- 1.
Allen R G, Tasumi M, and Trezza R. 2007. Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)—Model. Journal of Irrigation and Drainage Engineering, 133(4)
- 2.
Anderson M C, Norman J M, Diak G R, Kustas W P, and Mecikalski J R. 1997. A two-source time-integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sensing of Environment, 60(2):195-216
- 3.
Babaeian E, Sadeghi M, Franz T E, Jones S, and Tuller M. 2018. Mapping soil moisture with the OPtical TRApezoid Model (OPTRAM) based on long-term MODIS observations. Remote Sensing of Environment, 211:425-40
- 4.
Bastiaanssen W G M, Menenti M, Feddes R A, and Holtslag A A M. 1998. A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation. Journal of Hydrology, 212
- 5.
Bhattarai N, Quackenbush L J, Im J, and Shaw S B. 2017. A new optimized algorithm for automating endmember pixel selection in the SEBAL and METRIC models. Remote Sensing of Environment, 196:178-92
- 6.
Carlson T. 2007. An overview of the "triangle method" for estimating surface evapotranspiration and soil moisture from satellite imagery. Sensors, 7(8):1612-29
- 7.
Carlson T N. 2013. Triangle Models and Misconceptions. International Journal of Remote Sensing Applications, 3(3)
- 8.
Carlson T N, Perry E M, and Schmugge T J. 1990. Remote estimation of soil-moisture availability and fractional vegetation cover for agricultural fields.agricultural and Forest Meteorology, 52(1-2):45-69
- 9.
Carlson T N, and Petropoulos G P. 2019. A new method for estimating of evapotranspiration and surface soil moisture from optical and thermal infrared measurements: the simplified triangle. International Journal of Remote Sensing, 40(20):7716-29
- 10.
Carter C, and Liang S. 2019. Evaluation of ten machine learning methods for estimating terrestrial evapotranspiration from remote sensing. International Journal of Applied Earth Observation and Geoinformation, 78:86-92
- 11.
Chen J M, and Liu J. 2020. Evolution of evapotranspiration models using thermal and shortwave remote sensing data. Remote Sensing of Environment, 237
- 12.
Chen X, Su Z, Ma Y, Yang K, and Wang B. 2013. Estimation of surface energy fluxes under complex terrain of Mt. Qomolangma over the Tibetan Plateau. Hydrology and Earth System Sciences, 17(4):1607-18
- 13.
de Tomas A, Nieto H, Guzinski R, Salas J, Sandholt I, and Berliner P. 2014. Validation and scale dependencies of the triangle method for the evaporative fraction estimation over heterogeneous areas. Remote Sensing of Environment, 152:493-511
- 14.
Fisher J B, Tu K P, and Baldocchi D D. 2008. Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites. Remote Sensing of Environment, 112(3):901-19
- 15.
Gan G, Kang T, Yang S, Bu J, Feng Z, and Gao Y. 2019. An optimized two source energy balance model based on complementary concept and canopy conductance. Remote Sensing of Environment, 223:243-56
- 16.
Garcia M, Fernandez N, Villagarcia L, Domingo F, Puigdefabregas J, and Sandholt I. 2014. Accuracy of the Temperature-Vegetation Dryness Index using MODIS under water-limited vs. energy-limited evapotranspiration conditions. Remote Sensing of Environment, 149:100-17
- 17.
Gillies R R, Carlson T N, Cui J, Kustas W P, and Humes K S. 1997. A verification of the ‘triangle’ method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface radiant temperature. International Journal of Remote Sensing, 18(15):3145-66
- 18.
Goward S N, Cruickshanks G D, and Hope A S. 1985. Observed relation between thermal emission and reflected spectral radiance of a complex vegetated landscape. Remote Sensing of Environment, 18(2):137-46
- 19.
Goward S N, Xue Y K, and Czajkowski K P. 2002. Evaluating land surface moisture conditions from the remotely sensed temperature/vegetation index measurements-An exploration with the simplified simple biosphere model. Remote Sensing of Environment, 79(2-3):225-42
- 20.
