CHANGE DETECTION WITH SYNTHETIC APERTURE RADAR

The purpose of the study was to explore the information available in a multi-temporal Synthetic Aperture Radar (SAR) data set covering a full seasonal cycle, and to identify issues that must be considered in conducting further research in this area. The data set was compiled from images obtained using the C-band SAR of the Canada Centre for Remote Sensing over a test flight line near Ottawa. All SAR images were geometrically corrected, registered to a UTM projection and resampled to 6.25 m pixels. A fall Landsat Thematic Mapper image was also resampled and co-registered with the SAR images. A procedure was developed to display differences between SAR images taken at successive dates. Both individual and difference SAR images were analysed with reference to ground and hydrometeorological data acquired from various sources. Results of the analysis indicate that SAR images obtained over the annual cycle contain information on the dynamic behaviour of various land surface cover types. Variations were most pervasive in the case of vegetation and secondly in the case of surface water, including vegetation-water interactions. The results also highlighted the requirement of precise geometrical registration, calibrated (relatively or better) SAR and accurate hydrometeorological data (including within site variability) within the site to detect and analyse changes in SAR images.