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Article

Efficient Ground Surface Displacement Monitoring Using Sentinel-1 Data: Integrating Distributed Scatterers (DS) Identified Using Two-Sample t-Test with Persistent Scatterers (PS)

1
Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, 7491 Trondheim, Norway
2
Department of Geodesy, Section of Remote Sensing, GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany
3
Institute for Photogrammetry and GeoInformation, Leibniz University Hannover, 30167 Hannover, Germany
4
Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET), School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(5), 794; https://doi.org/10.3390/rs10050794
Received: 8 April 2018 / Revised: 15 May 2018 / Accepted: 17 May 2018 / Published: 19 May 2018
(This article belongs to the Special Issue Imaging Geodesy and Infrastructure Monitoring)
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. View Full-Text
Keywords: distributed scatterer; persistent scatterer; Sentinel-1; StaMPS/MTI; SqueeSAR; t-test distributed scatterer; persistent scatterer; Sentinel-1; StaMPS/MTI; SqueeSAR; t-test
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MDPI and ACS Style

Shamshiri, R.; Nahavandchi, H.; Motagh, M.; Hooper, A. Efficient Ground Surface Displacement Monitoring Using Sentinel-1 Data: Integrating Distributed Scatterers (DS) Identified Using Two-Sample t-Test with Persistent Scatterers (PS). Remote Sens. 2018, 10, 794. https://doi.org/10.3390/rs10050794

AMA Style

Shamshiri R, Nahavandchi H, Motagh M, Hooper A. Efficient Ground Surface Displacement Monitoring Using Sentinel-1 Data: Integrating Distributed Scatterers (DS) Identified Using Two-Sample t-Test with Persistent Scatterers (PS). Remote Sensing. 2018; 10(5):794. https://doi.org/10.3390/rs10050794

Chicago/Turabian Style

Shamshiri, Roghayeh, Hossein Nahavandchi, Mahdi Motagh, and Andy Hooper. 2018. "Efficient Ground Surface Displacement Monitoring Using Sentinel-1 Data: Integrating Distributed Scatterers (DS) Identified Using Two-Sample t-Test with Persistent Scatterers (PS)" Remote Sensing 10, no. 5: 794. https://doi.org/10.3390/rs10050794

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