Univ.Lektor Dipl.-Geoökol. Univ. Dr.rer.nat.
BiographyStefan Schlaffer received the Diplom in Geoecology from University of Bayreuth (Germany) in 2007 and the Dr. rer. nat. (PhD) in Remote Sensing from TU Wien (Austria) in 2017. From 2008 to 2010, he worked as a hydrological modeller at Dr.-Ing. Karl Ludwig Wasserwirtschaft-Wasserbau GmbH in Karlsruhe (Germany) on flood forecasting.
Between 2010 and 2015, he was a research assistant at the GEO department of TU Wien working on automatic delineation of flooded areas from SAR data. In 2015, he received a Marietta Blau scholarship to carry out a research stay in the framework of his PhD at Luxembourg Institute of Science and Technology (LIST). From 2017 to 2018, he was an integrated expert on capacity building in GIS and remote sensing at the Acopian Center for the Environment of the American University of Armenia (AUA) in collaboration with the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ). From 2018 to 2019, he worked as a Research Assistant at the German Aerospace Center (DLR) in Oberpfaffenhofen (Germany) on operational flood mapping from SAR sensors, such as Sentinel-1 and TerraSAR-X.
Since December 2019, he is with the CLIMERS group at TU Wien. His research interests include the retrieval of hydrological variables such as surface water dynamics and soil moisture from earth observation data and their application in hydrology and vegetation studies.
PublicationsCurrently in open discussion:
Schlaffer, S., Chini, M., Dorigo, W., and Plank, S.: Monitoring Surface Water Dynamics in the Prairie Pothole Region Using Dual-Polarised Sentinel-1 SAR Time Series, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2021-330, in review, 2021.
For a complete list of publications please see my Researchgate profile
Brill, F., Schlaffer, S., Martinis, S., Schröter, K., Kreibich, H. (2021) Extrapolating Satellite-Based Flood Masks by One-Class Classification—A Test Case in Houston. Remote Sensing, 13(11), 2042. https://doi.org/10.3390/rs13112042
Zappa, L., Schlaffer, S., Bauer-Marschallinger, B., Nendel, C., Zimmermann, B., Dorigo, W. (2021) Detection and Quantification of Irrigation Water Amounts at 500 m Using Sentinel-1 Surface Soil Moisture. Remote Sensing, 13(9), 1727. https://doi.org/10.3390/rs13091727
Bruggisser, M., Dorigo, W., Dostálová, A., Hollaus, M., Navacchi, C., Schlaffer, S., Pfeifer, N. (2021) Potential of Sentinel-1 C-Band Time Series to Derive Structural Parameters of Temperate Deciduous Forests. Remote Sensing, 13(4), 798. https://doi.org/10.3390/rs13040798
Li, Y., Martinis, S., Wieland, M., Schlaffer, S., Natsuaki, R. (2019) Urban Flood Mapping Using SAR Intensity and Interferometric Coherence via Bayesian Network Fusion. Remote Sensing, 11, 2231. https://doi.org/10.3390/rs11192231
Lindenschmidt K-E, Carstensen D, Fröhlich W, Hentschel B, Iwicki S, Kögel M, Kubicki M, Kundzewicz ZW, Lauschke C, Łazarów A, Łoś H, Marszelewski W, Niedzielski T, Nowak M, Pawłowski B, Roers M, Schlaffer S, Weintrit B. (2019) Development of an Ice Jam Flood Forecasting System for the Lower Oder River—Requirements for Real-Time Predictions of Water, Ice and Sediment Transport. Water, 11(1):95. https://doi.org/10.3390/w11010095
Bechtold, M., Schlaffer, S., Tiemeyer, B., De Lannoy, G. (2018) Inferring Water Table Depth Dynamics from ENVISAT-ASAR C-Band Backscatter over a Range of Peatlands from Deeply-Drained to Natural Conditions. Remote Sens. 2018, 10, 536. https://doi.org/10.3390/rs10040536
Schlaffer, S., Chini, M., Giustarini, L., Matgen, P. (2017) Probabilistic mapping of flood-induced backscatter changes in SAR time series. Int. J. Appl. Earth Obs. Geoinf. 56, 77–87. https://doi.org/10.1016/j.jag.2016.12.003
Schlaffer, S., Chini, M., Dettmering, D., Wagner, W. (2016) Mapping Wetlands in Zambia Using Seasonal Backscatter Signatures Derived from ENVISAT ASAR Time Series. Remote Sensing 8, 402. https://doi.org/10.3390/rs8050402
Giustarini, L., Hostache, R., Kavetski, D., Chini, M., Corato, G., Schlaffer, S., Matgen, P. (2016) Probabilistic Flood Mapping Using Synthetic Aperture Radar Data. IEEE Trans. Geosci. Remote Sens. 54, 6958–6969. https://doi.org/10.1109/TGRS.2016.2592951
Schlaffer, S., Matgen, P., Hollaus, M., Wagner, W. (2015) Flood detection from multi-temporal SAR data using harmonic analysis and change detection. Int. J. Appl. Earth Obs. Geoinf. 38, 15–24. https://doi.org/10.1016/j.jag.2014.12.001
Munier, S., Aires, F., Schlaffer, S., Prigent, C., Papa, F., Maisongrande, P., Pan, M. (2014) Combining data sets of satellite-retrieved products for basin-scale water balance study: 2. Evaluation on the Mississippi Basin and closure correction model. J. Geophys. Res. 119, 12,100-12,116. https://doi.org/10.1002/2014JD021953
Bartsch, A., Trofaier, A.M., Hayman, G., Sabel, D., Schlaffer, S., Clark, D.B., Blyth, E. (2012) Detection of open water dynamics with ENVISAT ASAR in support of land surface modelling at high latitudes. Biogeosciences 9, 703–714. https://doi.org/10.5194/bg-9-703-2012
Reschke, J., Bartsch, A., Schlaffer, S., Schepaschenko, D. (2012) Capability of C-Band SAR for Operational Wetland Monitoring at High Latitudes. Remote Sens. 4, 2923–2943. https://doi.org/10.3390/rs4102923
Wimmer, F., Schlaffer, S., aus der Beek, T., Menzel, L. (2009) Distributed modelling of climate change impacts on snow sublimation in Northern Mongolia. Adv. Geosci. 21, 117–124. https://doi.org/10.5194/adgeo-21-117-2009
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