COMPARISON AND EVALUATION OF DIFFERENT APPROACHES FOR EFFICIENT PROCESSING OF LONG GROUND-BASED SAR TIMES SERIES

Abstract. Ground-based Synthetic Aperture Radar (GB-SAR) is a monitoring tool which, once installed, acquires a large amount of data autonomously. For the IBIS-FM system, approximately 760 SAR images per day are acquired, which corresponds to more than 23 000 scenes per month. Therefore, this paper analysis different strategies for the interferometric processing of such large data stacks to find a compromise between accuracy, computational effort and the ability to (re-)process specific time intervals independently. This study compares the single master approach with the sequential approach and in addition two block-wise approaches. Moreover, a new baseline configuration called Daily Baseline Subset (DBAS) is compared which uses interferograms having a multiple of one day as temporal baseline. We evaluate them on a data stack of 30 000 images, acquired at Enguri Dam in Georgia. We check the unwrapping errors and the quality of the displacement estimation to compare the different configurations. We found that block-wise approaches show the best results considering unwrapping errors and Root Mean Square Error, while in our study the DBAS approach shows to the most plausible displacement map which is also dependent on the individual reduction of atmospheric noise.