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 (WWU) [en]. 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] und and has the aim to contribute to an increase in knowledge in ecosystem research via satellite data processing, modelling and simulation.

© Candy Fahrenholz

Drone mission in Namibia for vulture conservation

Our master student Candy Fahrenholz was working in the Kuzikus Wildlife Reserve in Namibia as part of her master thesis. One focus of her research was to survey the small-scale landscape structures using drone-based remote sensing. With the help of this high-resolution image data, the research question "Which environmental parameters affect nest tree selection of endangered vulture species in Namibia?" will be answered.

Marvin Ludwig after the successful defense of his thesis
© Marvin Ludwig


Marvin Ludwig successfully defended his dissertation on 10.02.2023 and was awarded a doctorate in natural sciences. The title of the thesis is: „Remote sensing and machine learning for multi-scale ecosystem monitoring”. Congratulations from your working group!

© Marvin Ludwig

New Publication in Global Ecology and Biogeography

Global-scale maps of the environment are an important source of information for researchers and decision makers. Often, these maps are created by training machine learning algorithms on field-sampled reference data using remote sensing information as predictors. Since field samples are often sparse and clustered in geographic space, model prediction requires a transfer of the trained model to regions where no reference data are available. However, recent studies question the feasibility of predictions far beyond the location of training data. Here, we propose a novel workflow for spatial predictive mapping that leverages recent developments in this field and combines them in innovative ways with the aim of improved model transferability and performance assessment. We demonstrate, evaluate and discuss the workflow with data from recently published global environmental maps. The publication can be found here: Ludwig, M., Moreno-Martinez, A., Hölzel, N., Pebesma, E., Meyer, H. (2023): Assessing and improving the transferability of current global spatial prediction models. Global Ecology and Biogeography.

Profile probes during the year
© Maiken Baumberger

Fieldwork in the Carbon4D project is completed

In the last 15 month, we measured the soil temperature and the soil moisture at 250 different locations in our 20 x 20 km large study area in the Fichtel Mountains. At each location the measurement duration was one week or one month. Thus, we now have a dataset with measurements at different locations (forest sites, meadows, and fields) under a variety of meteorological conditions. Now we want to use the data set to model the soil temperature and the soil moisture in the study area continuously in 4D, i.e., for each location, the entire time span, and every soil depth.

We're looking for a new team member!

We're looking for someone working with us on our upcoming project "BEyond - Learning from the Exploratories to make prediction beyond them: AI-based mapping and explanation of grassland biodiversity and ecosystem functions for entire landscape units”. The project is part of the Biodiversity Exploratories and will start 1st March 2023 or later. We're looking forward to interesting applications.  Find the full description here: https://www.uni-muenster.de/Rektorat/Stellen/ausschreibungen/st_20221111_sk21.html

Team photo from project meeting
© Carbon4D

Carbon-4D project meeting

Our second project meeting of the Carbon-4D project took place in the Fichtelgebirge on October 7. Together with the Soil Ecology of the University of Bayreuth, the current status of the project and initial results were discussed. The measurements of soil temperature and moisture have been running since September 2021 and will continue until December this year. Further information on the project can be found on the project page [en].

Group Picture Earth Observation Network 2022
© Earth Observation Network

Joint excursion/workshop of the Earth Observation Network

We had a great week in the Harz mountains (12.9.22-16.09.22) where students from our institute came together with students from the university of Göttingen, HAWK Göttingen as well as from the University of Würzburg. We learned about current challenges in forestry in the Harz region and how we can support a monitoring of the forests with remote sensing techniques. Especially the interdisciplinarity of the group (students of landscape ecology, forestry, forest science, remote sensing) was a great experience. During Walk&Talk through the National Park, we had the opportunity to exchange ideas between the groups and then to combine the different areas in a joint project work. We are already looking forward to the next joint event next year!

Group Picture OpenGeoHub 2022
© OpenGeoHub

OpenGeoHub Summer School

This year's OpenGeoHub Summer School took place from 28.8.-3.9.2022 in Siegburg. As in previous years, there was also a workshop from us, this time on the topic of „Machine learning-based maps of the environment: challenges of extrapolation and overfitting“. The course material is available on Github. The recordings of the lecture and exercise are available. The processed versions will be linked later on our course-website.


Presentation of the course projects
Presentation of the course projects
© Hanna Meyer
  • Poster by Katharina Küpers und Ariane Rehn
    © Katharina Küpers und Ariane Rehn
  • Poster by Fynn Riepe
    © Fynn Riepe
  • Poster by Daniel Dabelstein und Florian Stegmann
    © Daniel Dabelstein und Florian Stegmann
  • Poster by Viktoria Mosch und Damian Stickdorn
    © Viktoria Mosch und Damian Stickdorn
  • Poster by Robert Schmitz und Hendrik Lüning
    © Robert Schmitz und Hendrik Lüning
  • Poster by Jessica Groß und Helena Kunkis
    © Jessica Groß und Helena Kunkis

Winners of poster prizes in the bachelor course "Introduction to Remote Sensing"

As part of the course "Introduction to Remote Sensing" for landscape ecologists and geoinformaticians, the presentation of the course projects took place this week.We were impressed by the diversity and quality of the projects!

