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Felix Schiefer

MSc Felix Schiefer

Doktorand
Forschung
Gruppe: Vegetation
Sprechstunden: Nach Vereinbarung
Raum: 703.3
Tel.: +49 721 608-43829
felix schieferXxt6∂kit edu

Karlsruher Institut für Technologie (KIT)
Institut für Geographie und Geoökologie
Kaiserstr. 12
76131 Karlsruhe
Germany



Felix Schiefer

Themen

  • UAV-based remote sensing
  • Deep learning algorithms
  • Operational vegetation mapping
  • Radiative transfer models

 

Curriculum vitae

Since 2019 Doctoral candidate at the IfGG in the project UAVforSAT - Operationalization of Vegetation Mapping through UAV-based Reference Data Acquisitions and Cloud-based Analysis of Earth Observation Data
2019 M.Sc. Geoecology, KIT, thesis: “Plant phenology affects the retrieval of plant functional traits from canopy reflectance using statistical and RTM-based methods” (Prof. Dr. Sebastian Schmidtlein, Dr. Teja Kattenborn)
2017 - 2019 Student / research assistant, IfGG
2016 B.Sc. Physical Geography, Friedrich-Alexander University Erlangen-Nürnberg, thesis: „Kartierung der invasiven Moosart Campylopus introflexus mittels hyperspektraler Fernerkundung“ (Prof. Dr. Hannes Feilhauer, Dr. Sandra Skowronek)
2015 - 2016 Freelancer, Institut für Vegetationskunde und Landschaftsökologie (IVL), Hemhofen
2014 - 2015 Student Assistant, Institute of Geography, Friedrich-Alexander University Erlangen-Nürnberg

 

 

Publikationen

Beiträge in referierten Zeitschriften
2019Kattenborn, T., Schiefer, F., Zarco-Tejada, P. J., Schmidtlein, S. (2019): Advantages of retrieving pigment content [µg/cm²] versus concentration [%] from canopy reflectance. Remote Sensing of Environment 230(111195). 10.1016/j.rse.2019.05.014 PDF

2018Skowronek, S., Van de Kerchove, R., Rombouts, R., Aerts, R., Ewald, M., Warrie, J., Schiefer, F., Garzón-López, C. X., Hattab, T., Honnay, T., Lenoir, J., Rocchini, D., Schmidtlein, S., Somers, B., Feilhauer, H. (2018): Transferability of species distribution models for the detection of an invasive alien bryophyte using imaging spectroscopy data. International Journal of Applied Earth Observation and Geoinformation, S. 61–72. 10.1016/j.jag.2018.02.001