Dr. Hendrik Paasche

Kontakt/Adresse

Dr. Hendrik Paasche

Wissenschaftlicher Mitarbeiter, Leiter Arbeitsgebiet Datenintegration und Parameterschätzungen

Department Monitoring- und Erkundungstechnologien
Helmholtz-Zentrum für Umweltforschung - UFZ
Permoserstr. 15
04318 Leipzig

Tel: +49 341 6025 2742

hendrik.paasche@ufz.de


Arbeitsgebiete

  • Tomographie und gemeinsame Inversion
  • Datenintegration
  • Oberflächennahe Geophysik
  • Experimental Design

Lebenslauf / Akademische Ausbildung

seit 2012 wissenschaftlicher Mitarbeiter, Arbeitsgruppe Datenintegration und Parameterschätzung, Department Monitoring und Erkundungstechnologien,
Helmholtz-Zentrum für Umweltforschung GmbH - UFZ, Deutschland
2019 Venia Legendi in Geophysik, Mathematisch-Naturwissenschaftliche Fakultät,
Universität Potsdam, Deutschland
2018 Habilitation in Geophysik, Mathematisch-Naturwissenschaftliche Fakultät,
Universität Potsdam, Deutschland
2006 - 2012 wissenschaftlicher Mitarbeiter, Institut für Erd- und Umweltwissenschaften,
Universität Potsdam, Deutschland
2006 Dr. sc. nat. in Geophysik, ETH Zürich, Schweiz
Jan/Feb 2004 Gastwissenschaftler, The Hydrogeophysics Group,
University of Aarhus, Dänemark
2001 - 2006 Doktorand, Institut für Geophysik,
ETH Zürich, Schweiz
2000 - 2001 wissenschaftlicher Mitarbeiter, Institut für Geowissenschaften,
Martin-Luther-Universität Halle-Wittenberg, Deutschland
2000 Diplom in Geophysik, Universität Leipzig, Deutschland
1999 - 2000 Gastwissenschaftler, Department of Water Affairs,
Ministry of Agriculture, Water and Rural Development, Windhoek, Namibia
1995 - 2000 Student im Studiengang Diplom-Geophysik,
Universität Leipzig, Deutschland

Publikationen

in wissenschaftlichen Zeitschriften und Büchern mit peer-review

Lausch, A., Borg, E., Bumberger, J., Dietrich, P., Heurich, M., Huth, A., Jung, A., Klenke, R., Knapp, S., Mollenhauer, H., Paasche, H., Paulheim, H., Pause, M., Schweitzer, C., Schmulius, C., Settele, J., Skidmore, A.K., Wegmann, M., Zacharias, S., Kirsten, T., Schaepman, M.E. (2018): Understanding forest health with remote sensing, part III: Requirements for a scalable multi-source forest health monitoring network based on data science approaches. Remote Sensing, 10, 1120.

Paasche, H. (2018): About probabilistic integration of ill-posed geophysical tomography and logging data: A knowledge discovery approach versus petrophysical transfer function concepts illustrated using cross-borehole radar-, P-, and S-wave traveltime tomography in combination with cone penetration and dielectric logging data. Journal of Applied Geophysics, 148, 175-188.

Schröter, I., Paasche, H., Doktor, D., Xu, X., Dietrich, P., Wollschläger, U. (2017): Estimating soil moisture patterns with remote sensing and terrain data at the small catchment scale. Vadose Zone Journal, 16, doi:10.2136/vzj/2017.01.0012.

Paasche, H. (2017): Translating tomographic ambiguity into the probabilistic inference of hydrologic and engineering target parameters. Geophysics, 82, EN67-EN79.

Asadi, A., Dietrich, P., Paasche, H. (2017): Spatially continuous probabilistic prediction of sparsely measured ground properties constrained by ill-posed tomographic imaging considering data uncertainty and resolution. Geophysics, 82, V149-V162.

Tronicke, J., Paasche, H. (2017): Integrated interpretation of 2D ground-penetrating radar, P-, and S-wave velocity models in terms of petrophysical properties: Assessing uncertainties related to data inversion and petrophysical relations. Interpretation, 5, T121-T130.

Paasche, H. (2016): Post-inversion integration of disparate tomographic models by model structure analyses. In: Moorkamp, M., Lelièvre, P.G., Linde, N., Khan, A., eds., Integrated Imaging of the Earth: Theory and Applications. Wiley, 69-91.

Asadi, A., Dietrich, P., Paasche, H. (2016): 2D probabilistic prediction of sparsely measured earth properties constrained by geophysical imaging fully accounting for tomographic reconstruction ambiguity. Environmental Earth Sciences, 75, 1487.

