About us

Over the past years, our team has developed a range of methods to support the application of machine learning for spatial data. These methods have been implemented in our R package CAST. From March 11–13, we held our second CAST Package Developer Days. During these three days, the development team came together to revise the package, improve existing functions, and implement new features. More information about the package and its documentation can be found here: https://hannameyer.github.io/CAST/

Since February, Fyeqa Akram has joined our research team as a research associate and doctoral candidate. She will be working on our Twente–Münster collaboration project, “Quantifying and Modelling Peat Breathing with Satellite Radar Data,” which we supervise jointly with Ling Chang from the University of Twente. We are very much looking forward to the collaboration!

We are pleased to announce that R Coding for Ecology (Springer, 2025) has now been published with contributions from our group! The book features our CAST package, which implements key methods for spatial predictive modeling developed by our group. These methods are illustrated in a reproducible way using the example of mapping plant species richness. In addition, Jakub authored several other chapters, including contributions on landscapemetrics, cblindplotR, and cartogram.

Read more here: https://link.springer.com/book/10.1007/978-3-031-99665-8

Maiken Baumberger successfully defended her dissertation on 31.10.2025 and was awarded a doctorate in natural sciences. The title of her thesis is: „Landscape-scale modelling of soil properties in space, depth and time: an interpretable machine learning approach”. Congratulations from your working group!

With 14 students from Landscape Ecology in Münster and Physical Geography in Frankfurt, we spent 17 days on excursion – from Helsinki to Hamningberg in Varanger and back through western Finland. Along the way, we explored various topics in physical geography. We examined the omnipresent traces of the Ice Age, studied Finland’s agriculture and forestry, got to know Aapa and Palsa mires, and visited peatland restoration projects. In Lapland, we focused on cultural and ecological aspects of reindeer grazing as well as the traditions of the Sámi. The impacts of climate change on these ecosystems were a recurring central theme. We spent most of the trip camping, which allowed us to experience and enjoy the landscape with its numerous lakes particularly intensively, alongside the scientific program.
 

On July 3, our working group day took place at the Wersehaus. We discussed and developed the strategies and content of the working group together and then paddled, barbecued and had a great day in a convivial atmosphere.

From March 24th to 25th, we hosted an international workshop at our institute, focusing on advances in spatial machine learning (see https://jakubnowosad.com/advsml_2025/). Seventeen colleagues from various institutions joined us to discuss key topics such as model validation, uncertainty assessment, and interpretability. The event was inspiring, and we look forward to continuing the discussions with follow-up activities.

In April, Jan Steen starts as our new working group member and as a PhD student in our new project "Ready for Take-Off?!". Funded by the DBU and with our projects partners, we will utilize and develop new usecases of drone remote sensing for an improved habitat monitoring.

In our new projekt Sensorlök, we want to integrate environmental sensors into teaching at the Institute of Landscape Ecology in order to train students to implement innovative methods of environmental monitoring in practice. Led by Marvin Ludwig, a sensor network will be set up by students in our teaching and research area “Lüntener Wald” in the summer term '25 that automatically measures, transmits and evaluates groundwater levels, microclimate and soil parameters.

Our new project “Ready for Take-Off!?” starts in April. Together with the Biologischen Station Zwillbrock, the LWL and the Nationalpark Vorpommersche Boddenlandschaft, we are developing and evaluating drone remote sensing methods to support the flora-fauna-habitat monitoring of grassland and heath habitat types. The focus is on the reliable estimation of habitat quality criteria and the applicability of the methods for users in practice.

In a joint publication by the Animal Ecology working group and ourselves, and led by our former Master's student Alina Krämer, we modelled the habitat suitability of the sand lizard at its north-western distribution limit. The results have now been published in the Journal of Biogeography: https://doi.org/10.1111/jbi.15099

From Januray on, Darius Görgen will join our research team as a scientific assistant and PhD student.
He will work in our new project "Deep learning in Space and time", which is part of the Transregio 391 - Spatio-temporal Statistics for the Transition of Energy and Transport (https://trr391.tu-dortmund.de/).
In our subproject, we will explore new methods for using deep learning in the context of spatio-temporal earth observation data.