Hu G, Jia L, and Menenti M. 2015. Comparison of MOD16 and LSA-SAF MSG evapotranspiration products over Europe for 2011. Remote Sensing of Environment, 156:510-26
- 21.
Hu X, Ren H, Tansey K, Zheng Y, Ghent D, Liu X, and Yan L. 2019. Agricultural drought monitoring using European Space Agency Sentinel 3A land surface temperature and normalized difference vegetation index imageries. Agricultural and Forest Meteorology, 279
- 22.
Hu X, Shi L, Lin L, and Zha Y. 2019. Nonlinear boundaries of land surface temperature-vegetation index space to estimate water deficit index and evaporation fraction. Agricultural and Forest Meteorology, 279
- 23.
Jia L, Su Z B, van den Hurk B, Menenti M, Moene A, De Bruin H A R, Yrisarry J J B, Ibanez M, and Cuesta A. 2003. Estimation of sensible heat flux using the Surface Energy Balance System (SEBS) and ATSR measurements. Physics and Chemistry of the Earth, 28(1-3):75-88
- 24.
Jiang L, and Islam S. 1999. A methodology for estimation of surface evapotranspiration over large areas using remote sensing observations. Geophysical Research Letters, 26(17)
- 25.
Jiang L, and Islam S. 2003. An intercomparison of regional latent heat flux estimation using remote sensing data. International Journal of Remote Sensing, 24(11):2221-36
- 26.
Jiang L, Islam S, Guo W, Jutla A S, Senarath S U S, Ramsay B H, and Eltahir E A B. 2009. A satellite-based Daily Actual Evapotranspiration estimation algorithm over South Florida. Global and Planetary Change, 67(1-2):62-77
- 27.
Jiang Y, Tang R, Jiang X, Li Z-L, and Gao C. 2019. Estimation of Soil Evaporation and Vegetation Transpiration Using Two Trapezoidal Models From MODIS Data. Journal of Geophysical Research-Atmospheres, 124(14):7647-64
- 28.
Jung M, Koirala S, Weber U, Ichii K, Gans F, Camps-Valls G, Papale D, Schwalm C, Tramontana G, and Reichstein M. 2019. The FLUXCOM ensemble of global land-atmosphere energy fluxes. Scientific Data, 6
- 29.
Kalma J D, McVicar T R, and McCabe M F. 2009. Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data. Surveys in Geophysics, 29(4-5)
- 30.
Khan M S, Liaqat U W, Baik J, and Choi M. 2018. Stand-alone uncertainty characterization of GLEAM, GLDAS and MOD16 evapotranspiration products using an extended triple collocation approach. Agricultural and Forest Meteorology, 252:256-68
- 31.
Kustas W, and Anderson M. 2009. Advances in thermal infrared remote sensing for land surface modeling. Agricultural and Forest Meteorology, 149(12)
- 32.
Lambin E F, and Ehrlich D. 1996. The surface temperature-vegetation index space for land cover and land-cover change analysis. International Journal of Remote Sensing, 17(3)
- 33.
Li Z-L, Tang R L, Wan Z M, Bi Y Y, Zhou C H, Tang B H, Yan G J, and Zhang X Y. 2009. A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data. Sensors, 9(5):3801-53
- 34.
Liu K, Su H, Tian J, Li X, Wang W, Yang L, and Liang H. 2018. Assessing a scheme of spatial-temporal thermal remote-sensing sharpening for estimating regional evapotranspiration. International Journal of Remote Sensing, 39(10):3111-37
- 35.
Liu S, Xu Z, Song L, Zhao Q, Ge Y, Xu T, Ma Y, Zhu Z, Jia Z, and Zhang F. 2016. Upscaling evapotranspiration measurements from multi-site to the satellite pixel scale over heterogeneous land surfaces. Agricultural and Forest Meteorology, 230:97-113
- 36.
