An Empirical Orthogonal Function-Based Algorithm for Estimating Terrestrial Latent Heat Flux from Eddy Covariance, Meteorological and Satellite Observations

Feng, Fei; Li, Xianglan; Yao, Yunjun; Liang, Shunlin; Chen, Jiquan; Zhao, Xiang; Jia, Kun; Pintér, Krisztina; McCaughey, J. Harry

doi:10.1371/journal.pone.0160150

Title: An Empirical Orthogonal Function-Based Algorithm for Estimating Terrestrial Latent Heat Flux from Eddy Covariance, Meteorological and Satellite Observations

Journal Article · 29 July 2016 · PLoS ONE

DOI: https://doi.org/10.1371/journal.pone.0160150 · OSTI ID:1627799

Feng, Fei ^[1]; Li, Xianglan ^[1]; Yao, Yunjun ^[2]; Liang, Shunlin ^[3]; Chen, Jiquan ^[4]; Zhao, Xiang ^[2]; Jia, Kun ^[2]; Pintér, Krisztina ^[5]; McCaughey, J. Harry ^[6]

Beijing Normal Univ. (China). College of Global Change and Earth System Science. State Key Lab. of Remote Sensing Science
Beijing Normal Univ. (China). School of Geography. State Key Lb. of Remote Sensing Science
Beijing Normal Univ. (China). College of Global Change and Earth System Science. State Key Lab. of Remote Sensing Science; Univ. of Maryland, College Park, MD (United States). Dept. of Geographical Sciences
Michigan State Univ., East Lansing, MI (United States). Center for Global Change and Earth Observations (CGCEO). Landscape Ecology & Ecosystem Science (LEES) Lab
Szent István Univ., Gödöllő (Hungary). Inst. of Botany and Ecophysiology; Szent István Univ., Gödöllő (Hungary). MTA-SZIE Plant Ecology Research Group
Queen's Univ., Kingston, ON (Canada). Dept. of Geography

Accurate estimation of latent heat flux (LE) based on remote sensing data is critical in characterizing terrestrial ecosystems and modeling land surface processes. Many LE products were released during the past few decades, but their quality might not meet the requirements in terms of data consistency and estimation accuracy. Merging multiple algorithms could be an effective way to improve the quality of existing LE products. In this paper, we present a data integration method based on modified empirical orthogonal function (EOF) analysis to integrate the Moderate Resolution Imaging Spectroradiometer (MODIS) LE product (MOD16) and the Priestley-Taylor LE algorithm of Jet Propulsion Laboratory (PT-JPL) estimate. Twenty-two eddy covariance (EC) sites with LE observation were chosen to evaluate our algorithm, showing that the proposed EOF fusion method was capable of integrating the two satellite data sets with improved consistency and reduced uncertainties. Further efforts were needed to evaluate and improve the proposed algorithm at larger spatial scales and time periods, and over different land cover types.

View Accepted Manuscript (DOE)

Cite

Export

Save

Research Organization:: Univ. of Maryland, College Park, MD (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: FG02-04ER63917; FG02- 04ER63911

OSTI ID:: 1627799

Journal Information:: PLoS ONE, Vol. 11, Issue 7; ISSN 1932-6203

Publisher:: Public Library of ScienceCopyright Statement

Country of Publication:: United States

Language:: English

References (56)

