Talks and Poster Presentations (with Proceedings-Entry):

S. Elefante, S. Hahn, B. Bauer-Marschallinger, S. Hochstöger, W. Wagner:
"Soil Moisture Downscaling Meets Big Data Processing";
Poster: EUMETSAT Meteorological Satellite Conference 2017, Rome, Italy; 2017-10-02 - 2017-10-06; in: "Proceedings for the 2017 EUMETSAT Meteorological Satellite Conference", (2017).

English abstract:
In the framework of the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management soil moisture products are provided based on the Advanced Scatterometer with a spatial sampling of 25 km and 12.5 km. The data can be resampled to 1 km using a downscaling methodology which is based on the concept of soil moisture temporal stability. The downscaling technique uses the backscatter measurements from the Advanced Synthetic Aperture Radar on-board Sentinel-1 to compute linear and time-invariant downscaling parameters. However, the estimation of the downscaling parameters is a computationally extremely expensive task and they need to be calculated on a high performance computing platform such as the Vienna Scientific Cluster that is accessible through the Earth Observation Data Center infrastructure. The paper presents the Technische Universität Wien downscaling algorithm, followed by a first test investigating the suitability of Sentinel-1 data for the generation of new downscaling parameters.

Created from the Publication Database of the Vienna University of Technology.