Change detection techniques for ERS-1 SAR data

Several techniques for detecting temporal changes in satellite synthetic aperture radar ( S A R ) imagery are compared using both theoretical predictions and spaceborne S A R data collected by the European first Remote Sensing Satellite, ERS1. In a first set of techniques, changes are detected based on differences in the magnitude of the signal intensity between two dates. Ratioing of the multidate radar intensities is shown to be better adapted to the statistical characteristics of S A R data than subtracting, and works best when the number of looks is large. In a second set of techniques, changes are detected based on estimates of the temporal decorrelation of speckle. This method works best with one-look complex amplitude data, but can also be used with intensity data provided that the number of looks is small. The two techniques, ratioing of the signal intensity and decorrelation of speckle, are compared using actual S A R data collected by ERS-1. The results illustrate the viability as well as the complementary character of these techniques for detecting changes in the structural and dielectric properties of remotely sensed surfaces. Finally, change detection using the ratio method is applied to mosaics of repeat-pass S A R imagery to illustrate the potential of this method for monitoring applications at the regional scale.