Liu Y, Hiyama T, Yasunari T, and Tanaka H. 2012. A nonparametric approach to estimating terrestrial evaporation: Validation in eddy covariance sites. Agricultural and Forest Meteorology, 157:49-59
- 37.
Long D, and Singh V P. 2012. A Two-source Trapezoid Model for Evapotranspiration (TTME) from satellite imagery. Remote Sensing of Environment, 121:370-88
- 38.
Long D, Singh V P, and Scanlon B R. 2012. Deriving theoretical boundaries to address scale dependencies of triangle models for evapotranspiration estimation (vol 112, D05113, 2012). Journal of Geophysical Research-Atmospheres, 117
- 39.
Lu J, Li Z-L, Tang R, Tang B-H, Wu H, Yang F, Labed J, and Zhou G. 2013. Evaluating the SEBS-estimated evaporative fraction from MODIS data for a complex underlying surface. Hydrological Processes, 27(22):3139-49
- 40.
Ma Y, Liu S, Song L, Xu Z, Liu Y, Xu T, and Zhu Z. 2018. Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data. Remote Sensing of Environment, 216:715-34
- 41.
Merlin O, Chirouze J, Olioso A, Jarlan L, Chehbouni G, and Boulet G. 2014. An image-based four-source surface energy balance model to estimate crop evapotranspiration from solar reflectance/thermal emission data (SEB-4S). Agricultural and Forest Meteorology, 184:188-203
- 42.
Minacapilli M, Consoli S, Vanella D, Ciraolo G, and Motisi A. 2016. A time domain triangle method approach to estimate actual evapotranspiration: Application in a Mediterranean region using MODIS and MSG-SEVIRI products. Remote Sensing of Environment, 174:10-23
- 43.
Mohseni F, and Mokhtarzade M. 2020. A new soil moisture index driven from an adapted long-term temperature-vegetation scatter plot using MODIS data. Journal of Hydrology, 581
- 44.
Moran M S, Clarke T R, Inoue Y, and Vidal A. 1994. Estimating crop water-deficit using the relation between surface-air temperature and spectral vegetation index. Remote Sensing of Environment, 49(3):246-63
- 45.
Moran M S, Rahman A F, Washburne J C, Goodrich D C, Weltz M A, and Kustas W P. 1996. Combining the Penman-Monteith equation with measurements of surface temperature and reflectance to estimate evaporation rates of semiarid grassland. Agricultural and Forest Meteorology, 80(2-4):87-109
- 46.
Mu Q, Zhao M, and Running S W. 2011. Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sensing of Environment, 115(8):1781-800
- 47.
Nishida K, Nemani R R, Running S W, and Glassy J M. 2003. An operational remote sensing algorithm of land surface evaporation. Kenlo Nishida;Ramakrishna R. Nemani;Steven W. Running;Joseph M. Glassy, 108(D9)
- 48.
Norman J M, Kustas W P, and Humes K S. 1995. Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface-temperature. Agricultural and Forest Meteorology, 77(3-4):263-93
- 49.
Olioso A, Chauki H, Courault D, and Wigneron J P. 1999. Estimation of evapotranspiration and photosynthesis by assimilation of remote sensing data into SVAT models. Remote Sensing of Environment, 68(3):341-56
- 50.
Pan X, Liu Y, Gan G, Fan X, and Yang Y. 2017. Estimation of Evapotranspiration Using a Nonparametric Approach Under All Sky: Accuracy Evaluation and Error Analysis. Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(6):2528-39
- 51.
Peng J, Liu Y, Zhao X, and Loew A. 2013. Estimation of evapotranspiration from MODIS TOA radiances in the Poyang Lake basin, China. Hydrology and Earth System Sciences, 17(4):1431-44
- 52.
Petropoulos G, Carlson T N, Wooster M J, and Islam S. 2009. A review of T-s/VI remote sensing based methods for the retrieval of land surface energy fluxes and soil surface moisture. Progress in Physical Geography-Earth and Environment, 33(2):224-50
- 53.
