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@MISC{Fan:1038101,
      author       = {Fan, Dong and Zhao, Tianjie and Jiang, Xiaoguang and
                      García-García, Almudena and Schmidt, Toni and Samaniego,
                      Luis and Attinger, Sabine and Wu, Hua and Jiang, Yazhen and
                      Shi, Jiancheng and Fan, Lei and Tang, Bohui and Wagner,
                      Wolfgang and Dorigo, Wouter and Gruber, Alexander and
                      Mattia, Francesco and Balenzano, Anna and Brocca, Luca and
                      Jagdhuber, Thomas and Wigneron, Jean-Pierre and Montzka,
                      Carsten and Peng, Jian},
      title        = {{A} global soil moisture product at 1 km resolution based
                      on {S}entinel-1 (2016-2022)},
      publisher    = {PANGAEA},
      reportid     = {FZJ-2025-01148},
      year         = {2025},
      abstract     = {Soil moisture, although a small fraction of total water
                      content, plays a critical role in the Earth's surface
                      water-heat cycle by influencing processes such as
                      evaporation, infiltration, and vegetation growth and
                      development. Remote sensing has emerged as a critical method
                      for obtaining global-scale soil moisture data. A
                      dual-polarization algorithm (DPA) is proposed and the
                      dual-polarization (VV+VH) observations from the Sentinel-1
                      C-band synthetic aperture radar are used to generate a
                      global soil moisture dataset with a spatial resolution of 1
                      km. Due to the observation mode of Sentinel-1, the temporal
                      resolution of this dataset is higher in European and high
                      latitude regions compared to other continents and lower
                      latitude regions. The dataset is provided in raster format,
                      with one set of ascending and one set of descending data for
                      each day, and to ensure data quality, certain areas not
                      suitable for soil moisture retrieval have been excluded,
                      such as water bodies, permanent wetlands, frozen areas, ice
                      and snow covered surfaces, and urban and built-up areas.
                      Feedback and collaboration to improve the dataset is
                      encouraged.},
      keywords     = {1km spatial resolution (Other) / global (Other) / SAR
                      (Other) / Sentinel-1 (Other) / soil moisture/water content
                      (Other) / Binary Object (Other) / Binary Object (File Size)
                      (Other) / Binary Object (Media Type) (Other) / Binary Object
                      (MD5 Hash) (Other) / MATLAB ® - modeling and processing
                      (Other) / Model-Data fusion for understanding Environmental
                      Variability (MoDEV) (Other) / Monitoring and Modelling
                      Climate Change in Water, Energy and Carbon Cycles in the
                      Pan-Third Pole Environment (CLIMATE-Pan-TPE) (Other)},
      cin          = {IBG-3},
      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)32},
      doi          = {10.1594/PANGAEA.968754},
      url          = {https://juser.fz-juelich.de/record/1038101},
}