Vreugdenhil, Mariette

Senior Scientist Dr.techn. MSc

Research Division:
Remote Sensing
University Assistant
Research Area:
Remote sensing of soil moisture and vegetation dynamics

Develop high resolution vegetation datasets from Sentinel-1 and ASCAT backscatter observations

Wiedner Hauptstr. 8 / E120-01-1 (DC02P18)
Phone #:
+43 (1) 58801 12260


My interest in Earth Observation and the effect of climate change on Earth’s ecosystems developed during my B.Sc. and M.Sc. in Earth Sciences at the VU University Amsterdam, The Netherlands. This motivated me to pursue a PhD in remote sensing which I started in 2012 at the Department for Geodesy and Geoinformation, TU Wien with Prof. Wolfgang Wagner and as part of the Doctoral Programme on Water Resource Systems with Prof. Günter Blöschl. During my PhD I focused on assessing vegetation dynamics from spaceborne active microwave backscatter observations. Since obtaining my PhD in 2016 I have been working as a researcher at TU Wien in the field of microwave remote sensing.

My area of expertise is the development of retrieval algorithms for vegetation and soil moisture from active microwave observations, in particular from the Advanced SCATterometer on-board of EUMETSAT Metop satellites and from the Synthetic Aperture Radars on-board of the Copernicus Sentinel-1 satellites. In addition, I work on the validation of Earth Observation datasets with in situ data collected from networks and field campaigns.

Currently I work on my ESA Living Planet Fellowship project SHRED: Sentinel-1 for High REsolution monitoring of vegetation Dynamics. The objective of SHRED is to develop and use a novel high-resolution vegetation optical depth dataset based on ESA’s Sentinel-1 satellites to improve our understanding on the local impacts of water availability on vegetation at a global scale using novel machine learning approaches.
For more information on SHRED, please check: https://eo4society.esa.int/lpf/mariette-vreugdenhil/


Vreugdenhil, Mariette, Wolfgang Wagner, Bernhard Bauer-Marschallinger, Isabella Pfeil, Irene Teubner, Christoph Rüdiger, and Peter Strauss (2018). Sensitivity of Sentinel-1 Backscatter to Vegetation Dynamics: An Austrian Case Study. Remote Sensing 10, no. 9: 1396. https://doi.org/10.3390/rs10091396.

Vreugdenhil, M., S. Hahn, T. Melzer, B. Bauer-Marschallinger, C. Reimer, W. A. Dorigo, and W. Wagner (2017). Assessing Vegetation Dynamics Over Mainland Australia With Metop ASCAT. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10, no. 5: 2240–48. https://doi.org/10.1109/JSTARS.2016.2618838.

Vreugdenhil, M., W. A. Dorigo, W. Wagner, R. A. M. de Jeu, S. Hahn, and M. J. E. van Marle (2016). Analyzing the Vegetation Parameterization in the TU-Wien ASCAT Soil Moisture Retrieval. IEEE Transactions on Geoscience and Remote Sensing 54, no. 6: 3513–31. https://doi.org/10.1109/TGRS.2016.2519842.

Vreugdenhil, Mariette, Richard AM de Jeu, and Jeffrey P. Walker (2013). Identification of Clay Pans from AMSR-E Passive Microwave Observations. International Journal of Remote Sensing 34, no. 14: 5201–5212.

Pfeil, Isabella, Mariette Vreugdenhil, Sebastian Hahn, Wolfgang Wagner, Peter Strauss, and Günter Blöschl (2018). Improving the Seasonal Representation of ASCAT Soil Moisture and Vegetation Dynamics in a Temperate Climate. Remote Sensing 10, no. 11 : 1788. https://doi.org/10.3390/rs10111788.

Greifeneder, F., C. Notarnicola, S. Hahn, M. Vreugdenhil, C. Reimer, E. Santi, S. Paloscia, and W. Wagner (2018). The Added Value of the VH/VV Polarization-Ratio for Global Soil Moisture Estimations From Scatterometer Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11, no. 10: 3668-79.

Teubner, I. E., M. Forkel, M. Jung, Y.Y. Liu, D.G. Miralles, R. Parinussa, R. van der Schalie, M. Vreugdenhil, C. Schwalm, G. Tramontana, G. Camps-Vals and W. Dorigo (2018). Assessing the Relationship between Microwave Vegetation Optical Depth and Gross Primary Production. International Journal of Applied Earth Observation and Geoinformation, 65: 7991.

Hahn, S., C. Reimer, M. Vreugdenhil, T. Melzer and W. Wagner (2017). Dynamic Characterization of the Incidence Angle Dependency of Backscatter Using Metop ASCAT. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 99 : 112.

Colliander, A., T. J. Jackson, Rajat Bindlish, S. Chan, N. Das, S. B. Kim, M. H. Cosh,...,M. Vreugdenhil, et al (2017). Validation of SMAP Surface Soil Moisture Products with Core Validation Sites. Remote Sensing of Environment, 191: 215231.

Kasse, C., R. T. Van Balen, S. J. P. Bohncke, J. Wallinga, and M. Vreugdenhil (2017). Climate and Base-Level Controlled Fluvial System Change and Incision during the Last Glacial–Interglacial Transition, Roer River, the Netherlands – Western Germany. Netherlands Journal of Geosciences 96, no. 2: 71–92. https://doi.org/10.1017/njg.2016.50.

Blöschl, G., A. P. Blaschke, M. Broer, C. Bucher, G. Carr, X. Chen, A. Eder, M. Exner-Kittridge, A. Farnleitner, A. Flores-Orozco, P. Haas, p. Hogan, A. Kazemi-Amiri, M. Oismüller, J. Parajka, R. Silasari, P. Stadler, P. Strauss, M. Vreugdenhil, W. Wagner and M. Zessner (2016). The Hydrological Open Air Laboratory (HOAL) in Petzenkirchen: A Hypotheses Driven Observatory. Hydrology & Earth System Sciences, 20: 227-255.

Franz, T.E., A. Wahbi, M. Vreugdenhil, G. Weltin, L. Heng, M. Oismueller, P. Strauss, G. Dercon, D. Desilets (2016). Using Cosmic-Ray Neutron Probes to Monitor Landscape Scale Soil Water Content in Mixed Land Use Agricultural Systems. Applied and Environmental Soil Science

Dorigo, W. A. Xaver, M. Vreugdenhil, A. Gruber, A. Hegiyova, A Sanchis-Dufau, D. Zamojski, C. Cordes, W. Wagner and M. Drusch (2013). Global automated quality control of in situ soil moisture data from the International Soil Moisture Network. Vadose Zone Journal 12(3): -.


Type Title Semester Hours
VO Microwave Remote Sensing 2019W 2.0
VO Introduction to Earth Observation 2019W 1.0
VO Data Retrieval in Earth Observation 2020S 1.0
UE Data Retrieval in Earth Observation 2020S 1.0
SE Seminar of Geosciences (Photogrammetry and Remote Sensing) 2019W 2.0