MSc Topics

Master students interested in writing a thesis in remote sensing are very welcome to approach us to discuss their ideas and suggestions. In general, you should think about your interests, the skills you like to acquire and potential career paths. You should be excited about your topic, as you'll work on it for some months. Just pass by and talk with us about themes you find fascinating, interesting, or simply fun. For your inspiration, we occasionally advertise for specific Master theses. You can find these calls for Master theses below.

This project investigates the genetic diversity of semi-wild varieties of crops living under extreme climatic conditions. The goal is to find genes that could help adapting commercial crops to climate change. 
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Oliver Selmoni

This project aims to quantify the migration speed that wild population should have to persist in a changing habitat. The investigation will be performed by re-analysing existing environmental and genetic data on species adaptation to climate change.
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Oliver Selmoni

This project aims to assess how accurately genetic extinction can be predicted in absence of DNA data. The investigation will be performed through simulations of extinction on virtual populations, and then extended to real-world species.
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Oliver Selmoni

This project aims to investigate how varying levels of drought affect beech seedlings from across Europe, using leaf spectroscopy to explore phenotypic responses and assess the influence of genetic background on drought tolerance.
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Sofia van Moorsel

This project aims to compare the germination rates of European beech and silver fir across different seedling production methods, identifying environmental factors that influence germination and early survival.
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Sofia van Moorsel

The primary objective of this research is to assess the potential of drone-based SfM methodologies in accurately characterizing different forest structures.
More information (PDF, 32 KB) (PDF, 276 KB)
Felix Morsdorf

The objectives of this MSc thesis are to 1) evaluate performance of current computer vision methods, based on convolutional neural networks (CNNs), applied to optical imagery, and 2) adapt them for better performance when applied to SAR images.
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Elias Mendez

This project aims to use existing datasets to find out whether canopy spectra and leaf
spectra are useful to predict the genetic variation within European beech (Fagus sylvatica).
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Sofia van Moorsel

The objective of this MSc thesis is to investigate the current status and potential of polarimetric SAR for change detection purposes in urban and/or natural environments.
More information (PDF, 406 KB)
Elias Mendez

This project aims to understand if the provenance of a tree affects its phenotype based on hundred beech saplings from all over Europe.
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Sofia van Moorsel

The main objective of this MSc thesis is to measure and understand the thermal anisotropy of various surface types and to build up a database
of Bidirectional Temperature Distribution Function (BTDF) measurements.
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Jennifer Adams

The objective of this thesis is to map Plant Functional Diversity of Grasslands in the Swiss National Park using Imaging Spectroscopy Data.
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Christian Rossi

The objective of this thesis is to evaluate different sensors that could be used on lightweight drones, collect spectral measurements within the forest matrix and calibrate/compare the output to laboratory measurement of vegetation properties.
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Mathias Kneubühler

In this MSc, TLS and field data will be collected and the correlation between the ecological value of tree stems and the variations of its surfaces will be analyzed.
More information (PDF, 32 KB)
Felix Morsdorf

Laser remote sensing of vegetation
Felix Morsdorf

Spectroscopic Data Calibration and Validation
Andy Hueni

Imaging spectroscopy of ecosystems in the Swiss National Park
Mathias Kneubühler

Wet snow cover estimation from SAR backscatter time series
David Small

Time-series analysis of SAR backscatter
David Small

Geometric calibration of SAR sensors
David Small

Time series analysis of land surfaces using the Google Earth Engine
Hendrik Wulf