Trees as Sensors: A New Tool for Slope Movement Detection
October 28, 2025In order to understand how I, a Master student in mathematics, ended up working with real trees (not just the mathematical objects, we have to go back in time to my very first lecture at ETH Zurich. The subject was “Mathematics of Data Science”, and I attended it by coincidence, just because I was told it should be amazing – and it was! But not only was the lecture great, but I also discovered that this topic had exactly the flavour of mathematics I loved.
However, much to the dismay of the computer science students, the lecture stuck strictly to its title, meaning we only learned about the MATHEMATICS behind Data Science and never applied the techniques to real data. When I saw an ad for a short data science internship at the SLF (Institute for Snow and Avalanche Research), I got immediately excited. I wanted to use my newly acquired knowledge on real-world data, and, to my even greater excitement, the data would be in the field of environmental science, a field that I’ve always been interested in. So, just a few mails, a short video call and six months later I was sitting in a train that climbed its way up to the mountain town of Davos for the start of my internship.
The project I would spend the next five weeks working on, was about detecting slow movements of mountain slopes by using tree ring data. You might wonder why we are not using a more straightforward approach, like remote sensing techniques, and instead work with trees? These are wonderful questions!
The first thing one has to know about slope movements is that they are processes that happen over hundreds to thousands of years, whereas remote sensing data is often only available for the last decade.
Therefore, the available data covers a too short period of time to understand these very long-term processes of slope movements well. And that is exactly where trees come in! Trees are widely available on slopes in Europe and can be centuries old. So, if we could use trees as sensors for slope movements, this would extend our data from just a decade to potentially centuries.
And how can we use trees as sensors for slope movements?
The idea behind this approach is that naturally trees always try to grow straight upwards. However, if the slope beneath the trees moves, this tilts the trees and to stand straight again, the trees grow asymmetrically in the following years. This asymmetry can be measured by comparing the differences in tree ring width from two different directions of the trees (don’t worry, there were no trees cut down to collect the data, only two small cores were collected per tree. Sounds like a crazy idea. It is! But it was successfully used by other research groups to detect rapid slope movements. Which leads us to the question: Can we do the same for slow slope movements?

During my five-week journey to answer this question, I tried to apply many of the techniques learned during my course of Data Science. I learned more than I ever thought I would about bark beetles and polar expeditions from chats during lunch. Unfortunately, regardless of what I tried, I could not find a clear relationship between the tree ring data and slow slope movements. However, unexpectedly, I discovered a more rapid event in the data that turned out to coincide perfectly with a documented mudflow in the corresponding area. So, even though I could not answer the initial research question, we could prove again that the method works in the setting of more rapid events.
In addition to my project itself, I had a wonderful summer time in Davos with many after-work hikes and bike tours, I got to know so many nice people from different fields and talking with them really broadened my horizon of what research apart from mathematics can be like. Great thanks go to my supervisors Dr. Alessandra Bottero and Dr. Andrea Manconi who gave me the opportunity to be part of their team and ETH Studio for enabling me this enriching experience!
And if you got curious, then give it a try and apply as well😊!



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