Price J C. 1990. Using spatial context in satellite data to infer regional scale evapotranspiration. Ieee Transactions on Geoscience and Remote Sensing, 28(5):940-8
- 54.
Qiu G Y, Li C, and Yan C. 2015. Characteristics of soil evaporation, plant transpiration and water budget of Nitraria dune in the arid Northwest China. Agricultural and Forest Meteorology, 203:107-17
- 55.
Sadeghi M, Babaeian E, Tuller M, and Jones S B. 2017. The optical trapezoid model: A novel approach to remote sensing of soil moisture applied to Sentinel-2 and Landsat-8 observations. Remote Sensing of Environment, 198:52-68
- 56.
Sandholt I, Rasmussen K, and Andersen J. 2002. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sensing of Environment, 79(2-3):213-24
- 57.
Shekar S N C, and Nandagiri L. 2020. A Penman-Monteith evapotranspiration model with bulk surface conductance derived from remotely sensed spatial contextual information. International Journal of Remote Sensing, 41(4):1486-511
- 58.
Song L, Liu S, Kustas W P, Nieto H, Sun L, Xu Z, Skaggs T H, et al. 2018. Monitoring and validating spatially and temporally continuous daily evaporation and transpiration at river basin scale. Remote Sensing of Environment, 219:72-88
- 59.
Song L, Liu S, Kustas W P, Zhou J, Xu Z, Xia T, and Li M. 2016. Application of remote sensing-based two-source energy balance model for mapping field surface fluxes with composite and component surface temperatures. Agricultural and Forest Meteorology, 230:8-19
- 60.
Stisen S, Sandholt I, Norgaard A, Fensholt R, and Jensen K H. 2008. Combining the triangle method with thermal inertia to estimate regional evapotranspiration-Applied to MSG-SEVIRI data in the Senegal River basin. Remote Sensing of Environment, 112(3):1242-55
- 61.
Su Z. 2002. The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes. Hydrology and Earth System Sciences, 6(1):85-99
- 62.
Sun H. 2016. Two-Stage Trapezoid: A New Interpretation of the Land Surface Temperature and Fractional Vegetation Coverage Space. Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(1):336-46
- 63.
Sun H, Wang Y, Liu W, Yuan S, and Nie R. 2017. Comparison of Three Theoretical Methods for Determining Dry and Wet Edges of the LST/FVC Space: Revisit of Method Physics. Remote Sensing, 9(6) [DOI: 10.3390/rs9060528]
- 64.
Sun L, Sun R, Li X, Liang S, and Zhang R. 2012. Monitoring surface soil moisture status based on remotely sensed surface temperature and vegetation index information. Agricultural and Forest Meteorology, 166:175-87
- 65.
Tagesson T, Horion S, Nieto H, Fornies V Z, Gonzalez G M, Bulgin C E, Ghent D, and Fensholt R. 2018. Disaggregation of SMOS soil moisture over West Africa using the Temperature and Vegetation Dryness Index based on SEVIRI land surface parameters. Remote Sensing of Environment, 206:424-41
- 66.
Tang R, and Li Z L. 2015. Evaluation of two end-member-based. models for regional Land Surface evapotranspiration estimation from MoDIS data. Agricultural and Forest meteo vology, 202, 69-82
- 67.
Tang R, and Li Z L. 2017. An End-Member-Based Two-Source Approach for Estimating Land Surface Evapotranspiration From Remote Sensing Data. Ieee Transactions on Geoscience and Remote Sensing, 55(10):5818-32
- 68.
Tang R, Li Z L, and Tang B. 2010. An application of the T-s-VI triangle method with enhanced edges determination for evapotranspiration estimation from MODIS data in and and semi-arid regions: Implementation and validation. Remote Sensing of Environment, 114(3):540-51
- 69.
