Research
My ongoing research is focused on monitoring global vegetation systems, quantifying the resilience of natural ecosystems to climate change, and understanding the hydrology of alpine regions. My methods are data-driven and rely on the combination of high-performance computing and novel statistical methods to explore changes in the Earth system. I am particularly interested in the impacts of short- and long-term climate changes, as well as feedback loops that control the stability of natural ecosystems. I am currently a member of the Remote Sensing and Earth-Surface Processes team at the University of Potsdam. More details of my current and past research projects can be found on my Research and Publications pages.
Teaching
I am involved with the Remote Sensing, geoInformation, and Visualization Masters program at the University of Potsdam, where I teach quantitative data analysis and remote sensing courses. A particular focus is on efficiently analyzing very large remotely sensed datasets using online (e.g. Google Earth Engine) and offline (high-performance computing) approaches. I use the Python programming language extensively in my teaching and research.
Software
I aim to make all of my publication software open-source (see here), and maintain some useful code snippets on github. In particular I maintain a constantly updated set of codes for Google Earth Engine, which I use extensively in my research and teaching. I have also recently been working on low-cost environmental sensors, which I have deployed in the Himalaya. The design documents and ideas behind the sensors can be found on github: https://github.com/UP-RS-ESP/LowCostSensors