@article{JagdhuberHajnsekBronstertetal.2013,
  author    = {Jagdhuber, Thomas and Hajnsek, Irena and Bronstert, Axel and Papathanassiou, Konstantinos Panagiotis},
  title     = {Soil moisture estimation under low vegetation cover using a multi-angular polarimetric decomposition},
  series = {IEEE transactions on geoscience and remote sensing},
  volume    = {51},
  journal   = {IEEE transactions on geoscience and remote sensing},
  number    = {4},
  publisher = {Inst. of Electr. and Electronics Engineers},
  address   = {Piscataway},
  issn      = {0196-2892},
  doi       = {10.1109/TGRS.2012.2209433},
  pages     = {2201 -- 2215},
  year      = {2013},
  abstract  = {The estimation of volumetric soil moisture under low agricultural vegetation from fully polarimetric synthetic aperture radar (SAR) data at L-band using a multi-angular polarimetric decomposition is investigated. Radar polarimetry provides the framework to decompose the backscattered signal into different canonical scattering mechanisms referring to scattering contributions from the underlying soil and the vegetation cover. Multiangular observation diversity further increases the information space for soil moisture inversion enabling higher inversion rates and a stable inversion performance. The developed approach was applied on the multi-angular L-band data set acquired by German Aerospace Center's ESAR sensor as part of the OPAQUE campaign in 2008. The obtained results are compared against ground measurements collected by the OPAQUE team over a variety of vegetated agricultural fields. The validation of the estimated against ground measured soil moisture results in an root mean square error level of 6-8 vol.\% including all test fields with a variety of crop types.},
  language  = {en}
}