Schröter, I., Paasche, H., Dietrich, P., Wollschläger, U. (2015): Prediction of soil moisture patterns by means of a fuzzy c-means clustering algorithm, terrain data and sparse TDR measurements. Vadose Zone Journal, 14, doi:10.2136/vzj2015.01.0008.

Demuth, D., Bumberger, J., Paasche, H. (2015): Evaluation of direct push probes: sensor interface analysis of DC resistivity probes. Journal of Applied Geophysics, 122, 218-225.

Bumberger, J., Paasche, H., Dietrich, P. (2015): Systematic description of direct push sensor systems: A conceptual framework for system decomposition as the basis for the optimal sensor design. Journal of Applied Geophysics, 122, 210-217.

Eberle, D., Hutchins, D., Das, S., Majumdar, A., Paasche, H. (2015): Automated pattern recognition to support geological mapping and exploration target generation - A case study from southern Namibia. Journal of African Earth Sciences, 106, 60-74.

Paasche, H., Tronicke, J. (2014): Nonlinear joint inversion of tomographic data using swarm intelligence. Geophysics, 79, R133-R149.

Paasche, H., Eberle, D., Das, S., Cooper, A., Debba, P., Dietrich, P., Dudeni-Thlone, N., Gläßer, C., Kijko, A., Knobloch, A., Lausch, A., Meyer, U., Smit, A., Stettler, E., Werban, U. (2014): Are Earth Sciences lagging behind in data integration methodologies?. Environmental Earth Sciences, 71, 1997-2003.

Sauer, D., Popp, S., Dittfurth, A., Altdorff, D., Dietrich, P., Paasche, H. (2013): Soil moisture assessment over an alpine hillslope with significant soil heterogeneity. Vadose Zone Journal, 12, doi: 10.2136/vzj/2013.01.0009.

Hachmöller, B., Paasche, H. (2013): Integration of surface-based tomographic models for zonation and multi-model guided extrapolation of sparsely known parameters. Geophysics, 78, EN43-EN53.

Eberle, D., Paasche, H. (2012): Integrated data analysis for mineral exploration: A case study for clustering satellite imagery, airborne gamma-ray and regional geochemical data suites. Geophysics, 77, B167-B176.

Tronicke, J., Paasche, H., Böniger, U. (2012): Crosshole traveltime tomography using particle swarm optimization: a near-surface field example. Geophysics, 77, R19-R32.

Paasche, H., Tronicke, J., Dietrich, P. (2012): Zonal cooperative inversion of partially co-located data sets constrained by structural a priori information. Near Surface Geophysics, 10, 103-116.

Paasche, H., Eberle, D. (2011): Automated compilation of pseudo-lithology maps from geophysical data sets: A comparison of Gustafson-Kessel and fuzzy c-means cluster algorithms. Exploration Geophysics, 42, 275-285.

Linder, S., Paasche, H., Tronicke, J., Niederleithinger, E., Vienken, T. (2010): Zonal cooperative inversion of crosshole P-wave, S-wave, and georadar traveltime data sets. Journal of Applied Geophysics, 72, 254-262.

Paasche, H., Tronicke, J., Dietrich, P. (2010): Automated integration of partially colocated models: subsurface zonation using a modified fuzzy c-means cluster algorithm. Geophysics, 75, P11-P22.

Paasche, H., Eberle, D. (2009): Rapid integration of large airborne geophysical data suites using a fuzzy partitioning cluster algorithm: A tool for geological mapping and mineral exploration targeting. Exploration Geophysics, 40, 277-287.

Paasche, H., Werban, U., Dietrich, P. (2009): Near-surface seismic traveltime tomography using a direct-push source and surface-planted receivers. Geophysics, 74, G17-G25.

Holliger, K., Tronicke, J., Paasche, H., Dafflon, B. (2008): Quantitative integration of hydrogeophysical and hydrological data: Geostatistical approaches. In: Darnault, C., ed., Overexploitation and Contamination of Shared Groundwater Resources. Springer, 67-82.

Paasche, H., Wendrich, A., Trela, C., Tronicke, J. (2008): Detecting voids in masonry by cooperatively inverting P-wave and georadar traveltimes. Journal of Geophysics and Engineering, 5, 256-267.

Paasche, H., Tronicke, J., Maurer, H., Green, A.G., Auken, E., Stauffer, F. (2007): Geophysical surveying an active well catchment in the presence of significant topography and anthropogenic disturbances. Near Surface Geophysics, 5, 309-319.

Paasche, H., Tronicke, J. (2007): Cooperative inversion of 2D geophysical data sets: A zonal approach based on fuzzy c-means cluster analysis. Geophysics, 72, A35-A39.

Paasche, H., Tronicke, J., Holliger, K., Green, A.G., Maurer, H. (2006): Integration of diverse physical-property models: Subsurface zonation and petrophysical parameter estimation based on fuzzy c-means cluster analyses. Geophysics, 71, H33-H44.