Tang R, Li Z-L, Tang B, HuaWu, and Ieee. 2015. Interpretation of surface temperature/vegetation index space for evapotranspiration estimation from svat modeling. In 2015 IEEE International Geoscience and Remote Sensing Symposium, 2028-30
- 70.
Tian J, Su H, Sun X, Chen S, He H, and Zhao L. 2013. Impact of the Spatial Domain Size on the Performance of the T-s-VI Triangle Method in Terrestrial Evapotranspiration Estimation. Remote Sensing, 5(4):1998-2013
- 71.
Wang K, and Dickinson R E. 2012. A Review of global terrestrial evapotranspiration: observation, modeling, climatology, and climatic variability. Reviews of Geophysics, 50
- 72.
Wang K, Wang P, Li Z, Cribb M, and Sparrow M. 2007. A simple method to estimate actual evapotranspiration from a combination of net radiation, vegetation index, and temperature. Journal of Geophysical Research-Atmospheres, 112(D15) [DOI: 10.1029/20 06jd008351]
- 73.
Wang K C, Li Z Q, and Cribb M. 2006. Estimation of evaporative fraction from a combination of day and night land surface temperatures and NDVI: A new method to determine the Priestley-Taylor parameter. Remote Sensing of Environment, 102(3-4):293-305
- 74.
Wang L, Guo N, Wang X, and Wang W. 2017. Effects of Spatial Resolution for Evapotranspiration Estimation by Using the Triangular Method Over Heterogeneous Underling Surface. Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(6):2518-27
- 75.
Wang Y, Li R, Min Q, Fu Y, Wang Y, Zhong L, and Fu Y. 2019. A three-source satellite algorithm for retrieving all-sky evapotranspiration rate using combined optical and microwave vegetation index at twenty AsiaFlux sites. Remote Sensing of Environment, 235
- 76.
Wu B, Zhu W, Yan N, Feng X, Xing Q, and Zhuang Q. 2016. An Improved Method for Deriving Daily Evapotranspiration Estimates From Satellite Estimates on Cloud-Free Days. Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(4):1323-30
- 77.
Xiong Y J, Zhao S H, Tian F, and Qiu G Y. 2015. An evapotranspiration product for arid regions based on the three-temperature model and thermal remote sensing. Journal of Hydrology, 530:392-404
- 78.
Xu T, Guo Z, Liu S, He X, Meng Y, Xu Z, Xia Y, et al. 2018. Evaluating Diffferent Machine Learning Methods for Upscaling Evapotranspiration from Flux Towers to the Regional Scale. Journal of Geophysical Research-Atmospheres, 123(16):8674-90
- 79.
Xu T, He X, Bateni S M, Auligne T, Liu S, Xu Z, Zhou J, and Mao K. 2019. Mapping regional turbulent heat fluxes via variational assimilation of land surface temperature data from polar orbiting satellites. Remote Sensing of Environment, 221:444-61
- 80.
Xu Z, Liu S, Li X, Shi S, Wang J, Zhu Z, Xu T, Wang W, and Ma M. 2013. Intercomparison of surface energy flux measurement systems used during the HiWATER-MUSOEXE. Journal of Geophysical Research-Atmospheres, 118(23):13140-57
- 81.
Yang Y, and Shang S. 2013. A hybrid dual-source scheme and trapezoid framework-based evapotranspiration model (HTEM) using satellite images: Algorithm and model test. Journal of Geophysical Research-Atmospheres, 118(5):2284-300
- 82.
Yang Y, Su H, Zhang R, Tian J, and Li L. 2015. An enhanced two-source evapotranspiration model for land (ETEML): Algorithm and evaluation. Remote Sensing of Environment, 168:54-65
- 83.
Yao Y, Liang S, Li X, Chen J, Wang K, Jia K, Cheng J, et al. 2015. A satellite-based hybrid algorithm to determine the Priestley-Taylor parameter for global terrestrial latent heat flux estimation across multiple biomes. Remote Sensing of Environment, 165:216-33
- 84.
