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Distributed scatterer interferometry (DS-InSAR) is an important time-series technique of surface deformation monitoring. The accuracy of the results highly depends on the density of DS, which is mainly influenced by synthetic aperture radar (SAR) image resolution and land cover. In this work, firstly, we use split spectrum technique to enable construction of SAR images with different bandwidth (i.e. different resolution). With the land-cover map as classification basis and mean coherence as DS selection index, we quantitatively analyse the behaviour of DS pixel density on different resolution SAR images and three land-cover types. We find that the DS density increases linearly with the increase of SAR system bandwidth, but the linear coefficient decreases with the increase of mean coherence. Secondly, we extend the coherence framework proposed by Zebker in 1992 to establish a model of relationship between mean coherence and bandwidth. The DS density by three land cover and different bandwidth SAR images was predicted by this model. When the mean coherence threshold is set to 0.4, the prediction model can agree with empirical results within 50% difference, and rather closer on impervious surface.

The Effect of SAR resolution and land-cover type on the distributed scatterer density in times-series of InSAR data