scholarly journals Time Series Analysis with ALOS PALSAR images and GPS data: Detection of Ground Subsidence in the Mokpo Area using the SBAS Algorithm

Author(s):  
So-Yeon Kim ◽  
Tae-Suk Bae ◽  
Sang-Wan Kim
2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yu Morishita

AbstractGround subsidence in urban areas is a significant problem because it increases flood risk, damages buildings and infrastructure, and results in economic loss. Continual monitoring of ground deformation is important for early detection, mechanism understanding, countermeasure implementation, and deformation prediction. The Sentinel-1 satellite constellation has globally and freely provided frequent and abundant SAR data and enabled nationwide deformation monitoring through InSAR time series analysis. LiCSAR, an automatic Sentinel-1 interferometric processing system, has produced abundant interferograms with global coverage, and the products are freely accessible and downloadable through a web portal. LiCSBAS, an open source InSAR time series analysis package integrated with LiCSAR, enables users to obtain the deformation time series easily and quickly. In this study, spatially and temporally detailed deformation time series and velocities from the LiCSAR products using LiCSBAS for 73 major urban areas in Japan during 2014–2020 were derived. All LiCSBAS processing was automatically performed using predefined parameters. Many deformation signals with various temporal and spatial features, such as linear subsidence in Hirosaki, Kujyukuri, Niigata, and Kanazawa, episodic subsidence in Sanjo, annual vertical fluctuation in Hirosaki, Yamagata, Yonezawa, Ojiya, and Nogi, and linear uplift in Chofu were detected. Unknown small nonlinear uplift signals were found in Nara and Osaka in 2018. Complex postseismic deformations from the 2016 Kumamoto earthquake were also revealed. All the deformation data obtained in this study are available on an open repository and are expected to be used for further research, investigation, or interpretation. This nationwide monitoring approach using the LiCSAR products and LiCSBAS is easy to implement and applicable to other areas worldwide.


Author(s):  
S. Rokugawa ◽  
T. Nakamura

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.


2020 ◽  
Vol 12 (23) ◽  
pp. 3881
Author(s):  
Ryosuke Doke ◽  
George Kikugawa ◽  
Kazuhiro Itadera

The authors wish to make the following corrections to this paper [...]


2020 ◽  
Vol 12 (17) ◽  
pp. 2842 ◽  
Author(s):  
Ryosuke Doke ◽  
George Kikugawa ◽  
Kazuhiro Itadera

Monitoring of surface displacement by satellite-based interferometric synthetic aperture radar (InSAR) analysis is an effective method for detecting land subsidence in areas where routes of leveling measurements are undeveloped, such as mountainous areas. In particular, InSAR-based monitoring around well-developed hot spring resorts, such as those in Japan, is useful for conserving hot spring resources. Hakone Volcano is one of the major hot spring resorts in Japan, and many hot spring wells have been developed in the Owakudani fumarole area, where a small phreatic eruption occurred in 2015. In this study, we performed an InSAR time series analysis using the small baseline subset (SBAS) method and ALOS/PALSAR scenes of the Hakone Volcano to monitor surface displacements around the volcano. The results of the SBAS-InSAR time series analysis show highly localized subsidence to the west of Owakudani from 2006–2011 when the ALOS/PALSAR satellite was operated. The area of subsidence was approximately 500 m in diameter, and the peak rate of subsidence was approximately 25 mm/year. Modeling using a point pressure source suggested that the subsidence was caused by a contraction at approximately 700 m above sea level (about 300 m below the ground surface). The rate of this contraction was estimated to be 1.04 × 104 m3/year. Hot spring water is collected from a nearby well at almost the same depth as the contraction source, and its main dissolved ion component is chloride ions, suggesting that the hydrothermal fluids are supplied from deep within the volcano. The land subsidence suggests that the fumarole activity is attenuating due to a decrease in the supply of hydrothermal fluids from deeper areas.


2019 ◽  
Vol 11 (1) ◽  
pp. 738-749
Author(s):  
Jinchao Li ◽  
Fei Gao ◽  
Jiaguo Lu ◽  
Tingye Tao

Abstract Underground coal mining activities often cause ground subsidence and damage to surface construction, which seriously threatens the lives and property of residents in mining areas. In this paper, the deformation of the Yang Juzhuang village, which is a residential area in the Huainan mining area (China), was monitored through an interferometric synthetic aperture radar (InSAR) time series analysis. The vertical displacements were detected using thirteen Sentinel-1A images that were acquired between December 2016 and May 2017. The validity and applicability of the method are verified by comparing the acquired images with the GPS measurement results. Because of the deformation characteristics of the mining area, a prediction model that is combined with a grey support vector machine regression (GM-SVR) is proposed, and the practical effects of the model are verified using the deformation monitoring results of the study area. The combination of this model and SBAS-InSAR provides rapid dynamic monitoring and enables the issuance of disaster warnings in the region.


2017 ◽  
Author(s):  
Refi Rizqi Ramadian ◽  
Irwan Meilano ◽  
Endra Gunawan ◽  
Susilo ◽  
Joni Efendi

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