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@ARTICLE{Montzka:877860,
      author       = {Montzka, Carsten and Bogena, Heye R. and Herbst, Michael
                      and Cosh, Michael H. and Jagdhuber, Thomas and Vereecken,
                      Harry},
      title        = {{E}stimating the {N}umber of {R}eference {S}ites
                      {N}ecessary for the {V}alidation of {G}lobal {S}oil
                      {M}oisture {P}roducts},
      journal      = {IEEE geoscience and remote sensing letters},
      volume       = {18},
      number       = {9},
      issn         = {1545-598X},
      address      = {New York, NY},
      publisher    = {IEEE},
      reportid     = {FZJ-2020-02481},
      pages        = {1530 - 1534},
      year         = {2020},
      abstract     = {The Committee on Earth Observation Satellites (CEOS) Land
                      Product Validation (LPV) subgroup has been established to
                      coordinate the development of standardized validation across
                      the satellite-derived products from different platforms,
                      sensors, and algorithms with reference measurements from the
                      in situ networks. Soil moisture exhibits a high variability
                      in space that challenges the in situ validation. One of the
                      main drivers for this variability is the characteristic
                      heterogeneity in the soil texture. By the machine learning
                      methods using the soil profile measurements and the remotely
                      sensed predictors, spatially continuous maps of basic soil
                      properties such as soil texture and bulk density are
                      available. Those can be used to estimate soil moisture
                      variability within a satellite product grid cell, here
                      exemplarily shown for the Soil Moisture Active Passive
                      (SMAP) 36-km product. The soil moisture standard deviation
                      is described as a function of the mean soil moisture,
                      whereby the approach needs the mean and standard deviation
                      of the hydraulic parameters as input. The resulting global
                      data set helps identifying the number of in situ stations
                      necessary to validate the coarse soil moisture products. For
                      most SMAP grid cells, three to four stations are adequate to
                      estimate the mean soil moisture for validation; however,
                      also regions were identified where 80 stations are
                      necessary.},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {2173 - Agro-biogeosystems: controls, feedbacks and impact
                      (POF4-217)},
      pid          = {G:(DE-HGF)POF4-2173},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000690441200012},
      doi          = {10.1109/LGRS.2020.3005730},
      url          = {https://juser.fz-juelich.de/record/877860},
}