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@ARTICLE{Reichenau:820928,
      author       = {Reichenau, Tim G. and Korres, Wolfgang and Montzka, Carsten
                      and Fiener, Peter and Wilken, Florian and Stadler, Anja and
                      Waldhoff, Guido and Schneider, Karl},
      title        = {{S}patial {H}eterogeneity of {L}eaf {A}rea {I}ndex ({LAI})
                      and {I}ts {T}emporal {C}ourse on {A}rable {L}and:
                      {C}ombining {F}ield {M}easurements, {R}emote {S}ensing and
                      {S}imulation in a {C}omprehensive {D}ata {A}nalysis
                      {A}pproach ({CDAA})},
      journal      = {PLoS one},
      volume       = {11},
      number       = {7},
      issn         = {1932-6203},
      address      = {Lawrence, Kan.},
      publisher    = {PLoS},
      reportid     = {FZJ-2016-06192},
      pages        = {e0158451 -},
      year         = {2016},
      abstract     = {The ratio of leaf area to ground area (leaf area index,
                      LAI) is an important state variable in ecosystem studies
                      since it influences fluxes of matter and energy between the
                      land surface and the atmosphere. As a basis for generating
                      temporally continuous and spatially distributed datasets of
                      LAI, the current study contributes an analysis of its
                      spatial variability and spatial structure.
                      Soil-vegetation-atmosphere fluxes of water, carbon and
                      energy are nonlinearly related to LAI. Therefore, its
                      spatial heterogeneity, i.e., the combination of spatial
                      variability and structure, has an effect on simulations of
                      these fluxes. To assess LAI spatial heterogeneity, we apply
                      a Comprehensive Data Analysis Approach that combines data
                      from remote sensing (5 m resolution) and simulation (150 m
                      resolution) with field measurements and a detailed land use
                      map. Test area is the arable land in the fertile loess plain
                      of the Rur catchment on the Germany-Belgium-Netherlands
                      border. LAI from remote sensing and simulation compares well
                      with field measurements. Based on the simulation results, we
                      describe characteristic crop-specific temporal patterns of
                      LAI spatial variability. By means of these patterns, we
                      explain the complex multimodal frequency distributions of
                      LAI in the remote sensing data. In the test area,
                      variability between agricultural fields is higher than
                      within fields. Therefore, spatial resolutions less than the
                      5 m of the remote sensing scenes are sufficient to infer LAI
                      spatial variability. Frequency distributions from the
                      simulation agree better with the multimodal distributions
                      from remote sensing than normal distributions do. The
                      spatial structure of LAI in the test area is dominated by a
                      short distance referring to field sizes. Longer distances
                      that refer to soil and weather can only be derived from
                      remote sensing data. Therefore, simulations alone are not
                      sufficient to characterize LAI spatial structure. It can be
                      concluded that a comprehensive picture of LAI spatial
                      heterogeneity and its temporal course can contribute to the
                      development of an approach to create spatially distributed
                      and temporally continuous datasets of LAI.},
      cin          = {IBG-3},
      ddc          = {500},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255)},
      pid          = {G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000380005400061},
      doi          = {10.1371/journal.pone.0158451},
      url          = {https://juser.fz-juelich.de/record/820928},
}