Winners of the poster award this year are:

1st place: Viktoria Mosch and Damian Stickdorn (heavy rainfall event in the Berchtesgadener Land)

2nd place: Fynn Riepe (Land use changes around the ancient city of Doliche / Dülük since 1992)

3rd place: Jessica Groß and Helena Kunkis (Destruction of peat swamp forests on Borneo in Sebangau National Park)

4th place: Robert Schmitz and Hendrik Lüning (volcanic eruption on La Palma)

5th place: Daniel Dabelstein and Florian Stegmann (impact of the Dos Bocas oil refinery, built in 2018, on the mangrove forest in the Mexican state of Tabasco)

6th place: Katharina Küpers and Ariane Rehn (Black Summer in New South Wales - vegetation loss due to 2019/2020 fires).


© Marvin Ludwig
  • © Maiken Baumberger
  • © Hanna Meyer
  • © Hanna Meyer
  • © Marvin Ludwig
  • © Maiken Baumberger

After two years of remote conferences, this year we were happy to finally participate in person again. We had inspiring sessions and meetings at the ESA Living Planet Symposium in Bonn along with great discussion at our poster contributions from the Carbon4D and Uebersat Projects. Model transferability, along with utilizing cloud computing in openEO, was also part of a poster at the International Symposium of Remote Sensing and Photogrammetry in Nice.

New publication in Nature Communications

The recent wave of published global maps of ecological variables has caused as much excitement as it has received criticism. In our new publication "Machine learning-based global maps of ecological variables and the challenge of assessing them", we look into the data and methods mostly used for creating these maps, and discuss whether the quality of predicted values can be assessed, globally and locally.

Meyer H, Pebesma E. 2022. ‘Machine learning-based global maps of ecological variables and the challenge of assessing them.’ Nature Communications 13.
Link to the paper

New publication in Methods in Ecology & Evolution

In a new publication "Nearest neighbour distance matching Leave-One-Out Cross-Validation for map validation" led by our former master student Carles Mila, we propose a new cross-validation method that considers the geographical prediction space of spatial prediction models to obtain better accuracy estimates.

Mila C, Mateu J, Pebesma E, Meyer H. 2022. ‘Nearest neighbour distance matching leave-one-out cross-validation for map validation.’ Methods in Ecology and Evolution n/a.
Link to the paper [en]

© Jan Lehmann

Study project Amtsvenn - The UAS-field season 2022 has been successfully started

As part of the study project Amtsvenn the first UAS flight campaign was successfully conducted on the 3rd of March 2022. High-resolution multispectral and very high-resolution RGB imagery was collected with the WingtraOne. The campaign was supervised by the “Biologische Station Zwillbrock e.V.” to survey the low disturbance of the UAS on wildlife and no disturbances were observed.
The study project investigates how UAS imagery can be used to detect and spatially model the humidity and vitality of bog vegetation. For ground truth, humidity and temperature are measured in a measurement setup developed by the students, representing different gradients (elevation, vegetation, degradation) of the bog.
This study projects follows the ongoing research in the Vechta bogs and kicks off the in April 2022 starting “Reversal Project” [en].
There are many research project, bachelor and master thesis topics for students interested in remote sensing and spatial modelling in bog ecosystems. If interested, please contact Jan Lehmann [en], Hanna Meyer [en] and Laura Giese [en].

Fieldwork in the snowy Fichtelgebirge

Measurements in the Carbon4D project are in full swing and will continue until the end of 2022. Every week, the team from the University of Bayreuth takes 3 cores in the study area to quantify the mineralization of soil organic carbon. Each month, the team from the University of Münster relocates all profile probes to measure soil temperature and moisture. In the picture gallery you can see some impressions of the field work in the snowy Fichtelgebirge. More information can be found on the project page [en].


Installation of a profile probe for measuring soil temperature and soil moisture.
Installation of a profile probe for measuring soil temperature and soil moisture.
© Maiken Baumberger
  • Drilling a hole for the installation of a profile probe.
    © Maiken Baumberger
  • Drilling a hole for a profile probe.
    © Linda Adorf
  • Taking a drill core to quantify soil organic carbon mineralization.
    © Maiken Baumberger
  • Equipment for the installation of a profile probe.
    © Maiken Baumberger
  • Knocking down a soil sampling corer to determine the soil texture.
    © Maiken Baumberger
  • Measurement of soil respiration with a soil respiration chamber.
    © Maiken Baumberger
  • Profile probe for measuring soil temperature and soil moisture.
    © Maiken Baumberger
  • Profile probe for measuring soil temperature and soil moisture.
    © Maiken Baumberger
Graphical Abstract of the paper
© Maite Lezama Valdes

New Publication in the project Antarctic Science Platform

What to do when the spatial or temporal resolution of satellite data is insufficient for the research topic? Our study shows how the strengths of two satellite sensors in terms of spatial and temporal resolution can be combined in a data-driven approach. As a result, from 1999 on, we can generate Land Surface Temperature data with a subdaily temporal and 30m spatial resolution for the Antarctic Dry Valleys – a dataset that can be used for various research applications, such as species distribution modelling or to model further relevant environmental information.

More News...

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