to the Skukuza, and due to a shorter measurement period, data validation was performed for 2009 only. The inconsistent comparison of MOD16 and flux tower-based ET can be attributed to, among other things, the parameterization of the Penman-Monteith model, flux tower measurement errors, and flux tower footprint vs. OPEN ACCESSRemote Sens. 2014, 6 7407 MODIS pixel. MOD16 is important for global inference of ET, but for use in South Africa's integrated water management, a locally parameterized and improved product should be developed.

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“…The typical definition of drought is a period with a precipitation deficit that influences agriculture, water resources, incorporating air temperature, enhancing dry/wet edge determination, combining with thermal inertia, etc. [23,24,31,35,36]. The factors that most affect the accuracy of the TVDI were determined and evaluated when the TVDI was used to estimate water deficits [37].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Two Simulation Methods of the Temperature Vegetation Dryness Index (TVDI) for Drought Monitoring in Semi-Arid Regions of China

Song

Liu

et al. 2017

Remote Sensing

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Abstract:The Temperature Vegetation Dryness Index (TVDI), a drought monitoring index based on an empirical parameterization of the Land Surface Temperature (LST)-Normalized Difference Vegetation Index (NDVI) space, has been widely implemented in a variety of ecosystems worldwide because it does not depend on ancillary data. However, the simulation of dry/wet edges in the TVDI model can be problematic because remote sensing images do not have sufficient pixels to identify the wetness and dryness extremes of different vegetation coverages. In this study, an improvement in dry/wet edge simulation was proposed, and a comparison of the original TVDI and the modified Temperature Vegetation Dryness Index (TVDI m ) was performed for drought monitoring in Ningxia Province, which is a typical semi-arid region in China. First, the difference between the land surface temperatures in day and night (∆LST) was used as an alternative to LST when building the TVDI m model. In addition, the wet edges were improved by removing outliers using a statistical method, and the dry edges were optimized by removing the "tail down" points in the NDVI range of 0.0-0.1. Here, the modeling process of TVDI m in 2005, one of recent extreme drought year is illustrated. The results show that both the TVDI and TVDI m can be used to monitor the temporal and spatial variations of drought, and the onset, duration, extent, and severity of drought can be reflected by TVDI and TVDI m maps. However, the magnitude of TVDI is higher than that of TVDI m , which could cause the TVDI-simulated drought condition to be elevated in normal years and underestimated in dry years. The TVDI m has higher coefficients of correlation with in situ meteorological drought index and agricultural drought statistical data than does the original TVDI, and it exhibits better performance in drought monitoring compared to that of the original TVDI in semi-arid regions of China.

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Impact of the Spatial Domain Size on the Performance of the Ts-VI Triangle Method in Terrestrial Evapotranspiration Estimation

Cited by 31 publications

References 24 publications

An enhanced two-source evapotranspiration model for land (ETEML): Algorithm and evaluation

An enhanced two-source evapotranspiration model for land (ETEML): Algorithm and evaluation

Validation of Global Evapotranspiration Product (MOD16) using Flux Tower Data in the African Savanna, South Africa

Comparison of Two Simulation Methods of the Temperature Vegetation Dryness Index (TVDI) for Drought Monitoring in Semi-Arid Regions of China

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