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@ARTICLE{Reichenau:884858,
      author       = {Reichenau, Tim G. and Korres, Wolfgang and Schmidt, Marius
                      and Graf, Alexander and Welp, Gerhard and Meyer, Nele and
                      Stadler, Anja and Brogi, Cosimo and Schneider, Karl},
      title        = {{A} comprehensive dataset of vegetation states, fluxes of
                      matter and energy, weather, agricultural management, and
                      soil properties from intensively monitored crop sites in
                      western {G}ermany},
      journal      = {Earth system science data},
      volume       = {12},
      number       = {4},
      issn         = {1866-3516},
      address      = {Katlenburg-Lindau},
      publisher    = {Copernics Publications},
      reportid     = {FZJ-2020-03294},
      pages        = {2333 - 2364},
      year         = {2020},
      abstract     = {The development and validation of hydroecological
                      land-surface models to simulate agricultural ar-eas require
                      extensive data on weather, soil properties, agricultural
                      management, and vegetation states and fluxes.However, these
                      comprehensive data are rarely available since measurement,
                      quality control, documentation, andcompilation of the
                      different data types are costly in terms of time and money.
                      Here, we present a comprehensivedataset, which was collected
                      at four agricultural sites within the Rur catchment in
                      western Germany in the frame-work of the Transregional
                      Collaborative Research Centre 32 (TR32) “Patterns in
                      Soil–Vegetation–AtmosphereSystems: Monitoring, Modeling
                      and Data Assimilation”. Vegetation-related data comprise
                      fresh and dry biomass(green and brown, predominantly per
                      organ), plant height, green and brown leaf area index,
                      phenological devel-opment state, nitrogen and carbon content
                      (overall>17 000 entries), and masses of harvest residues and
                      regrowthof vegetation after harvest or before planting of
                      the main crop (>250 entries). Vegetation data including
                      LAIwere collected in frequencies of 1 to 3 weeks in the
                      years 2015 until 2017, mostly during overflights of the
                      Sen-tinel 1 and Radarsat 2 satellites. In addition, fluxes
                      of carbon, energy, and water (>180 000 half-hourly
                      records)measured using the eddy covariance technique are
                      included. Three flux time series have simultaneous data
                      fromtwo different heights. Data on agricultural management
                      include sowing and harvest dates as well as informationon
                      cultivation, fertilization, and agrochemicals (27 management
                      periods). The dataset also includes gap-filledweather data
                      (>200 000 hourly records) and soil parameters (particle size
                      distributions, carbon and nitrogencontent;>800 records).
                      These data can also be useful for development and validation
                      of remote-sensing prod-ucts. The dataset is hosted at the
                      TR32 database
                      (https://www.tr32db.uni-koeln.de/data.php?dataID=1889,
                      lastaccess: 29 September 2020) and has the DOI
                      https://doi.org/10.5880/TR32DB.39 (Reichenau et al., 2020).},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255) / DFG project 15232683 - TRR 32: Muster und
                      Strukturen in Boden-Pflanzen-Atmosphären-Systemen:
                      Erfassung, Modellierung und Datenassimilation (15232683) /
                      TERENO - Terrestrial Environmental Observatories
                      (TERENO-2008)},
      pid          = {G:(DE-HGF)POF3-255 / G:(GEPRIS)15232683 /
                      G:(DE-HGF)TERENO-2008},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000576810700001},
      doi          = {10.5194/essd-12-2333-2020},
      url          = {https://juser.fz-juelich.de/record/884858},
}