None at the moment.
If you have your own idea for a master’s project and are enrolled in Lund University (at INES or CEC), I may be able to supervise you provided you are: (1) a self-starter, (2) have strong foundations in remote sensing, GIS, and basic statistics as evidenced by graduate-level coursework, and (3) have experience in, or are willing to learn, programming (e.g. R, Python, etc.) and quantitative methods (e.g. machine learning).
Camilla Persson (MSc in Geomatics, Lund University):
Thesis: Comparing the vegetation condition of 2017 and 2018 over southern Sweden using Sentinel-2 satellite imagery.
Emma Bylund (MSc in Geographic Information Systems, Lund University):
Thesis: An analysis of the causes of the 2004 and 2007 desert locust outbreaks in Niger and Yemen and their implications on food security using remote sensing and GIS.
Enass Al Kharusi (PhD in Geobiosphere Science, Lund University)
Dissertation: Remote sensing and forecasting techniques for monitoring surface water quality.
4. Enzo Zerega (2018, co-supervisor)
Thesis: Assessing edge pixel classification and growing stock volume in forest stands using a machine learning algorithm and Sentinel-2 data. Master of Science in Geomatics. Department of Physical Geography and Ecosystem Science, Lund University.
3. Abdalla Eltayeb (2017)
Thesis: Mapping woody canopy cover in the semi-arid Sahel: an approach using satellite remote sensing and Google Earth imagery. Master of Science in Geomatics. Department of Physical Geography and Ecosystem Science, Lund University.
2. Stefanos Georganos (2016) ***
Thesis: Exploring the spatial relationship between NDVI and rainfall in the semi-arid Sahel using geographically weighted regression. Master of Science in Geomatics. Department of Physical Geography and Ecosystem Science, Lund University.
*** Thesis published in Journal of Arid Environments
1. Deborah Bowyer (2015)
Thesis: Measuring Urban Growth, Urban Form and Accessibility as Indicators of Urban Sprawl in Hamilton, New Zealand. Master of Science in Geographical Information Science. Department of Physical Geography and Ecosystem Science, Lund University.