Data Processing, Feature Extraction, and Time-Series Analysis of Sentinel-1 Synthetic Aperture Radar (SAR) Imagery: Examples from Damghan and Bajestan Playa (Iran)

2019 ◽  
Vol 62 (1) ◽  
pp. 9-39 ◽  
Author(s):  
Tobias Ullmann ◽  
Konstantin Serfas ◽  
Christian Büdel ◽  
Majid Padashi ◽  
Roland Baumhauer
Keyword(s):  
Time Series ◽  
Feature Extraction ◽  
Time Series Analysis ◽  
Data Processing ◽  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Series Analysis ◽  
Sar Imagery ◽  
Aperture Radar

scholarly journals Long-range ground deformation monitoring by InSAR analysis

2015 ◽  
Vol 372 ◽  
pp. 343-346 ◽  
Author(s):  
S. Rokugawa ◽  
T. Nakamura
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Synthetic Aperture Radar ◽  
Surface Deformation ◽  
Ground Deformation ◽  
Synthetic Aperture ◽  
Alos Palsar ◽  
Envisat Asar ◽  
Series Analysis ◽  
Kanto District

Abstract. InSAR (Interferometric Synthetic Aperture Radar) analysis is an effective technique to map 3-dimensional surface deformation with high spatial resolution. The aim of this study was to evaluate the capability of InSAR analysis when applied to ground monitoring of an environmental disaster. We performed a time series InSAR analysis using ENVISAT/ASAR and ALOS/PALSAR data and commercial software to investigate subsidence around the Kanto District of Japan. We also investigated techniques for efficient early detection of landslides in Kyushu using time series analysis that incorporated synthetic aperture radar (SAR) images. ENVISAT/ASAR data acquired from 2003–2010 and ALOS/PALSAR data acquired from 2006–2011 were used to detect poorly expressed geomorphological deformation by conducting time series analyses of periodically acquired SAR data. In addition, to remove noise caused by geographical feature stripes or phase retardation, we applied median filtering, histogram extraction processing, and clarification of the displacement with a Laplacian filter. The main functions of the InSAR time series analysis are the calculation of phase differences between two images and the inversion with smoothness constraint for the estimation of deformation along the line of sight. The results enabled us to establish criteria for the selection of suitable InSAR data pairs, and provided the final error estimation of the derived surface deformation. The results of the analysis in the Kanto District suggested that localized areas of uplift and subsidence have occurred at irregular intervals in this area. Furthermore, the method offers the possibility of early warning of environmental disasters such as landslide and abrupt subsidence. Our results confirm the effectiveness of InSAR analysis for the monitoring of ground deformation over wide areas via the detection of localized subsidence and landslides.

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