Trends in Land–Atmosphere Interactions from CMIP5 Simulations Dirmeyer, Paul A.; Jin, Yan; Singh, Bohar Journal of Hydrometeorology, Vol. 14, Issue 3 https://doi.org/10.1175/JHM-D-12-0107.1	journal	June 2013
Comparison of satellite-based evapotranspiration models over terrestrial ecosystems in China Chen, Yang; Xia, Jiangzhou; Liang, Shunlin Remote Sensing of Environment, Vol. 140 https://doi.org/10.1016/j.rse.2013.08.045	journal	January 2014
Improvements to a MODIS global terrestrial evapotranspiration algorithm Mu, Qiaozhen; Zhao, Maosheng; Running, Steven W. Remote Sensing of Environment, Vol. 115, Issue 8 https://doi.org/10.1016/j.rse.2011.02.019	journal	August 2011
The net carbon drawdown of small scale afforestation from satellite observations Montenegro, Alvaro; Eby, Michael; Mu, Qiaozhen Global and Planetary Change, Vol. 69, Issue 4 https://doi.org/10.1016/j.gloplacha.2009.08.005	journal	December 2009
Evaluation of multireanalysis products with in situ observations over the Tibetan Plateau: EVALUATION OF REANALYSIS OVER TIBETAN PLATEAU Wang, Aihui; Zeng, Xubin Journal of Geophysical Research: Atmospheres, Vol. 117, Issue D5 https://doi.org/10.1029/2011JD016553	journal	March 2012
Development of a global evapotranspiration algorithm based on MODIS and global meteorology data Mu, Qiaozhen; Heinsch, Faith Ann; Zhao, Maosheng Remote Sensing of Environment, Vol. 111, Issue 4 https://doi.org/10.1016/j.rse.2007.04.015	journal	December 2007
MODIS-driven estimation of terrestrial latent heat flux in China based on a modified Priestley–Taylor algorithm Yao, Yunjun; Liang, Shunlin; Cheng, Jie Agricultural and Forest Meteorology, Vol. 171-172 https://doi.org/10.1016/j.agrformet.2012.11.016	journal	April 2013
Some terms of reference in data fusion Wald, L. IEEE Transactions on Geoscience and Remote Sensing, Vol. 37, Issue 3 https://doi.org/10.1109/36.763269	journal	May 1999
Correcting surface solar radiation of two data assimilation systems against FLUXNET observations in North America: CORRECTING MODELED SOLAR RADIATION Zhao, Lei; Lee, Xuhui; Liu, Shoudong Journal of Geophysical Research: Atmospheres, Vol. 118, Issue 17 https://doi.org/10.1002/jgrd.50697	journal	September 2013
Global estimates of the land–atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites Fisher, Joshua B.; Tu, Kevin P.; Baldocchi, Dennis D. Remote Sensing of Environment, Vol. 112, Issue 3 https://doi.org/10.1016/j.rse.2007.06.025	journal	March 2008
Multi-model ensemble hydrologic prediction using Bayesian model averaging Duan, Qingyun; Ajami, Newsha K.; Gao, Xiaogang Advances in Water Resources, Vol. 30, Issue 5 https://doi.org/10.1016/j.advwatres.2006.11.014	journal	May 2007
Energy balance closure at FLUXNET sites Wilson, Kell; Goldstein, Allen; Falge, Eva Agricultural and Forest Meteorology, Vol. 113, Issue 1-4 https://doi.org/10.1016/S0168-1923(02)00109-0	journal	December 2002
A Weak-Constraint-Based Data Assimilation Scheme for Estimating Surface Turbulent Fluxes Qin, Jun; Liang, Shunlin; Liu, Ronggao IEEE Geoscience and Remote Sensing Letters, Vol. 4, Issue 4 https://doi.org/10.1109/LGRS.2007.904004	journal	October 2007
Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data Yuan, Wenping; Liu, Shuguang; Yu, Guirui Remote Sensing of Environment, Vol. 114, Issue 7 https://doi.org/10.1016/j.rse.2010.01.022	journal	July 2010
Improvements of the MODIS terrestrial gross and net primary production global data set Zhao, Maosheng; Heinsch, Faith Ann; Nemani, Ramakrishna R. Remote Sensing of Environment, Vol. 95, Issue 2 https://doi.org/10.1016/j.rse.2004.12.011	journal	March 2005
