% 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”.

@PHDTHESIS{Rtzer:810733,
      author       = {Rötzer, Kathrina},
      title        = {{S}tatistical analysis and combination of active and
                      passive microwave remote sensing methods for soil moisture
                      retrieval},
      volume       = {321},
      school       = {Universität Bonn},
      type         = {Dr.},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {FZJ-2016-03325},
      isbn         = {978-3-95806-143-9},
      series       = {Schriften des Forschungszentrums Jülich Reihe Energie $\&$
                      Umwelt / Energy $\&$ Environment},
      pages        = {XIV, 112 S.},
      year         = {2016},
      note         = {Universität Bonn, Diss., 2016},
      abstract     = {Knowledge about soil moisture and its spatio-temporal
                      dynamics is essential for the improvement of climate and
                      hydrological modeling, including drought and flood
                      monitoring and forecasting, as well as weather forecasting
                      models. In recent years, several soil moisture products from
                      active and passive microwave remote sensing have become
                      available with high temporal resolution and global coverage.
                      However, for the improvement of a soil moisture product and
                      for its proper use in models or other applications,
                      validation and evaluation of its spatial and temporal
                      patterns are of great importance. In chapter 2 the Level 2
                      Soil Moisture and Ocean Salinity (SMOS) soil moisture
                      product and the Advanced Scatterometer (ASCAT) surface soil
                      moisture product are validated in the Rur and Erft
                      catchments in western Germany for the years 2010 to 2012
                      against a soil moisture reference created by a hydrological
                      model, which was calibrated by in situ observations.
                      Correlation with the modeled soil moisture reference results
                      in an overall correlation coefficient of 0.28 for the SMOS
                      product and 0.50 for ASCAT. While the correlation of both
                      products with the reference is highly dependent ontopography
                      and vegetation, SMOS is also strongly influenced by
                      radiofrequency interferences in the study area. Both
                      products exhibit dry biases as compared to the reference.
                      The bias of the SMOS product is constant in time, while the
                      ASCAT bias is more variable. For the investigation of spatio
                      temporal soil moisture patterns in the study area, a new
                      validation method based on the temporal stability analysis
                      is developed. Through investigation of mean relative
                      differences of soil moisture for every pixel the temporal
                      persistence of spatial patterns is analyzed. Results
                      indicate a lower temporal persistence for both SMOS and
                      ASCAT soil moisture products as compared to modeled soil
                      moisture. ASCAT soil moisture, converted to absolute values,
                      shows highest consistence of ranks and therefore most
                      similar spatio-temporal patterns with the soil moisture
                      reference, while the correlation of ranks of mean relative
                      differences is low for SMOS and relative ASCAT soil moisture
                      products. Chapter 3 investigates the spatial and temporal
                      behavior of the SMOS and ASCAT soil moisture products and
                      additionally of the ERA Interim product from a weather
                      forecast model reanalysis on global scale. Results show
                      similar temporal patterns of the soil moisture products, but
                      high impact of sensor and retrieval types and therefore
                      higher deviations in absolute soil moisture values. Results
                      are more variable for the spatial patterns of the soil
                      moisture products: While the global patterns are similar, a
                      ranking of mean relative differences reveals that ASCAT and
                      ERA Interim products show most similar spatial soil moisture
                      patterns, while ERA and SMOS products show least
                      similarities. Patterns are generally more similar between
                      the products in regions with low vegetation. [...]},
      cin          = {IBG-3},
      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)11},
      url          = {https://juser.fz-juelich.de/record/810733},
}