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

Roghayeh Shamshiri,Hossein Nahavandchi,Mahdi Motagh,Andy Hooper

doi:10.3390/rs10050794

Abstract

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.

Highlights

Efficient space-based techniques are a key tool to assess changes and deformation related to natural hazards such as earthquakes [1,2,3,4], volcanoes [5,6], and landslides [7,8] and anthropogenic hazards such as subsidence/uplift due to fluid withdrawal/injection [9,10,11]
We applied our technique for a dataset composed of 50 SLC Sentinel-1 images acquired between January 2015 and December 2016 over Trondheim central Norway
The images were acquired in the interferometric wide swath (IW) mode, from an ascending track number 73, with a mean incidence angle of 33 degrees and “VV” polarization

Summary

Introduction

Efficient space-based techniques are a key tool to assess changes and deformation related to natural hazards such as earthquakes [1,2,3,4], volcanoes [5,6], and landslides [7,8] and anthropogenic hazards such as subsidence/uplift due to fluid withdrawal/injection [9,10,11]. Sentinel-1A/B images, with high temporal resolution (6–12 days) and moderate spatial resolution (5 m × 20 m), can provide ground deformation maps with enough density of PS points in urban areas [25,26]. The sampling density of measurements points in both urban and agricultural regions can be further increased either by incorporating information from polarimetric observations [28] or by integrating DS and PS pixels [29] in single-polarimetry time-series analysis. These lead to more effective filtering of the atmospheric signals affecting InSAR measurements, and result in more accurate phase unwrapping

Methods

Results

Discussion

Conclusion