Dr. Marion Stellmes

Former Senior Researcher

Now at
Freie Universität Berlin
Department of Earth Sciences
Institute of Geographical Sciences
Remote Sensing and Geoinformatics

About me

Until October 2016, I was a senior scientist in the Department of Environmental Remote Sensing and Geoinformatics at Trier University, Germany, where I also obtained my PhD in 2012. I received my Diploma in Applied Environmental Sciences in 2002, with an emphasis on optical remote sensing and geomathematics and I wrote my diploma thesis in collaboration with the German Aerospace Centre (DLR), Oberpfaffenhofen, Germany.

I am interested in interdisciplinary environmental research, especially in the evaluation of ecosystem goods and services and I have a strong background in remote sensing based monitoring of land degradation and desertification and worked in many EU-funded projects, amongst others the LADAMER project and the DeSurvey project, which were dedicated to assessment of land degradation in the Mediterranean.Currently, I am involved in the international interdisciplinary project SASSCAL, which is funded by the German Federal Ministry of Education and Research.

I am specialized in time series analysis of medium and coarse resolution remote sensing time series and I have been working for more than ten years in the field of land cover/use change detection. Moreover, I have attented in many field studies and campaigns to collect validation data with spectrometers and many other instruments.

Selected Publications

Stellmes, M., Sonnenschein, R., Röder, A., Udelhoven, T., Sommer, S. & Hill, J. (2015): Land Degradation Assessment and Monitoring of Drylands. In P. Thenkabail (ed.), Remote Sensing of Water Resources, Disasters, and Urban Studies, Remote Sensing Handbook, Volume 3, Boca Raton, USA, p. 417-452.
Download the post-print version here.

Frantz, D., A. Röder, M. Stellmes, and J. Hill (2016): An Operational Radiometric Landsat Preprocessing Framework for Large-Area Time Series Applications.IEEE Transactions on Geoscience and Remote Sensing, 54 (7): 3928-3943. DOI
Download the post-print version here.

Schneibel, A., Stellmes, M., Röder, A., Finckh, M., Revermann, R., Frantz, D. and Hill, J. (2016): Evaluating the trade-off between food and timber resulting from the conversion of Miombo forests to agricultural land in Angola using multi-temporal Landsat data. Science of The Total Environment, 548–549: 390-401. DOI

Stellmes, M., Frantz, D., Finckh, M., Revermann, R., Röder, A. & Hill, J. (2013): Fire frequency, fire seasonality and fire intensity within the Okavango region derived from MODIS fire products. Biodiversity & Ecology, 5, 351-362. 

Stellmes, M., Röder, A., Udelhoven, T. & Hill, J. (2013): Mapping syndromes of land change in Spain with remote sensing time series, demographic and climatic data. Land Use Policy, 30, 685-702. doi: 10.1016/j.landusepol.2012.05.007

Full publication list


SASSCAL is a joint initiative of Angola, Botswana, Namibia, South Africa, Zambia, and Germany, responding to the challenges of global change. The establishment of a Southern African Science Service Centre for Climate Change and Adaptive Land Management could create added value for the whole southern African region. It should be conceptualised and operationalised to complement the excellent existing research and capacity development infrastructures and research initiatives in the region. It should be embedded in the regional and national research. Its mission is to conduct problem-oriented research in the area of adaptation to climate and change and sustainable land management and provide evidence-based advice for all decision-makers and stakeholders to improve the livelihoods of people in the region and to contribute to the creation of an African knowledge-based society.

Fields of Activity

  • Land degradation assessment in Mediterranean area
  • Evaluation of ecosystem goods and services
  • Monitoring in remote sensing
  • Time series analysis
  • Land use/cover classification and land use/cover dynamics
  • Derviation of vegetation-related biophysical parameters
  • Integration of raster and vector layers