Climate-Driven Increases in Global Terrestrial Net Primary Production from 1982 to 1999 Nemani, R. R. Science, Vol. 300, Issue 5625 https://doi.org/10.1126/science.1082750	journal	June 2003
Intercomparison of surface energy flux measurement systems used during the HiWATER-MUSOEXE: INTERCOMPARISON OF FLUX INSTRUMENTS Xu, Ziwei; Liu, Shaomin; Li, Xin Journal of Geophysical Research: Atmospheres, Vol. 118, Issue 23 https://doi.org/10.1002/2013JD020260	journal	December 2013
Estimation of surface turbulent heat fluxes via variational assimilation of sequences of land surface temperatures from Geostationary Operational Environmental Satellites Xu, Tongren; Bateni, S. M.; Liang, S. Journal of Geophysical Research: Atmospheres, Vol. 119, Issue 18 https://doi.org/10.1002/2014JD021814	journal	September 2014
Bayesian multimodel estimation of global terrestrial latent heat flux from eddy covariance, meteorological, and satellite observations Yao, Yunjun; Liang, Shunlin; Li, Xianglan Journal of Geophysical Research: Atmospheres, Vol. 119, Issue 8 https://doi.org/10.1002/2013JD020864	journal	April 2014
Regional evaporation estimates from flux tower and MODIS satellite data Cleugh, Helen A.; Leuning, Ray; Mu, Qiaozhen Remote Sensing of Environment, Vol. 106, Issue 3 https://doi.org/10.1016/j.rse.2006.07.007	journal	February 2007
An improved method for estimating global evapotranspiration based on satellite determination of surface net radiation, vegetation index, temperature, and soil moisture Wang, Kaicun; Liang, Shunlin 2008 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium https://doi.org/10.1109/IGARSS.2008.4779489	conference	July 2008
On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters Priestley, C. H. B.; Taylor, R. J. Monthly Weather Review, Vol. 100, Issue 2 https://doi.org/10.1175/1520-0493(1972)100<0081:OTAOSH>2.3.CO;2	journal	February 1972
Effects of spatial aggregation on the multi-scale estimation of evapotranspiration Ershadi, A.; McCabe, M. F.; Evans, J. P. Remote Sensing of Environment, Vol. 131 https://doi.org/10.1016/j.rse.2012.12.007	journal	April 2013
On the net surface water exchange rate estimated from remote-sensing observation and reanalysis Behrangi, Ali; Wong, Sun; Mallick, Kaniska International Journal of Remote Sensing, Vol. 35, Issue 6 https://doi.org/10.1080/01431161.2014.889866	journal	March 2014
A continuous satellite-derived global record of land surface evapotranspiration from 1983 to 2006: GLOBAL RECORD OF LAND SURFACE EVAPOTRANSPIRATION Zhang, Ke; Kimball, John S.; Nemani, Ramakrishna R. Water Resources Research, Vol. 46, Issue 9 https://doi.org/10.1029/2009WR008800	journal	September 2010
A long-term Global LAnd Surface Satellite (GLASS) data-set for environmental studies Liang, Shunlin; Zhao, Xiang; Liu, Suhong International Journal of Digital Earth, Vol. 6, Issue sup1 https://doi.org/10.1080/17538947.2013.805262	journal	December 2013
Correcting eddy-covariance flux underestimates over a grassland Twine, T. E.; Kustas, W. P.; Norman, J. M. Agricultural and Forest Meteorology, Vol. 103, Issue 3 https://doi.org/10.1016/S0168-1923(00)00123-4	journal	June 2000
Validation of Global Evapotranspiration Product (MOD16) using Flux Tower Data in the African Savanna, South Africa Ramoelo, Abel; Majozi, Nobuhle; Mathieu, Renaud Remote Sensing, Vol. 6, Issue 8 https://doi.org/10.3390/rs6087406	journal	August 2014
Integrating MODIS and CYCLOPES Leaf Area Index Products Using Empirical Orthogonal Functions Wang, Dongdong; Liang, Shunlin IEEE Transactions on Geoscience and Remote Sensing, Vol. 49, Issue 5 https://doi.org/10.1109/TGRS.2010.2086463	journal	May 2011
