Estimation of high-resolution terrestrial evapotranspiration from Landsat data using a simple Taylor skill fusion method

Research output: Contribution to journalArticle


Estimation of high-resolution terrestrial evapotranspiration (ET) from Landsat data is important in many climatic, hydrologic, and agricultural applications, as it can help bridging the gap between existing coarse-resolution ET products and point-based field measurements. However, there is large uncertainty among existing ET products from Landsat that limit their application. This study presents a simple Taylor skill fusion (STS) method that merges five Landsat-based ET products and directly measured ET from eddy covariance (EC) to improve the global estimation of terrestrial ET. The STS method uses a weighted average of the individual ET products and weights are determined by their Taylor skill scores (S). The validation with site-scale measurements at 206 EC flux towers showed large differences and uncertainties among the five ET products. The merged ET product exhibited the best performance with a decrease in the averaged root-mean-square error (RMSE) by 2–5 W/m2 when compared to the individual products. To evaluate the reliability of the STS method at the regional scale, the weights of the STS method for these five ET products were determined using EC ground-measurements. An example of regional ET mapping demonstrates that the STS-merged ET can effectively integrate the individual Landsat ET products. Our proposed method provides an improved high-resolution ET product for identifying agricultural crop water consumption and providing a diagnostic assessment for global land surface models.


  • Yunjun Yao
  • Shunlin Liang
  • Xianglan Li
  • Yuhu Zhang
  • Jiquan Chen
  • Kun Jia
  • Xiaotong Zhang
  • Joshua B. Fisher
  • Xuanyu Wang
  • Lilin Zhang
  • Jia Xu
  • Changliang Shao
  • Gabriela Posse
  • Yingnian Li
  • Vincenzo Magliulo
  • Andrej Varlagin
  • Eddy J. Moors
  • Julia Boike
  • Craig Macfarlane
  • Tomomichi Kato
  • Nina Buchmann
  • D. P. Billesbach
  • Jason Beringer
  • Sebastian Wolf
  • Shirley A. Papuga
  • Georg Wohlfahrt
  • Leonardo Montagnani
  • Eugénie Paul-Limoges
  • Carmen Emmel
  • Lukas Hörtnagl
  • Torsten Sachs
  • Carsten Gruening
  • Beniamino Gioli
  • Ana López-Ballesteros
  • Rainer Steinbrecher
  • Bert Gielen
External organisations
  • Beijing Normal University
  • Michigan State University
  • Wageningen University
  • Alfred-Wegener Institute for Polar and Marine Research, Potsdam
  • Hokkaido University
  • ETH Zürich
  • University of Nebraska - Lincoln
  • University of Western Australia, Crawley
  • University of Arizona
  • University of Innsbruck
  • Free University of Bozen-Bolzano
  • European Commission Joint Research Centre, Ispra
  • University of Antwerp
  • Capital Normal University
  • California Institute of Technology
  • National Institute of Agricultural Technology (INTA)
  • Northwest Institute of Plateau Biology, CAS
  • CNR Institute for Agricultural and Forestry Systems in the Mediterranean (CNR-ISAFOM)
  • A.N. Severtsov Institute of Ecology and Evolution, RAS
  • CSIRO Land & Water Flagship
  • GFZ German Research Centre for Geosciences
  • CNR Institute of Biometeorology (CNR-IBIMET)
  • University of Granada
  • Karlsruhe Institute of Technology
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Oceanography, Hydrology, Water Resources


  • Eddy covariance, Fusion method, High-resolution products, Landsat data, Terrestrial evapotranspiration
Original languageEnglish
Pages (from-to)508-526
Number of pages19
JournalJournal of Hydrology
Publication statusPublished - 2017 Oct 1
Publication categoryResearch