Abstract

ABSTRACTThis article presents the results of a study conducted to quantify the seasonal variation of coherence in synthetic aperture radar (SAR) interferograms in Kiruna, Northern Sweden. In SAR interferometry (InSAR), coherence is an important concept that provides a good indication of the phase stability of the scatterers. Therefore, in this study, the degree of coherence is used as a parameter to identify the seasonal variation interferograms. For this study, 34 Radarsat-2 ultra-fine beam mode (U6D) images of the Kiruna area (67°51ʹN, 20°14ʹE) and the improved digital elevation model (DEM) created by merging the Radarsat-2 DEM and ASTER DEM were used to produce 561 differential interferograms. The interferograms were arranged in three different ways for the analysis, with the first including common master interferograms (with the summer master image), the second including the sequential interferograms that have the shortest temporal baseline, and the third accounting for all possible combinations of the interferograms (full network of interferograms). Following this step, the variation of coherence for forest areas, urban areas, and flat waste rock areas was studied. This study shows that interferograms generated for the Kiruna region exhibit seasonal variations in coherence due to the ground snow layer in winter. Furthermore, when there is water on the ground due to the melting of the snow layer (in the spring) or due to rains in autumn, the coherence is reduced considerably. Another significant feature is that there is a significant change in summer-to-summer coherence for some regions even over the course of a few years. Based on this study, it is clear that the winter Radarsat-2 U6D beam mode images are not suitable for differential interferometric SAR (DInSAR) deformation measurements in flat waste rock regions in Kiruna. It is expected that even with winter images, PSInSAR or CTM techniques will be able to provide better deformation measurements, but, in this study, those techniques were not assessed. The next step will be to study the seasonal variations in coherence in natural or man-made targets/persistent scatterers using persistent scatter InSAR (PSInSAR) or coherence target monitoring (CTM) techniques.

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