Faculty of Mathematics and Natural Sciences - Earth Observation Lab

Publications

Suess, S., van der Linden, S.,Okujeni, A., Griffiths, P., Leitão, P.J., Schwieder & Hostert, P. (2018). Characterizing 32 years of shrub cover dynamics in southern Portugal using annual Landsat composites and machine learning regression modeling. Remote Sensing of Environment.

Okujeni, A., van der Linden, S., Suess, S., & Hostert, P. (2016). Ensemble Learning From Synthetically Mixed Training Data for Quantifying Urban Land Cover With Support Vector Regression. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, PP, 1-11. 10.1109/JSTARS.2016.2634859.

Suess, S., van der Linden, S., Okujeni, A., Leitão, P.J., Schwieder, M. & Hostert, P. (2015): Using class-probabilities to map gradual transitions in shrub vegetation from simulated EnMAP data. Remote Sensing, 7(8), 10668–10688. http://doi.org/10.3390/rs70810668.

Leitão, P.J., Schwieder, M., Suess, S., Okujeni, A., Galvão, L.S., van der Linden, S.,& Hostert, P. (2015): Monitoring Natural Ecosystem and Ecological Gradients with EnMAP. Remote Sensing, 7(10): 13098-13119.

van der Linden, S., Rabe, A., Held, M., Jakimow, B., Leitão, P.J., Okujeni, A., Schwieder, M., Suess, S., & Hostert, P. (2015): The EnMAP-Box – a toolbox and application programming interface for EnMAP data processing. Remote Sensing, 7(9), 11249–11266.

Leitão, P.J., Schwieder, M., Suess, S., Catry, I., Milton, E.J., Moreira, F., Osborne, P.E., Pinto, M.J., van der Linden, S.,& Hostert, P. (2015): Mapping beta diversity from space: Sparse Generalised Dissimilarity Modelling (SGDM) for analysing high-dimensional data, Methods in Ecology and Evolution, doi: 10.1111/2041-210X.12378.

Schwieder, M., Leitão, P.J., Suess, S., Senf, C., Hostert, P. (2014): Estimating Fractional Shrub Cover Using Simulated EnMAP Data: A Comparison of Three Machine Learning Regression Techniques, Remote Sensing, 6, 3427-3445.

Suess, S.; van der Linden, S.; Leitao, P.J.; Okujeni, A.; Waske, B.; Hostert, P. (2014): Import Vector Machines for Quantitative Analysis of Hyperspectral Data, Geoscience and Remote Sensing Letters, IEEE , vol. 11, no. 2, pp.1-5, doi: 10.1109/LGRS.2013.2265102. See abstract.

Müller, D., Suess, S., Hoffmann, A., and Buchholz, G. (2014), The Value of Satellite-Based Active Fire Data for Monitoring, Reporting and Verification of REDD+ in the Lao PDR, Human Ecology, pp. 1-14. Download paper.

van der Linden, S., Rabe, A., Held, M., Wirth, F., Suess, S., Okujeni, A., Hostert, P., (2014). imageSVM Classification, Manual for Application: imageSVM version 3.0. Humboldt-Universität zu Berlin, Germany.

van der Linden, S., Rabe, A., Held, M., Wirth, F., Suess, S., Okujeni, A., Hostert, P., (2014). imageSVM Regression, Manual for Application: imageSVM version 3.0. Humboldt-Universität zu Berlin, Germany.

Müller, D. and Suess, S. (2011). Can the MODIS active fire hotspots be used to monitor vegetation fires in the Lao PDR? Climate Protection through Avoided Deforestation Project (CliPAD). Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH. Download report.

Suess, S., van der Linden, S., Leitão, P. J., Rabe, A., Wirth, F., Okujeni, A., Hostert, P. (2010). SVM Regression, EnMAP-Box Application Tutorial: SVM Regression, Humboldt-Universität zu Berlin, Germany. EnMAP-Box Portal.

van der Linden, S., Rabe, A., Leitão, P.J., Suess, S., Wirth, F. Hostert, P. (2010). EnMAP-Box Manual, Version 1.1, Humboldt-Universität zu Berlin, Germany. EnMAP-Box Portal.

van der Linden, S., Wirth, F., Suess, S., Leitão, P. J., Rabe, A., Hostert, P. (2010). EnMAP-Box Application Tutorial: Data handling and visualization, Humboldt-Universität zu Berlin, Germany. EnMAP-Box Portal.

