The SHARE project team, Institute of Photogrammetry and Remote Sensing, Vienna University of Technology
www.ipf.tuwien.ac.at/radar/share
Contact: share@ipf.tuwien.ac.at

SHARE is one of the European Space Agency's DUE Tiger Innovator projects. It addresses one of today's most severe obstacles in water resource management, which is the lack of availability of reliable soil moisture information on a dynamic basis at a frequency of a week and less. An operational soil moisture monitoring service using a change detection approach has been set up for the region of the Southern African Development Community (SADC).

Data acquired by the Advanced Synthetic Aperture Radar (ASAR) sensor onboard the European ENVISAT satellite are used for the derivation of the soil moisture information. With the sensor operating in Global Mode (GM), employing the ScanSAR acquisition technique, a spatial resolution of 1 km and a temporal sampling sufficient for change detection is achieved. Within the first three years of data availability (2005 - 2007) more than 4300 ASAR GM scenes had to be processed for the SADC region. An automatic processing chain has been setup, which makes use of SARscapeŽ. SARscapeŽ functions have been used for import, geocoding and radiometric calibration. Based on a SRTM-GTOPO30-DEM and precise orbit information (DORIS orbit files), SARscapeŽ allows fast terrain-corrected geocoding without user interaction (e.g. selection of tie points) based on the Range-Doppler approach.

Efficient and fast data analysis and product generation require multi-temporal data sets. Therefore geocoded and calibrated ASAR GM scenes are resampled to a defined fixed discrete global grid. For each 0.5° times 0.5° region in the grid, a binary file containing the full time series of data was stored in a database (http://www.ipf.tuwien.ac.at/radar/share/publ/0032.pdf). Customized resampling, local incidence angle normalization, data base management, soil moisture product generation, validation and visualization procedures have been implemented using ENVI/IDL functions. Sample maps can be viewed as PNG and KML (for use with Google Earth) files on the project web page: http://www.ipf.tuwien.ac.at/radar/share/. Figure 1 shows a KML of monthly mean soil moisture for Angola from January 2005. Figure 2 shows a snapshot of the visualization and analysis tool implemented using IDL.

Figure 1: Sample for surface soil moisture dataset (1km, monthly composite) as KML for viewing with Google Earth

Figure 2. The Selectscape interface for analysis and visualization of satellite radar data and derived products, developed at the Vienna University of Technology. More than 4300 radar images, resulting in a 70 GB database, were processed for southern and central Africa.