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.
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- StudienassistentIn Photogrammetrie
- SAR Data Processing Specialist
- PreDoc position in Engineering Geodesy
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- Hermannskogellauf 2018
- International Remote Sensing School for Hydrological Applications, Rome, 13-16 November 2018
- How much water is used for irrigation?
- 9th VieVS User-Workshop at TU Wien
- Farewell Gregor Möller
- L. Brocca, A. Tarpanelli, P. Filippucci, W. Dorigo, F. Zaussinger, A. Gruber, D. Prieto:
How much water is used for irrigation? A new approach exploiting satellite soil moisture observations
International Journal of Applied Earth Observation and Geoinformation, 73 (2018), 752 - 766.
- H. Huang, G. Gartner:
Current Trends and Challenges in Location-Based Services
ISPRS International Journal of Geo-Information, 7 (2018), 6. [ More information ]
- H. Liao, W. Dong, H. Huang, G. Gartner, H. Liu:
Inferring user tasks in pedestrian navigation from eye movement data in real-world environments
International Journal of Geographical Information Science, 32 (2018). [ More information ]
- S. Thaler, L. Brocca, L. Ciabatta, J. Eitzinger, S. Hahn, W. Wagner:
Effects of Different Spatial Precipitation Input Data on Crop Model Outputs under a Central European Climate
Atmosphere, 9 (2018), 8; 290-1 - 290-25.
- Y. Li, S. Williams, B. Moran, A. Kealy, G. Retscher:
High-Dimensional Probabilistic Fingerprinting in Wireless Sensor Networks Based on a Multivariate Gaussian Mixture Model
Sensors (invited), 18 (2018), 8; 24 pages. [ More information ]