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Suess, S., van der Linden, S., Okujeni, A., Leitão, P.J., Schwieder, M. & Hostert, P. (2015): Using class-probabilities to map gradual transitions in shrub vegetation from simulated EnMAP data. Oral @ 9th EARSeL Workshop of Special Interest Group in Imaging Spectroscopy. Luxembourg.

van der Linden, S., Rabe, A., Held, M., Jakimow, B., Leitão, P.J., Okujeni, A., Schwieder, M., Suess, S. & Hostert, P. (2015): EnMAP-Box 2.1 – an overview of the concept and available applications. Poster @ 9th EARSeL Workshop of Special Interest Group in Imaging Spectroscopy. Luxembourg.

Leitão, P.J., Suess, S., Schwieder, M., van der Linden, S., Hostert, P. (2014). Monitoring ecosystem transitions with EnMAP: preparatory research activities. Proceedings of the Global Land Project 2nd Open Science Meeting, Berlin, Germany, March 19.

Leitão, P.J., Suess, S., Schwieder, M., van der Linden, S., Hostert, P. (2014). Proceedings of the Global Land Project 2 nd Open Science Meeting, Monitoring ecosystem transitions with EnMAP: preparatory research activities, Berlin, Gernmany, March 19.

Suess, S., Leitão, P.J., van der Linden, S., Okujeni, A., Hostert, P. (2013). Import Vector Machines for quantitative mapping of vegetation cover fractions in natural environments. Oral @ National EnMAP-Workshop. Bonn, Germany.

Leitão, P.J., Suess, S., Schwieder, M., Milton, E.J., van der Linden, S., Hostert, P. (2013). Hyperspectral satellite data for modelling spatial beta diversity patterns of birds along an environmental gradient. ESA Living Planet Symposium. September 2013, Edinburgh, UK.

Suess, S., van der Linden, S., Leitão, P.J., Okujeni, A., Waske, B., Hostert, P. (2013). Import Vector Machines for sub-pixel analysis. Poster @ 8th EARSeL Imaging Spectrometry Workshop. Nantes, France.

Rabe, A., Jakimow, B., van der Linden, S., Okujeni, A., Suess, S., Leitão, P.J., Hostert, P. (2013). Simplifying Support Vector Regression Parameterisation by Heuristic Search for Optimal Epsilon-Loss. Poster @ 8th EARSeL Imaging Spectrometry Workshop. Nantes, France.

Leitão, P.J., van der Linden, S., Suess, S., Okujeni, A., Hostert, P. (2012). Monitoring Ecosystem Transitions. Oral @ 3rd National EnMAP-Workshop. Potsdam, Germany.

Suess, S., van der Linden, S., Leitão, P.J., Okujeni, A., Waske, B.,and Hostert, P. (2012). Wrapper approach to optimized parameter selection for quantitative modeling - A case study on synthetically mixed data and Import Vector Machines. Poster @ EnMAP Summerschool. Berlin, Germany.

Suess, S., Müller, (2011). Forest cover change of post-socialist landscapes in Albania and Kosovo: a remote sensing approach. Poster @ 4th EARSeL Workshop on Land Use & Land Cover. Prague, Czech Republic.

Suess, S. (2010). Forest cover change of post-socialist landscapes in Albania and Kosovo: A remote sensing and statistical approach. Thesis.

Müller, D., Suess, S. (2010). Can the MODIS active fire hotspots be used as an input into MRV for REDD+? Oral @ Global Land Project Open Science Meeting, Phoenix, AZ.

Suess, S., van der Linden, S., Leitão, P.J., Okujeni, A., Waske, B.,and Hostert, P. (2013). Import Vector Machines for sub-pixel analysis. Poster @ EnMAP Summerschool. Berlin, Germany.