% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Silvestro:892954,
      author       = {Silvestro, Paolo Cosmo and Casa, Raffaele and Hanuš, Jan
                      and Koetz, Benjamin and Rascher, Uwe and Schuettemeyer, Dirk
                      and Siegmann, Bastian and Skokovic, Drazen and Sobrino,
                      José and Tudoroiu, Marin},
      title        = {{S}ynergistic {U}se of {M}ultispectral {D}ata and {C}rop
                      {G}rowth {M}odelling for {S}patial and {T}emporal
                      {E}vapotranspiration {E}stimations},
      journal      = {Remote sensing},
      volume       = {13},
      number       = {11},
      issn         = {2072-4292},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2021-02453},
      pages        = {2138 -},
      year         = {2021},
      abstract     = {The aim of this research is to explore the analysis of
                      methods allowing a synergetic use of information exchange
                      between Earth Observation (EO) data and growth models in
                      order to provide high spatial and temporal resolution actual
                      evapotranspiration predictions. An assimilation method based
                      on the Ensemble Kalman Filter algorithm allows for combining
                      Sentinel-2 data with a new version of Simple Algorithm For
                      Yield $(SAFY_swb)$ that considers the effect of the water
                      balance on yield and estimates the daily trend of
                      evapotranspiration (ET). Our study is relevant in the
                      context of demonstrating the effectiveness and necessity of
                      satellite missions such as Land Surface Temperature
                      Monitoring (LSTM), to provide high spatial and temporal
                      resolution data for agriculture. The proposed method
                      addresses the problem both from a spatial point of view,
                      providing maps of the areas of interest of the main
                      biophysical quantities of vegetation (LAI, biomass, yield
                      and actual Evapotranspiration), and from a temporal point of
                      view, providing a simulation on a daily basis of the
                      aforementioned variables. The assimilation efficiency was
                      initially evaluated with a synthetic, large and
                      heterogeneous dataset, reaching values of $70\%$ even for
                      high measurement errors of the assimilated variable.
                      Subsequently, the method was tested in a case study in
                      central Italy, allowing estimates of the daily Actual
                      Evapotranspiration with a relative RMSE of $18\%.$ The
                      novelty of this research is in proposing a solution that
                      partially solves the main problems related to the
                      synergistic use of EO data with crop growth models, such as
                      the difficult calibration of initial parameters, the lack of
                      frequent high-resolution data or the high computational cost
                      of data assimilation methods. It opens the way to future
                      developments, such as the use of simultaneous assimilation
                      of multiple variables, to deeper investigations using more
                      specific datasets and exploiting the advanced tools.},
      cin          = {IBG-2},
      ddc          = {620},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {217 - Für eine nachhaltige Bio-Ökonomie – von
                      Ressourcen zu Produkten (POF4-217)},
      pid          = {G:(DE-HGF)POF4-217},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000660619600001},
      doi          = {10.3390/rs13112138},
      url          = {https://juser.fz-juelich.de/record/892954},
}