Abstract

The launch of the European Space Agency's (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite in November 2009 opened a new era in monitoring globally and continuously these two environmental parameters. The importance of these measurements to provide information on Earth's climate and its changes has been pointed out by the scientific community in recent years [1]. With SMOS data weather prediction models can be improved and extreme weather phenomena better understood. The SMOS payload radiometer called MIRAS (Microwave Imaging Radiometer using Aperture Synthesis) uses aperture synthesis technique, new to remote sensing, to form an image of the target [2]. The used technique is very effective in producing good quality data with reasonable ground resolution for passive L-band measurements. However, since it is based on having numerous individual receivers, from which the output signals are correlated, the technique is sensitive to artificial or man-made interfering signal sources. It is of great importance to identify the existing sources of RFI (Radio Frequency Interference) to ensure good quality data. This paper describes the work done in Aalto University in this field using available SMOS data and the Aalto University L-band aperture synthesis radiometer (HUT-2D) airborne data collected during the SMOS rehearsal campaigns and other national funded campaigns.

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