Talks and Poster Presentations (without Proceedings-Entry):

E. Haas, U Gangkofner, J. Militzer, W. Wagner, W. Dorigo, A. Gruber:
"Near-Real Time Operational Processing of Soil Moisture Indicators for Africa";
Talk: Big Data from Space, Frascati; 2013-06-05 - 2013-06-07.

English abstract:
Near-real time information about the Start of the wet Season and dryness events are of importance especially in semi-arid and sub-humid regions, where vegetation growth is significantly driven by soil moisture availability. Decadal (10 day)Soil Water Index data (SWI) values show the course of soil moisture through the years, reflecting the onset, duration, strength and number of the rainy period(s). Early Warning systems require that such information is available in near-real time, and the development, production and dissemination of the soil moisture indicators for Africa in the frame of ESA´s Global Monitoring for Food Security (GMFS) project was designed accordingly.
The SWI data are derived from surface soil moisture data (SSM), which are retrieved from the radar backscattering coefficients measured by the ERS (from 1993 until 2006) and ASCAT (Advanced scatterometer onboard the MetOp satellite, since 2007) using a change detection method, developed at the Vienna University of Technology. In the frame of the GMFS project an operational processing chain was set up that allows processing the SWI data to Start of Season and dryness information in nearreal time. Key elements in the processing chain are automated notifications when new data is available and the timely
availability of large data amounts. The resulting soil moisture indicators are then distributed every 10 days to various users in Africa.
The currently processed time series starts in 1993 and is based on active microwave sensors. In the frame of ESA´s Climate Change Initiative the most complete and most consistent global soil moisture data record based on active and passive microwave sensors is produced. The inclusion of 30 years of 10 daily soil moisture data in this operational processing chain is thus the next step.

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