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Staff
apl. Prof. Dr. habil.  Christian Thiel
apl. Prof. Dr. habil. Christian Thiel
apl. Prof. Dr. habil. Christian Thiel
Professor at the FSU Jena - Acting Department Leader

German Aerospace Center (DLR)
in the Helmholtz Association

Institute of Data Science
Data Analysis and Intelligence
Mälzerstraße 3
07745 Jena

Phone:+49 3641 30960 128
Mail:Christian Thiel

 

 

Teaching at the Friedrich Schiller University Jena

  • WS 2020/2021 – GEO 404 / LV 45853: Applied Geoinformatics - Deriving Geo-Information from Twitter Data (4 SWS, joint course with Dr. Kersten)
  • SS 2021 – GEO 345: Introduction to Remote Sensing in Schools (2 SWS, joint course with Dr. Dubois)
  • Supervision of Bachelor and Master theses

 

Academic Career

since 2020   Professor at the Friedrich Schiller University Jena

2019           Appointment as university professor at grade W 2 for geographic remote sensing at the Julius-Maximilians-Universität Würzburg (call not accepted)

2016–2018  Academic Council at the Chair of Remote Sensing at the Friedrich Schiller University Jena

2013–2020  Private lecturer at the Friedrich Schiller University Jena

2013           Venia Legendi in Geography

2013           Habilitation as Dr. rer. nat. habil. at the Friedrich Schiller University Jena

                  Title of thesis: Radar remote sensing over forests
 

2004           Doctorate (Dr. rer. nat.) at the Friedrich Schiller University Jena (summa cum laude)

                  Title of thesis: Extraction of hydrologically relevant parameters from high-resolution polarimetric L-band and interferometric X-band SAR data
 

2000           Diploma in Geography; specialisation in Hydrological Modelling and Geoinformatics

 

Research Interests

  • Integrative Earth Observation: problem-solving-oriented consolidation of different observation data sources
  • Collection and provision of observation data required at DLR (and externally) for R&D and development of market-oriented products
  • Development and implementation of technologies for quality assurance of data during acquisition
  • Further development of acceptance enhancing strategies for new technology to increase the transfer potential
  • Investigation of persuasive technology as a way of improving human-machine interaction 

 

 

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