Validation of MODIS 16 global terrestrial evapotranspiration products in various climates and land cover types in Asia Kim, Hyun Woo; Hwang, Kyotaek; Mu, Qiaozhen KSCE Journal of Civil Engineering, Vol. 16, Issue 2 https://doi.org/10.1007/s12205-012-0006-1	journal	January 2012
Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis Mueller, B.; Hirschi, M.; Jimenez, C. Hydrology and Earth System Sciences, Vol. 17, Issue 10 https://doi.org/10.5194/hess-17-3707-2013	journal	January 2013
Evapotranspiration models compared on a Sierra Nevada forest ecosystem Fisher, Joshua B.; DeBiase, Terry A.; Qi, Ye Environmental Modelling & Software, Vol. 20, Issue 6 https://doi.org/10.1016/j.envsoft.2004.04.009	journal	June 2005
Effects of remote sensing pixel resolution on modeled energy flux variability of croplands in Iowa Kustas, W. Remote Sensing of Environment, Vol. 92, Issue 4 https://doi.org/10.1016/j.rse.2004.02.020	journal	September 2004
An Empirical Orthogonal Function Iteration Approach for Obtaining Homogeneous Radiative Fluxes from Satellite Observations Zhang, Banglin; Pinker, Rachel T.; Stackhouse, Paul W. Journal of Applied Meteorology and Climatology, Vol. 46, Issue 4 https://doi.org/10.1175/JAM2478.1	journal	April 2007
A comparison of eddy-covariance and large aperture scintillometer measurements with respect to the energy balance closure problem Liu, S. M.; Xu, Z. W.; Wang, W. Z. Hydrology and Earth System Sciences, Vol. 15, Issue 4 https://doi.org/10.5194/hess-15-1291-2011	journal	January 2011
Evaluation of global observations-based evapotranspiration datasets and IPCC AR4 simulations: GLOBAL LAND EVAPOTRANSPIRATION DATASETS Mueller, B.; Seneviratne, S. I.; Jimenez, C. Geophysical Research Letters, Vol. 38, Issue 6 https://doi.org/10.1029/2010GL046230	journal	March 2011
Evaluation and Intercomparison of Cloud Fraction and Radiative Fluxes in Recent Reanalyses over the Arctic Using BSRN Surface Observations Zib, Behnjamin J.; Dong, Xiquan; Xi, Baike Journal of Climate, Vol. 25, Issue 7 https://doi.org/10.1175/JCLI-D-11-00147.1	journal	April 2012
Global estimates of evapotranspiration for climate studies using multi-sensor remote sensing data: Evaluation of three process-based approaches Vinukollu, Raghuveer K.; Wood, Eric F.; Ferguson, Craig R. Remote Sensing of Environment, Vol. 115, Issue 3 https://doi.org/10.1016/j.rse.2010.11.006	journal	March 2011
Multi-site evaluation of terrestrial evaporation models using FLUXNET data Ershadi, A.; McCabe, M. F.; Evans, J. P. Agricultural and Forest Meteorology, Vol. 187 https://doi.org/10.1016/j.agrformet.2013.11.008	journal	April 2014
Global intercomparison of 12 land surface heat flux estimates Jiménez, C.; Prigent, C.; Mueller, B. Journal of Geophysical Research, Vol. 116, Issue D2 https://doi.org/10.1029/2010JD014545	journal	January 2011
Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites Long, Di; Longuevergne, Laurent; Scanlon, Bridget R. Water Resources Research, Vol. 50, Issue 2 https://doi.org/10.1002/2013WR014581	journal	February 2014
Empirical orthogonal functions and related techniques in atmospheric science: A review Hannachi, A.; Jolliffe, I. T.; Stephenson, D. B. International Journal of Climatology, Vol. 27, Issue 9 https://doi.org/10.1002/joc.1499	journal	January 2007
Interpretation of Extended Empirical Orthogonal Function (EEOF) Analysis Chen, Jeng-Ming; Harr, Patrick A. Monthly Weather Review, Vol. 121, Issue 9 https://doi.org/10.1175/1520-0493(1993)121<2631:IOEEOF>2.0.CO;2	journal	September 1993
