Prof. Dr. Sebastian van der Linden
Head of Lab
talk time: Mo. 14-16 h
phone: +49 3834 420 4500
I am an environmental scientist and since 2019 professor of geography at the University of Greifswald. I am heading the Earth Observation and Geoinformation Science Lab. In my research I use Earth observation data to analyse land use and cover and their variation in space and time. This way, I want to contribute to a better understanding of underlying environmental processes and the functioning of human-environment systems. A special focus of my work is on the monitoring of peatlands. Together with my team I work on approaches for quantitative mapping of land cover from multi- and hyperspectral data, mostly at local to regional scales. We use machine learning algorithms and sophisticated learning strategies to achieve more accurate and temporally robust mapping models.
Since 2020, I am a member of the Greifswald Mire Centre (GMC), since 2021 a member of the EnMAP Science Advisory Group (EnSAG) and since 2022 deputy director of the Interdisciplinary Research Centre on Baltic Sea Region Research at University of Greifswald (IFZO).
My teaching reaches from basic modules on geoinformation science and remote sensing to advanced remote sensing modules. The latter include field work and deal with applied questions of environmental science, e.g. land use monitoring or forest and vegetation remote sensing.
|since 10/2019||University of Greifswald - Professor for Geoinformation Science and Remote Sensing at the Department of Geography and Geology|
|01/2007– 09/2019||Humboldt-Universität zu Berlin – Senior scientist and lecturer at the Earth Observation Lab of the Geography Department|
|10/2012 – 03/2018 Managing director (part-time) of the IRI THESys of Humboldt-Universität zu Berlin|
|10/2006– 12/2006||Columbia University, New York – Guest scientist at Lamont-Doherty Earth Observatory|
|01/2004– 09/2006||Humboldt-Universität zu Berlin & Center for Remote Sensing of Land Surfaces at Bonn University – PhD student in scholarship program of German Environmental Foundation (DBU)|
|Dr. rer. nat., Mathematisch-Naturwissenschaftliche Fakultät (01/2008), Dissertation title: „Investigating the potential of hyperspectral remote sensing data for the analysis of urban imperviousness“ (https://edoc.hu-berlin.de/handle/18452/16409)|
|10/1996– 10/2002||Trier University – Student of Applied Environmental Sciences, Majors Remote Sensing, Climatologie, Minors Geomathematics, Hydrology|
|09/1999 – 06/2000 University of Edinburgh – Exchange student|
|Diplom-Umweltwissenschaftler (MSc equivalent 10/2002)|
- van der Linden S, Okujeni A, Canters F, Degerickx J, Heiden U, Hostert P, Priem F, Somers B, Thiel F (2018). Imaging Spectroscopy of Urban Environments. Surveys in Geophysics, pages pending. 10.1007/s10712-018-9486-y
- Jakimow B, Griffiths P, van der Linden S, Hostert P (2018). Mapping pasture management in the Brazilian Amazon from dense Landsat time series. Remote Sensing of Environment, 205(Supplement C), 453-468. 10.1016/j.rse.2017.10.009
- Schug F, Okujeni A, Hauer J, Hostert P, Nielsen JØ, van der Linden S (2018): Mapping patterns of urban development in Ouagadougou, Burkina Faso, using machine learning regression modeling with bi-seasonal Landsat time series. Remote Sensing of Environment, 210, 218-227. 10.1016/j.rse.2018.03.022
- Suess S, van der Linden S, Okujeni A, Griffiths P, Leitão P, Schwieder M, Hostert P (2018). Characterizing 32 years of shrub cover dynamics in Southern Portugal using annual Landsat composites and machine learning regression modeling. Remote Sensing of Environment, 219, 353-364. 10.1016/j.rse.2018.10.004
- van der Linden S, Rabe A, Held M, Jakimow B, Leitão P, Okujeni A, Schwieder M, Suess S, Hostert P (2015). The EnMAP-Box—A Toolbox and Application Programming Interface for EnMAP Data Processing. Remote Sensing, 7(9), 11249. 10.3390/rs70911249
- Okujeni A, van der Linden S, Hostert P (2015). Extending the Vegetation-Impervious-Soil model using simulated EnMAP data and machine learning. Remote Sensing of Environment, 158, 69-80. 10.1016/j.rse.2014.11.009