About us

We published two new papers within the Carbon4D project, both led by Maiken Baumberger. The papers are advancing high-resolution soil temperature and moisture modeling on a landscape scale. The first paper, published in Geoderma, introduces a novel approach to predict soil temperature and moisture patterns in four dimensions (space, depth, time) for the Fichtelgebirge in Germany, using random forest models. The second paper, published in Environmental Modelling & Software, presents the use of Gated Recurrent Units to take lag effects into account, required to predict time series of moisture and temperature. Both studies offer crucial insights into soil dynamics and will be used by our team to estimate soil respiration in space, time and depth (see Carbon4D).
Read more: https://doi.org/10.1016/j.geoderma.2024.117049 and
https://doi.org/10.1016/j.envsoft.2024.106245

Laura and Nele from our Reversal Team successfully conducted fieldwork at the peatland site 'Bagno Kusowo' in Poland and visited our project partners at Adam Mickiewicz University in Poznań. Over four days of intensive fieldwork, we carried out multiple UAV flights using our RGB, multispectral, and Lidar sensors, in addition to measuring surface moisture and conducting vegetation surveys. We are very grateful for the support from the research team in Poland and all the helping hands involved. It was a wonderful field campaign at this beautiful site, with pristine conditions and a high abundance of stunning Sphagnum magellanicum!

We offer an excursion to Finland and Varanger from 30. Juli – 15. August 2025, covering various topics from landscape ecology and physical geography.
Please let us know if you are interested.
 

Our research group is gaining new strength! Since mid-August, Jakub Nowosad has joined us for two years. Jakub is well known for his book Geocomputation with R and various R packages, such as landscapemetrics. He has successfully secured a Marie Curie Postdoctoral Fellowship, and over the next two years, we will be collaborating on the analysis of spatial patterns in machine learning models. Additionally, Jakub will surely enrich our teaching in the field of spatial data analysis with R from time to time.

Laura, Jan, and Hanna took part in the annual conference of the German Ecological Society from September 9 to 13 in Freising. Laura gave a talk on satellite-based monitoring of moisture conditions in peatlands, Jan presented his work on using the long-term plots of the Biodiversity Exploratories to model species richness across larger areas, and Hanna showcased the latest methodological developments in spatial prediction modeling. We also took the opportunity to connect with other researchers, meet colleagues, and develop new research plans.

institute came together with students from HAWK Göttingen and the University of Marburg. Together, we discussed current challenges in forestry and the Harz National Park and learned about methods to support forest monitoring using remote sensing. The interdisciplinary nature of the group (students of landscape ecology, forestry, and physical geography) was a valuable experience. During our Walk & Talk through the national park, we had the opportunity to exchange ideas between the groups and combine the different focus areas in a joint project. We are already looking forward to the next collaborative event next year!

This year, as part of the course "Introduction to Remote Sensing" for landscape ecologists and geoinformaticians, a poster presentation of the students' own projects was held. The creativity in topic selection and its implementation was once again impressive and brought us much joy.

The winning posters this year were:

Vegetation Periods of the Tandjilé Savannah Region (Eduard Luz & Timo Mätzschker)

Heavy Rainfall in Lower Saxony (Julia Iichmann & Anke Nienaber)

Istanbul Airport (Florian Thiemann & Mika Dinnus)

On June 11, 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.

In the past few years, we developed a number of methods to support the application of machine learning for spatial data. These methods are implemented in the R package CAST. From March 11th to 13th, our development team of the R package gathered together to implement and document new functionalities. The results:

• A Preprint describing our package: https://arxiv.org/abs/2404.06978v1
• Publication of the Package Version CAST 1.0.0 on CRAN: https://CRAN.R-project.org/package=CAST
• New and re-worked Software Tutorials: https://hannameyer.github.io/CAST/