Yuan W, Liu S, Yu G, Bonnefond J-M, Chen J, Davis K, Desai A R, et al. 2010. Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data. Remote Sensing of Environment, 114(7):1416-31
- 85.
Zare M, Drastig K, and Zude-Sasse M. 2020. Tree Water Status in Apple Orchards Measured by Means of Land Surface Temperature and Vegetation Index (LST-NDVI) Trapezoidal Space Derived from Landsat 8 Satellite Images. Sustainability, 12(1) [DOI: 10.33 90/su12010070]
- 86.
Zhang D, Tang R, Tang B-H, Wu H, and Li Z-L. 2015. A Simple Method for Soil Moisture Determination From LST-VI Feature Space Using Nonlinear Interpolation Based on Thermal Infrared Remotely Sensed Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(2):638-48
- 87.
Zhang H, Gorelick S M, Avisse N, Tilmant A, Rajsekhar D, and Yoon J. 2016. A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE) for Satellite-Based Actual Evapotranspiration Estimation. Remote Sensing, 8(9) [DOI: 10.3390/rs8090735]
- 88.
Zhang K, Kimball J S, and Running S W. 2016. A review of remote sensing based actual evapotranspiration estimation. Wiley Interdisciplinary Reviews-Water, 3(6):834-53
- 89.
Zhang R, Tian J, Su H, Sun X, Chen S, and Xia J. 2008. Two Improvements of an Operational Two-Layer Model for Terrestrial Surface Heat Flux Retrieval. Sensors, 8(10):6165-87
- 90.
Zhang R H, Sun X M, Wang W M, Xu J P, Zhu Z L, and Tian J. 2005. An operational two-layer remote sensing model to estimate surface flux in regional scale: Physical background. Science in China Series D-Earth Sciences, 48:225-44
- 91.
Zhang Y, Kong D, Gan R, Chiew F H S, McVicar T R, Zhang Q, and Yang Y. 2019. Coupled estimation of 500 m and 8-day resolution global evapotranspiration and gross primary production in 2002-2017. Remote Sensing of Environment, 222:165-82
- 92.
Zhao W, Li A, Jin H, Zhang Z, Bian J, and Yin G. 2017. Performance Evaluation of the Triangle-Based Empirical Soil Moisture Relationship Models Based on Landsat-5 TM Data and In Situ Measurements. Ieee Transactions on Geoscience and Remote Sensing, 55(5):2632-45
- 93.
Zhao X, and Liu Y. 2014. Relative Contribution of the Topographic Influence on the Triangle Approach for Evapotranspiration Estimation over Mountainous Areas. Advances in Meteorology, 2014
- 94.
Zhu W, Jia S, and Lv A. 2017a. A Universal T-s-VI Triangle Method for the Continuous Retrieval of Evaporative Fraction From MODIS Products. Journal of Geophysical Research-Atmospheres, 122(19):10406-27
- 95.
Zhu W, Jia S, and Lv A. 2017b. A time domain solution of the Modified Temperature Vegetation Dryness Index (MTVDI) for continuous soil moisture monitoring. Remote Sensing of Environment, 200:1-17
- 96.
Gao Y C, Long D. 2008. Advances in remote sensing ET modeling. Journal of Remote Sensing,(03):515-28
- 97.
Song L S, Liu S M, Xu T R, Xu Z W, and Ma Y F. 2017. Estimation and verification of soil evaporation and vegetation transpiration. Journal of Remote Sensing, 21(06):966-81
- 98.
Tang R L. 2011. Research on remote sensing retrieval method of land surface evapotranspiration based on the characteristic space of land surface temperature and vegetation coverage. Graduate School of Chinese Academy of Sciences
- 99.
Zhou T, Peng Z Q, Xin X Z, and Li F G. 2016. Research Review on non-uniform surface evapotranspiration Remote sensing. Journal of Remote Sensing, 20(02):257-77