Welcome to the Remote Sensing and Spatial Modelling Research Group
© Hanna Meyer

About us

The Research Group of "Remote Sensing and Spatial Modelling" is part of the Institute of Landscape Ecology (ILOEK) [en] of the University of Münster. We study and teach the acquisition and analysis of spatio-temporal environmental dynamics in a board spectrum of landscape-ecological topics. We combine multi-scale remote sensing data with methods of spatial modelling in order to obtain continuous spatio-temporal information from limited ecological field samples.
The complexity of environmental systems requires the use of modelling strategies that take complex relationships into account. For this reason, we focus on the application of machine learning methods. In addition to their application for research questions in the context of landscape ecology, we also develop new modelling strategies for spatial and spatio-temporal data. Thus, the research group is at the interface between Geoinformatics and Landscape Ecology [en] and has the aim to contribute to an increase in knowledge in ecosystem research via drone data acquisition, satellite data processing, modelling and simulation.

© Adrian Wykrota

Welcome, Jakub!

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.

© AG Fernerkundung & Räumliche Modellierung

Our Group at the GFÖ Conference in Freising

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.

Group picture Summer school 2024
© AG Fernerkundung & Räumliche Modellierung

Earth Observation Summer School in the Harz mountains

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!

© Jan Lehmann

Impressive Poster Presentations in "Introduction to Remote Sensing"

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)

AG Tag 2024
© Jan Lehmann

Working group day 2024

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.

© AG Fernerkundung & räumliche Modellierung

CAST developer week

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:

More News...

Older news can be found in the archive [en] of the Remote Sensing and Spatial Modelling Research Group.