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Faculty of Mathematics and Natural SciencesInstitute of Geography

Contact

Fabian Reddig


E-mail fabian.reddig(at)uni-koeln.de


Academic career

  • Since 10/21: PhD candidate, GIS & Remote Sensing
  • Since 04/21: PhD candidate, Ecosystem Research,  Department of Geography, University of Cologne

Research Assistant

  • Since 01/21: CRC 806, GIS and Remote Sensing Group, Department of Geography, University of Cologne
  • Since 08/20 – 01/21: GIS and Remote Sensing Group, Department of Geography, University of Cologne

Research Assistant

  • 01/20 - 08/20: Graduate School of Geosciences (GSGS), Department of Geosciences, University of Cologne

Education

  • 01/19: M.Sc.: Modeling the potential distribution of the cushion plant species Oxychloe andina and Distichia muscoides in northwestern Argentina using a maximum entropy modeling approach, University of Cologne
  • 09/15: B.Sc.: Zustandsbewertung von erheblich veränderten Gewässern anhand der Durchgängigkeit für benthischen Organismen - Methodenentwicklung am Fallbeispiel. Philipps University of Marburg

Interests

  • GIS and Spatial Analysis
  • Environmental Modeling
  • Climate and Land-use change
  • Mediterranean, Iberian Peninsula, and South America

Grants

Presentations

  • EGU2022 - Effect of compound events on oak tree vitality in a climate change hotspot: analysis of time series in a traditional Spanish dehesa, EGU General Assembly 2022, online, 23–27 May 2022, EGU22-9852, https://doi.org/10.5194/egusphere-egu22-9852, 2022 (Vortrag: Reddig, F., Bareth, G., and Bogner, C.).
  • EGU2021 - Vegetation dynamics in a climate change hotspot: trend analysis in a Spanish dehesa, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2374, https://doi.org/10.5194/egusphere-egu21-2374, 2021 (Talk: Reddig, F., Bareth, G., and Bogner, C.).

Publications

  • Tilly, N., F. Reddig, U. Lussem, and G. Bareth (2020). First investigation of Mediterranean oak tree vitality with high-resolution Worldview-3 satellite data: comparing ten vegetation Indices and three machine learning classifiers. en. In: ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020, pp. 1069–1076. ISSN: 2194-9034. DOI:10.5194/isprs-archives-XLIII-B3-2020-1069-2020.

Other

Research Gate