Reconstruction of Historical Sea Surface Temperatures Using Empirical Orthogonal Functions Smith, Thomas M.; Reynolds, Richard W.; Livezey, Robert E. Journal of Climate, Vol. 9, Issue 6 https://doi.org/10.1175/1520-0442(1996)009<1403:ROHSST>2.0.CO;2	journal	June 1996
ET come home: potential evapotranspiration in geographical ecology: ET come home Fisher, Joshua B.; Whittaker, Robert J.; Malhi, Yadvinder Global Ecology and Biogeography, Vol. 20, Issue 1 https://doi.org/10.1111/j.1466-8238.2010.00578.x	journal	August 2010
Mapping daily evapotranspiration at field scales over rainfed and irrigated agricultural areas using remote sensing data fusion Cammalleri, C.; Anderson, M. C.; Gao, F. Agricultural and Forest Meteorology, Vol. 186 https://doi.org/10.1016/j.agrformet.2013.11.001	journal	March 2014
Reconstruction of incomplete oceanographic data sets using empirical orthogonal functions: application to the Adriatic Sea surface temperature Alvera-Azcárate, A.; Barth, A.; Rixen, M. Ocean Modelling, Vol. 9, Issue 4 https://doi.org/10.1016/j.ocemod.2004.08.001	journal	January 2005
EOF Calculations and Data Filling from Incomplete Oceanographic Datasets* Beckers, J. M.; Rixen, M. Journal of Atmospheric and Oceanic Technology, Vol. 20, Issue 12 https://doi.org/10.1175/1520-0426(2003)020<1839:ECADFF>2.0.CO;2	journal	December 2003
Mapping of Land-Atmosphere Heat Fluxes and Surface Parameters with Remote Sensing Data Caparrini, Francesca; Castelli, Fabio; Entekhabi, Dara Boundary-Layer Meteorology, Vol. 107, Issue 3 https://doi.org/10.1023/A:1022821718791	journal	June 2003
Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping Terrestrial Evapotranspiration Yao, Yunjun; Liang, Shunlin; Zhao, Shaohua Remote Sensing, Vol. 6, Issue 1 https://doi.org/10.3390/rs6010880	journal	January 2014
Empirical orthogonal functions and related techniques in atmospheric science: A review Hannachi, A.; Jolliffe, I. T.; Stephenson, D. B. International Journal of Climatology, Vol. 27, Issue 9 https://doi.org/10.1002/joc.1499	journal	January 2007
Improvements of the MODIS terrestrial gross and net primary production global data set Zhao, Maosheng; Heinsch, Faith Ann; Nemani, Ramakrishna R. Remote Sensing of Environment, Vol. 95, Issue 2 https://doi.org/10.1016/j.rse.2004.12.011	journal	March 2005
Effects of spatial aggregation on the multi-scale estimation of evapotranspiration Ershadi, A.; McCabe, M. F.; Evans, J. P. Remote Sensing of Environment, Vol. 131 https://doi.org/10.1016/j.rse.2012.12.007	journal	April 2013
Comparison of satellite-based evapotranspiration models over terrestrial ecosystems in China Chen, Yang; Xia, Jiangzhou; Liang, Shunlin Remote Sensing of Environment, Vol. 140 https://doi.org/10.1016/j.rse.2013.08.045	journal	January 2014
Climate-Driven Increases in Global Terrestrial Net Primary Production from 1982 to 1999 Nemani, R. R. Science, Vol. 300, Issue 5625 https://doi.org/10.1126/science.1082750	journal	June 2003
A comparison of eddy-covariance and large aperture scintillometer measurements with respect to the energy balance closure problem Liu, S. M.; Xu, Z. W.; Wang, W. Z. Hydrology and Earth System Sciences, Vol. 15, Issue 4 https://doi.org/10.5194/hess-15-1291-2011	journal	January 2011

Cited By (1)

Integrating Latent Heat Flux Products from MODIS and Landsat Data Using Multi-Resolution Kalman Filter Method in the Midstream of Heihe River Basin of Northwest China Xu, Jia; Yao, Yunjun; Tan, Kanran Remote Sensing, Vol. 11, Issue 15 https://doi.org/10.3390/rs11151787	journal	July 2019