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Combining persistent scatterers (PS) and distributed scatterers (DS) is important for effective displacement monitoring using time-series of SAR data. However, for large stacks of synthetic aperture radar (SAR) data, the DS analysis using existing algorithms becomes a time-consuming process. Moreover, the whole procedure of DS selection should be repeated as soon as a new SAR acquisition is made, which is challenging considering the short repeat-observation of missions such as Sentinel-1. SqueeSAR is an approach for extracting signals from DS, which first applies a spatiotemporal filter on images and optimizes DS, then incorporates information from both optimized DS and PS points into interferometric SAR (InSAR) time-series analysis. In this study, we followed SqueeSAR and implemented a new approach for DS analysis using two-sample t-test to efficiently identify neighboring pixels with similar behaviour. We evaluated the performance of our approach on 50 Sentinel-1 images acquired over Trondheim in Norway between January 2015 and December 2016. A cross check on the number of the identified neighboring pixels using the Kolmogorov-Smirnov (KS) test, which is employed in the SqueeSAR approach, and the t-test shows that their results are strongly correlated. However, in comparison to KS-test, the t-test is less computationally intensive (98% faster). Moreover, the results obtained by applying the tests under different SAR stack sizes from 40 to 10 show that the t-test is less sensitive to the number of images.

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The regular acquisition and relatively short revisit 4 time of Sentinel-1 satellite improve the capability of a persistent 5 scatterer interferometric synthetic aperture radar (PS-InSAR) as 6 a suitable geodetic method of choice for measuring ground sur-7 face deformation in space and time. The SAR instrument aboard 8 the Sentinel-1 satellite supports operation in dual polarization 9 (HH-HV, VV-VH), which can be used to increase the spatial den-10 sity of measurement points through the polarimetric optimization 11 method. This study evaluates the improvement in displacement 12 mapping by incorporating the information obtained from the VH 13 channel of Sentinel-1 data into the PS-InSAR analysis. The method 14 that has shown great success with different polarimetric data per-15 forms a search over the available polarimetric space in order to 16 find a linear combination of polarization states, which yields the 17 optimum PS selection criterion using the amplitude dispersion in-18 dex (ADI) criterion. We applied the method to a dataset of 50 19 dual-polarized (VV-VH) Sentinel-1 images over Trondheim city 20 in Norway. The results show overall increase of about 186% and 21 78% in the number of PS points with respect to the conventional 22 channels of VH and VV, respectively. The study concludes that, 23 using the ADI optimization, we can incorporate information from 24 the VH channel into the PS-InSAR analysis, which otherwise is lost 25 due to its low amplitude.26

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We derive the mass balance of Greenland ice sheet from the Gravity Recovery and Climate Experiment (GRACE) for the period January 2003-October 2014. We have found an ice mass loss with peak amplitude of-15 cm/yr in the southeastern and northwestern parts, and an acceleration of-2.5 cm/yr 2 in the southwestern region. Global warming is a wellknown suspected triggering factor of ice melting. We use MODIS-derived Ice Surface Temperature (IST), and continuous and cross wavelet transforms have been determined to investigate the common power and relative phase between GRACE derived time-series of ice mass changes and IST time-series. Results indicate a high common power between the two time-series for the whole study period, but with different time patterns.

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