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Faculty of Mathematics and Natural Sciences - Earth Observation Lab

Franz Schug

Franz Schug
Status Doctoral researcher
E-Mail franz.schug@geo.hu-berlin.de
Office location Rudower Chaussee 16, Room 2'212, 12489 Berlin, Germany
Phone +49 (0)30 2093-6883
Postal address Unter den Linden 6, 10099 Berlin, Germany


About me

My current research contributes to the MAT_STOCKS project. We use different remote sensing and geoinformation methods to map and quantify anthropogenic material stock patterns in the broad context of social sustainability and transformation research.

Generally, my research interest is related to methods and technologies in remote sensing, geodata processing, modeling and visualization and their application in urban areas, e.g. for urban expansion and land cover change monitoring.


Curriculum Vitae

since 03/2018   

Doctoral Researcher, Geomatics Lab

Humboldt-Universität zu Berlin, Germany.

2014 - 2017

M.Sc. Physical Geography

Humboldt-Universität zu Berlin, Germany

  • Land system science, spatial analysis and statistics, (web-)mapping and visualization, coupled humand-environment systems, mobile app and LBS development
2015 - 2016

Visiting Student

Simon Fraser University, Canada

  • Spatial modeling, Unity3D for Geographic applications

2011 - 2014

B.Sc. Geography (major) / Computer Sciences (minor)

Humboldt-Universität zu Berlin, Germany.

  • Optical remote sensing of urban areas and vegetation, spatial data analysis and methods of geoinformation science

Please find a complete résumé for download here (pdf)




Schug, F.; Frantz, D.; van der Linden, S.; Hostert, P. (2021): Gridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates. PLOS ONE, 16(3). doi: 10.1371/journal.pone.0249044

Haberl, H.; Wiedenhofer, D.; Schug, F.; Frantz, D.; Virág, D.; Plutzar, C.; Gruhler, K.; Lederer, J.; Schiller, G.; Fishman, T.; Lanau ,M.; Gattringer, A.; Kemper, T.; Liu, G.; Tanikawa, H.; van der Linden, S.; Hostert, P. (2021): High-Resolution Maps of Material Stocks in Buildings and Infrastructures in Austria and Germany. Environmental Science & Technology, doi: 10.1021/acs.est.0c05642

Frantz, D.; Schug, F.; Okujeni, A.; Navacchi, C.; Wagner, W.; van der Linden, S.; Hostert, P. (2021): National-scale mapping of building height using Sentinel-1 and Sentinel-2 time series. Remote Sensing of Environment, vol. 252. doi: 10.1016/j.rse.2020.112128

Wellmann, T.; Lausch, A.; Andersson, E.; Knapp, S.; Cortinovis, C.; Jache, J.; Scheuer, S.; Kremer, P.; Mascarenhas, A.; Kraemer, R.; Haase, A.;  Schug, F.; Haase, D. (2020): Remote Sensing in urban planning: Contributions towards ecologically sound policies? Landscape and Urban Planning, vol. 204. doi: https://doi.org/10.1016/j.landurbplan.2020.103921

Schug, F.; Frantz, D.; Okujeni, A.; van der Linden, S.; Hostert, P. (2020): Mapping urban-rural gradients of settlements and vegetation at national scale using Sentinel-2 spectral-temporal metrics and regression-based unmixing with synthetic training data. Remote Sensing of Environment, vol. 246. doi: 10.1016/j.rse.2020.111810

Wellmann, T.; Schug, F.; Haase, D.; Pflugmacher, D.; van der Linden, S. (2020): Green growth? On the relation between popoulation density, land use and vegetation cover fractions in a city using a 30-years Landsat time series. Landscape and Urban Planning, vol. 202. doi: 10.1016/j.landurbplan.2020.103857

Schug, F.; Okujeni, A.; Hauer, J.; Hostert, P.; Nielsen, J. Ø.; van der Linden, S. (2018): Mapping patterns of urban development in Ouagadougou, Burkina Faso, using machine learning regression modeling with bi-seasonal Lnadsat time series. Remote Sensing of Environment, vol. 210, 218-227. doi: 10.1016/j.rse.2018.03.022