@article{HannemannPapazachosOhrnbergeretal.2014,
  author    = {Hannemann, Katrin and Papazachos, Costas and Ohrnberger, Matthias and Savvaidis, Alexandros and Anthymidis, Marios and Lontsi, Agostiny Marrios},
  title     = {Three-dimensional shallow structure from high-frequency ambient noise tomography: New results for the Mygdonia basin-Euroseistest area, northern Greece},
  series = {Journal of geophysical research : Solid earth},
  volume    = {119},
  journal   = {Journal of geophysical research : Solid earth},
  number    = {6},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {2169-9313},
  doi       = {10.1002/2013JB010914},
  pages     = {4979 -- 4999},
  year      = {2014},
  abstract  = {We examine the use of ambient noise cross-correlation tomography for shallow site characterization using a modified two-step approach. Initially, we extract Rayleigh wave traveltimes from correlation traces of vertical component seismic recordings from a local network installed in Mygdonia basin, northern Greece. The obtained Rayleigh wave traveltimes show significant spatial variability, as well as distance and frequency dependence due to the 3-D structure of the area, dispersion, and anelastic attenuation effects. The traveltime data sets are inverted through a surface wave tomography approach to determine group velocity maps for each frequency. The proposed tomographic inversion involves the use of approximate Fresnel volumes and interfrequency smoothing constraints to stabilize the results. In the last step, we determine a final 3-D velocity model using a node-based Monte Carlo 1-D dispersion curve inversion. The reliability of the final 3-D velocity model is examined by spatial and depth resolution analysis, as well as by inversion for different model parameterizations. The obtained results are in very good agreement with previous findings from seismic and other geophysical methods. The new 3-D VS model provides additional structural constraints for the shallow sediments and bedrock structure of the northern Mygdonia basin up to the depth of similar to 200-250 m. Present work results suggest that the migration of ambient tomography techniques from large scales (tens or hundreds of km) to local scales (few hundred meters) is possible but cannot be used as a black box technique for 3-D modeling and detailed geotechnical site characterization.},
  language  = {en}
}
@article{RiggelsenOhrnberger2014,
  author    = {Riggelsen, Carsten and Ohrnberger, Matthias},
  title     = {A machine learning approach for improving the detection capabilities at 3C Seismic Stations},
  series = {Pure and applied geophysics},
  volume    = {171},
  journal   = {Pure and applied geophysics},
  number    = {3-5},
  publisher = {Springer},
  address   = {Basel},
  issn      = {0033-4553},
  doi       = {10.1007/s00024-012-0592-3},
  pages     = {395 -- 411},
  year      = {2014},
  abstract  = {We apply and evaluate a recent machine learning method for the automatic classification of seismic waveforms. The method relies on Dynamic Bayesian Networks (DBN) and supervised learning to improve the detection capabilities at 3C seismic stations. A time-frequency decomposition provides the basis for the required signal characteristics we need in order to derive the features defining typical "signal" and "noise" patterns. Each pattern class is modeled by a DBN, specifying the interrelationships of the derived features in the time-frequency plane. Subsequently, the models are trained using previously labeled segments of seismic data. The DBN models can now be compared against in order to determine the likelihood of new incoming seismic waveform segments to be either signal or noise. As the noise characteristics of seismic stations varies smoothly in time (seasonal variation as well as anthropogenic influence), we accommodate in our approach for a continuous adaptation of the DBN model that is associated with the noise class. Given the difficulty for obtaining a golden standard for real data (ground truth) the proof of concept and evaluation is shown by conducting experiments based on 3C seismic data from the International Monitoring Stations, BOSA and LPAZ.},
  language  = {en}
}