Welcome to the GEO Department of TU Wien
Geodesy and Geoinformation take on key roles in our modern society as provider of information about geographical locations, environmental processes, physical fundamentals and are pivotal in enabling access to social relevant spatial data. Since its early days in the 19th century, the Vienna University of Technology hosts scientists and engineers undertaking geospatial data research. Today, a multitude of research fields in the evolving domain of geodesy and geoinformation is in the scope of our academic institution. The Department of Geodesy and Geoinformation, which is part of the Faculty of Mathematics and Geoinformation, unites the seven research groups Advanced Geodesy, Cartography, Engineering Geodesy, Geoinformation, Geophysics, Photogrammetry and Remote Sensing and conducts research as well as teaching in modelling and communicating states and processes of planet Earth and objects in, upon and above it.
hidden, but needed
hidden, but needed
- GEO contribute to European State of the Climate 2017 with C3S Long-term soil moisture
- Copernicus nutzbar machen II: Workshop-Präsentationen sind online
- DriDanube - Let's talk about drought!
- African VLBI Network School 2018
- Congratulations, Dr. Milenkovic!
- S Schaphoff, M. Forkel, C. Müller, J. Knauer, W. von Bloh, D. Gerten, J. Jägermeyr, W. Lucht, A. Rammig, K. Thonicke, K. Waha:
LPJmL4 - a dynamic global vegetation model with managed land - Part 2: Model evaluation
Geoscientific Model Development, 11 (2018), 4; 1377 - 1403. [ More information ]
- S Schaphoff, W. von Bloh, A. Rammig, K. Thonicke, H. Biemans, M. Forkel, D. Gerten, J. Heinke, J. Jägermeyr, J. Knauer, F. Langerwisch, W. Lucht, C. Müller, S. Rolinski, K. Waha:
LPJmL4 - a dynamic global vegetation model with managed land - Part 1: Model description
Geoscientific Model Development, 11 (2018), 4; 1343 - 1375. [ More information ]
- M. Bechtold, S. Schlaffer, B. Tiemeyer, G. De Lannoy:
Inferring Water Table Depth Dynamics from ENVISAT-ASAR C-Band Backscatter over a Range of Peatlands from Deeply-Drained to Natural Conditions
Remote Sensing, 10 (2018), 4; 536-1 - 536-21.
- I. Ali, S. Cao, V. Freeman, C. Paulik, W. Wagner:
Methods to Remove the Border Noise From Sentinel-1 Synthetic Aperture Radar Data: Implications and Importance For Time-Series Analysis
IEEE Journal Of Selected Topics In Applied Earth Observations And Remote Sensing, 11 (2018), 3; 777 - 786. [ More information ]
- A. Gruber, W. Crow, W. Dorigo:
Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain
Water Resources Research, 54 (2018), 2; 1353 - 1367. [ More information ]