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Ron Hagensieker


Remote Sensing and Geoinformatics

Former Research Assistant

Research Projects

Self-taught Learning (2016-2017):

DFG - German Research Foundation (WA 2728/3-1)

SenseCarbon (2013-2016):

BMWi/DLR - Förderkennzeichen 50 EE 1255


Master of Science (2010-2013):

Physical Geography (Landscape System Sciences), Eberhard Karls Universität Tübingen.

Master thesis on "Urban Indicators of Da Nang (Vietnam) derived from WorldView-2 Imagery"

Bachelor of Science (2007-2010):

Philipps-Universität Marburg & Eberhard Karls Universität Tübingen

Bachelor Thesis on "GIS-based reconstruction of a 17th century landscape in northern Yunnan (China) for estimation of wooden biomas"


Advanced Geoinformation Processing (MSc. Lab Exercise, FU Berlin): WS 13/14 and WS 14/15

Referee Service

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Discontinued 2017 Journal articles

Hagensieker, R.; Roscher, R.; Rosentreter, J..; Jakimow, B. & Waske, B. (2017): 'Tropical Land Use Land Cover Mapping in Pará (Brazil) using Discriminative Markov Random Fields and Multi-temporal TerraSAR-X Data', International Journal of Applied Earth Observation and Geoinformation

Rosentreter, J.; Hagensieker, R.; Okujeni, A.; Roscher, R.; Wagner, P. D. & Waske, B. (2017): 'Sub-pixel mapping of urban areas using EnMAP data and multioutput support vector regression', Journal of Selected Topics in Applied Earth Observation and Remote Sensing

Braun, A.; Rosner, H.-J.; Hagensieker, R. & Dieball, S. (2015), 'Multi-method dynamical reconstruction of the ecological impact of copper mining on Chinese historical landscapes', Ecological Modelling

Conferences and Proceedings (peer reviewed)

Hagensieker, R. & Waske, B. (2017): 'Synergetic Potentials of C-Band SAR and Multi-Spectral Imagery for Tropical Classifications in Northern Mato Grosso (BR)', IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, USA

Hagensieker, R. & Waske, B. (2016): 'Potentials of multi-temporal TerraSAR-X images for tropical land cover mapping', TerraSAR-X / TanDEM-X Science Team Meeting, Munich, Germany

Griffiths, P.; Jakimow, B.; Hagensieker, R.; Waske, B. & Hostert, P. (2016), 'Novel Land cover and land use mapping methods in support to REDD+', 10th GEO European Projects Workshop, Berlin, Germany

Hagensieker, R. & Waske, B. (2016), 'Mapping Deforestation in Pará (Brazil) Using A Multi-Sensoral Time-Series And Expert Knowledge', ESA Living Planet Symposium, Prague, Czechia

Rosentreter, J., Hagensieker, R., Okujeni, A., Roscher, R., Wagner, P.D. & Waske, B. (2016), 'Sub-Pixel Mapping of Urban Surfaces Using EnMAP Data and Machine Learning Algorithms, ESA Living Planet Symposium, Prague, Czechia

Braun, A., Hagensieker, R. & Hochschild, V. (2016), 'Filling of cloud-induced gaps for land use and land cover classifications around refugee camps', ESA Living Planet Symposium, Prague, Czechia

Hagensieker, R.; Roscher, R. & Waske, B. (2015), 'Mapping of Burnt Areas in Brazilian Amazon using TerraSAR-X Data', IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milano, Italy

Bachofer, F.; Hagensieker, R. & Hochschild, V. (2015), 'A multi-scale approach to derive urban landuse / landcover from multispectral images', 36th International Symposium on Remote Sensing of Environment, Berlin, Germany

Hagensieker, R.; Waske, B. & Roscher, R. (2014), 'Texture-Based Classification of a Tropical Forest Area Using Multi-Temporal ASAR Data', IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Quebec City, Canada

Hagensieker, R.; Waske, B.; Pflugmacher, D. & Hostert, P. (2014), 'Evaluation of GLCM based Texture Parameters for tropical forest mapping with C-band SAR', EARSeL SIG LULC - NASA LCLUS Workshop, Berlin, Germany

Hagensieker, R.; Waske, B.; Pflugmacher; D., Widayati, A. & Hostert, P. (2013), 'Integration of C-band SAR and Multi-Spectral Data for Mapping Tropical Forest Areas in Southeast Asia', ESA Living Planet Symposium, Edinbourgh, Scotland

Hagensieker, R. & Rosner, H.-J. (2011), 'GIS-assisted Modelling of the Historical Climax Forest in North East Yunnan (China) at the Beginning of the 18th Century', GI_Forum 11. Proceedings of the Geoinformatics Symposium, Salzburg, Austria