@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}
}
@phdthesis{Jagdhuber2012,
  author    = {Jagdhuber, Thomas},
  title     = {Soil parameter retrieval under vegetation cover using SAR polarimetry},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-60519},
  school      = {Universit{\"a}t Potsdam},
  year      = {2012},
  abstract  = {Soil conditions under vegetation cover and their spatial and temporal variations from point to catchment scale are crucial for understanding hydrological processes within the vadose zone, for managing irrigation and consequently maximizing yield by precision farming. Soil moisture and soil roughness are the key parameters that characterize the soil status. In order to monitor their spatial and temporal variability on large scales, remote sensing techniques are required. Therefore the determination of soil parameters under vegetation cover was approached in this thesis by means of (multi-angular) polarimetric SAR acquisitions at a longer wavelength (L-band, lambda=23cm). In this thesis, the penetration capabilities of L-band are combined with newly developed (multi-angular) polarimetric decomposition techniques to separate the different scattering contributions, which are occurring in vegetation and on ground. Subsequently the ground components are inverted to estimate the soil characteristics. The novel (multi-angular) polarimetric decomposition techniques for soil parameter retrieval are physically-based, computationally inexpensive and can be solved analytically without any a priori knowledge. Therefore they can be applied without test site calibration directly to agricultural areas. The developed algorithms are validated with fully polarimetric SAR data acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR) for three different study areas in Germany. The achieved results reveal inversion rates up to 99\% for the soil moisture and soil roughness retrieval in agricultural areas. However, in forested areas the inversion rate drops significantly for most of the algorithms, because the inversion in forests is invalid for the applied scattering models at L-band. The validation against simultaneously acquired field measurements indicates an estimation accuracy (root mean square error) of 5-10vol.\% for the soil moisture (range of in situ values: 1-46vol.\%) and of 0.37-0.45cm for the soil roughness (range of in situ values: 0.5-4.0cm) within the catchment. Hence, a continuous monitoring of soil parameters with the obtained precision, excluding frozen and snow covered conditions, is possible. Especially future, fully polarimetric, space-borne, long wavelength SAR missions can profit distinctively from the developed polarimetric decomposition techniques for separation of ground and volume contributions as well as for soil parameter retrieval on large spatial scales.},
  language  = {en}
}
@article{BronstertCreutzfeldtGraeffetal.2012,
  author    = {Bronstert, Axel and Creutzfeldt, Benjamin and Gr{\"a}ff, Thomas and Hajnsek, Irena and Heistermann, Maik and Itzerott, Sibylle and Jagdhuber, Thomas and Kneis, David and Lueck, Erika and Reusser, Dominik and Zehe, Erwin},
  title     = {Potentials and constraints of different types of soil moisture observations for flood simulations in headwater catchments},
  series = {Natural hazards : journal of the International Society for the Prevention and Mitigation of Natural Hazards},
  volume    = {60},
  journal   = {Natural hazards : journal of the International Society for the Prevention and Mitigation of Natural Hazards},
  number    = {3},
  publisher = {Springer},
  address   = {New York},
  issn      = {0921-030X},
  doi       = {10.1007/s11069-011-9874-9},
  pages     = {879 -- 914},
  year      = {2012},
  abstract  = {Flood generation in mountainous headwater catchments is governed by rainfall intensities, by the spatial distribution of rainfall and by the state of the catchment prior to the rainfall, e. g. by the spatial pattern of the soil moisture, groundwater conditions and possibly snow. The work presented here explores the limits and potentials of measuring soil moisture with different methods and in different scales and their potential use for flood simulation. These measurements were obtained in 2007 and 2008 within a comprehensive multi-scale experiment in the Weisseritz headwater catchment in the Ore-Mountains, Germany. The following technologies have been applied jointly thermogravimetric method, frequency domain reflectometry (FDR) sensors, spatial time domain reflectometry (STDR) cluster, ground-penetrating radar (GPR), airborne polarimetric synthetic aperture radar (polarimetric SAR) and advanced synthetic aperture radar (ASAR) based on the satellite Envisat. We present exemplary soil measurement results, with spatial scales ranging from point scale, via hillslope and field scale, to the catchment scale. Only the spatial TDR cluster was able to record continuous data. The other methods are limited to the date of over-flights (airplane and satellite) or measurement campaigns on the ground. For possible use in flood simulation, the observation of soil moisture at multiple scales has to be combined with suitable hydrological modelling, using the hydrological model WaSiM-ETH. Therefore, several simulation experiments have been conducted in order to test both the usability of the recorded soil moisture data and the suitability of a distributed hydrological model to make use of this information. The measurement results show that airborne-based and satellite-based systems in particular provide information on the near-surface spatial distribution. However, there are still a variety of limitations, such as the need for parallel ground measurements (Envisat ASAR), uncertainties in polarimetric decomposition techniques (polarimetric SAR), very limited information from remote sensing methods about vegetated surfaces and the non-availability of continuous measurements. The model experiments showed the importance of soil moisture as an initial condition for physically based flood modelling. However, the observed moisture data reflect the surface or near-surface soil moisture only. Hence, only saturated overland flow might be related to these data. Other flood generation processes influenced by catchment wetness in the subsurface such as subsurface storm flow or quick groundwater drainage cannot be assessed by these data. One has to acknowledge that, in spite of innovative measuring techniques on all spatial scales, soil moisture data for entire vegetated catchments are still today not operationally available. Therefore, observations of soil moisture should primarily be used to improve the quality of continuous, distributed hydrological catchment models that simulate the spatial distribution of moisture internally. Thus, when and where soil moisture data are available, they should be compared with their simulated equivalents in order to improve the parameter estimates and possibly the structure of the hydrological model.},
  language  = {en}
}