Swiss Federal Institute for Forest, Snow and Landscape Research WSL
Function
Group leader
Group
Swiss Federal Research Institute WSL
Zürcherstrasse 111
8903 Birmensdorf
Site
WSL Birmensdorf Bi HP C 76
Understanding the dynamics of forests in a changing environment is essential for sustainable forest management. This requires knowledge of the key drivers influencing forest status and trends. My research focuses on deriving environmental factors, such as soil properties, soil water availability, and three-dimensional forest structure, for Swiss forests across various spatial scales.
Using these spatial datasets, I model and spatially predict biodiversity and species composition, and examine forest development in response to climate change. To achieve this, I combine machine learning methods with remote sensing and GIS technologies.
Geographic Information Systems. Master course (No. 651-4031-00L) at the Department of Earth Sciences. Yearly course autumn semester.
Geographic Data Processing with Python and ArcGIS. Master course (No. 701-1776-00L) at the Department of Environmental Systems Science. Yearly course (3 day block course) one week before the autumn semester starts.
Geoprocessing with ArcGIS and Python. Module at Certificate of Advanced Studies (CAS) in RIS/GIS at the Institute of Cartography and Geoinformation (Department of Civil, Environmental and Geomatic Engineering).
If you are interested in writing a master thesis in the context of digital soil mapping, modelling biodiversity or forest functions using remote sensing techniques, please contact me.
Keywords: Geographic information science, Remote Sensing, Airborne and terrestrial LiDAR, Machine Learning, Digital soil mapping, Species distribution models, Forest structures, Drought
Zhang Z. 2024. Machine Learning Based Digital Soil Mapping using Ecological Indicator Values for Switzerland. MSc thesis, ETH Zurich. Supervisor Prof. I. Hajnsek.
Paganini R. 2024. Assessment of multitemporal drought damage in beech forests using commercial smallsats. MSc thesis, EPFL. Supervisor Prof. C. Grossiord, Cosupervisor C. Bloom.
Flükiger, L. 2020. Including soil information in high-resolution distribution modelling of woody species. MSc thesis, ETH Zurich. Supervisor Prof. N. Zimmermann, Cosupervisor R. Wüest.
Füglister B. 2020. Spatial distribution and environmental factors of dead spruce stands in the Swiss Plateau and Jura. MSc thesis, ETH Zurich. Supervisor Prof. N. Zimmermann.
Pranga J. 2019. Analysis of drought patterns in beech stands concerning environmental factors, in Switzerland. MSc thesis, University of Freiburg (D), Supervisor Dr. H. Weinacker.
Flavian S. 2019. Modellierungen von Baumarten der Schweiz mit Einbezug der Bewirtschaftung. BSc thesis, ETH Zürich.
Hertzog M. 2017. Modelling soil attributes with the Random Forest method for the Swiss forest area. MSc thesis, ETH Zurich. Supervisor Prof. D. Or, Cosupervisors: A. Papritz, L. Walthert.
Hürlimann R. 2016. Geostatistical modelling of soil pH based on LiDAR-measurements. MSc thesis, Wageningen University. Supervisor Prof. Gerard Heuvelink.
Lenggenhager A. 2014. Modellierung der Bodenacidität mit terrestrischem LiDAR im Alptal. MSc thesis University of Zurich. Supervisor Prof. R. Purves.
Allemann M. 2012. Nachbilden der Bodeneignungskarte für die Waldböden in der Schweiz und ergänzen der Kartierungseinheiten mit Informationen zum Wasser- und Nährstoffspeichervermögen. MSc thesis University of Bern. Supervisor Prof. W. Wilcke, Cosupervisor L. Walthert.
Nussbaum M. 2011. Modellierung des organischen Kohlenstoffgehalts und –vorrats in Schweizer Waldböden. MSc thesis, University of Zurich. Supervisor Prof. M. Schmidt, Cosupervisor A. Papritz.
Camathias L. 2010. Potential von hochauflösenden Höhenmodellen als Indikatoren für die Biodiversität im Wald. MSc thesis University of Bern. Supervisor PD Dr. S. Wunderle, Cosupervisor A. Bergamini.
Stadelmann G. 2008. Modellierung der Waldentwicklung an der Rigi-Nordlehne zur Analyse der Schutzwirkung von Wald gegen Murgang. MSc thesis, ETH Zurich. Supervisor Dr. M. Frehner, Cosupervisors Prof. H. Bugmann, C. Graf.
