• Title/Summary/Keyword: Time-series InSAR

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Analysis of time-series displacement using satellite SAR interferometry technique for Dam safety monitoring (댐 안전 관리를 위한 위성 SAR 간섭기법 활용 시계열 변위 분석)

  • Kang, Ki-mook;Hwang, EuiHo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.440-440
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    • 2022
  • 1970년대부터 집중 건설 된 우리나라의 다목적댐, 홍수조절댐, 용수전용댐 등의 대형 국가 수자원시설물들의 '고령화'가 급속히 진행되어 수리구조물에 대한 안정성을 주기적으로 파악할 수 있는 정밀안전모니터링 체계 구축이 시급한 시점이다. 주기적인 정밀안전모니터링 방법들 중에는 위성 등을 활용한 원격관측 기술들이 최근 시도되고 있다. 위성 영상레이더(SAR; Synthetic Aperture Radar)는 마이크로파 대역의 전자기파를 송·수신하는 능동센서로 날씨 및 주·야간에 영향을 받지 않고 지표면 관측이 가능한 장점이 있다. 특히, 고정산란체 영상레이더 간섭(PSInSAR; Permanent Scatterer Interferometry SAR)기법은 영상레이더 영상에서 긴밀도(coherence)가 상대적으로 높은 수자원시설물과 같은 고정산란체의 위상(phase) 정보를 이용하여 mm급의 측정민감도로 시계열 변위 분석이 가능하다. 또한, 여러 장의 InSAR 영상을 생성하였기 때문에 DEM 오차, 위성궤도 오차, 대기 성분에 의한 지연 오차 등을 보다 정밀하게 제거할 수 있는 장점이 있다 본 연구에서는 국내 중대형 수자원시설물의 정밀안전모니터링을 위하여 고정산란체 영상레이더 간섭 기법을 영암금호방조제, 영주댐, 소양강댐 등에 적용하여 시계열 변위 분석을 수행하였다. 2014년 11월부터 2022년 3월(현재)까지 획득된 Sentinel-1 SLC(Single Look Complex) 위성자료의 상승(Ascending) 궤도 126장 및 하강(Descending)궤도 187장을 각각 활용하였다. 두 위성궤도를 모두 활용하여 수직, 수평 변위 등 3차원 분석을 수행하였으며, 특히 소양강댐 GPS 관측 자료와 정확도 검증에서 연평균 2mm의 RMSE를 보였다. 이를 통해 위성 원격탐사 기술로도 댐, 보, 방조제와 같은 수자원시설물에 대한 시계열 변위 분석을 통한 댐 안전관리가 가능함을 보여주고 있다. 2025년 발사될 국내 C-밴드 SAR 탑재 수자원위성 개발을 통해 한반도 재방문주기를 단축시킴으로써, 한반도 전역의 수자원시설물 정밀안전진단체계 구축이 가능할 것으로 기대된다.

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Research of Water-related Disaster Monitoring Using Satellite Bigdata Based on Google Earth Engine Cloud Computing Platform (구글어스엔진 클라우드 컴퓨팅 플랫폼 기반 위성 빅데이터를 활용한 수재해 모니터링 연구)

  • Park, Jongsoo;Kang, Ki-mook
    • Korean Journal of Remote Sensing
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    • v.38 no.6_3
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    • pp.1761-1775
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    • 2022
  • Due to unpredictable climate change, the frequency of occurrence of water-related disasters and the scale of damage are also continuously increasing. In terms of disaster management, it is essential to identify the damaged area in a wide area and monitor for mid-term and long-term forecasting. In the field of water disasters, research on remote sensing technology using Synthetic Aperture Radar (SAR) satellite images for wide-area monitoring is being actively conducted. Time-series analysis for monitoring requires a complex preprocessing process that collects a large amount of images and considers the noisy radar characteristics, and for this, a considerable amount of time is required. With the recent development of cloud computing technology, many platforms capable of performing spatiotemporal analysis using satellite big data have been proposed. Google Earth Engine (GEE)is a representative platform that provides about 600 satellite data for free and enables semi real time space time analysis based on the analysis preparation data of satellite images. Therefore, in this study, immediate water disaster damage detection and mid to long term time series observation studies were conducted using GEE. Through the Otsu technique, which is mainly used for change detection, changes in river width and flood area due to river flooding were confirmed, centered on the torrential rains that occurred in 2020. In addition, in terms of disaster management, the change trend of the time series waterbody from 2018 to 2022 was confirmed. The short processing time through javascript based coding, and the strength of spatiotemporal analysis and result expression, are expected to enable use in the field of water disasters. In addition, it is expected that the field of application will be expanded through connection with various satellite bigdata in the future.

Analysis of Surface Displacement of Oil Sands Region in Alberta, Canada Using Sentinel-1 SAR Time Series Images (Sentinel-1 SAR 시계열 영상을 이용한 캐나다 앨버타 오일샌드 지역의 지표변위 분석)

  • Kim, Taewook;Han, Hyangsun
    • Korean Journal of Remote Sensing
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    • v.38 no.2
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    • pp.139-151
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    • 2022
  • SAGD (Steam-Assisted Gravity Drainage) method is widely used for oil recovery in oil sands regions. The SAGD operation causes surface displacement, which can affect the stability of oil recovery plants and trigger various geological disasters. Therefore, it isimportant to monitor the surface displacement due to SAGD in the oil sands region. In this study, the surface displacement due to SAGD operations of the Athabasca oil sands region in Alberta, Canada, was observed by applying Permanent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique to the Sentinel-1 time series SAR data acquired from 2016 to 2021. We also investigated the construction and expansion of SAGD facilitiesfrom Landsat-7/8 time seriesimages, from which the characteristics of the surface displacement according to the oil production activity of SAGD were analyzed. Uplift rates of 0.3-2.5 cm/yr in the direction of line of sight were observed over the SAGDs and their vicinity, whereas subsidence rates of -0.3--0.6 cm/yr were observed in areas more than several kilometers away from the SAGDs and not affected by oil recovery activities. Through the analysis of Landsat-7/8 images, we could confirm that the SAGDs operating after 2012 and showing high oil production activity caused uplift rates greater than 1.6 cm/yr due to the subsurface steam injection. Meanwhile, very small uplift rates of several mm per year occurred over SAGDs which have been operated for a longer period of time and show relatively low oil production activity. This was probably due to the compression of reservoir sandstone due to continuous oil recovery. The subsidence observed in areas except for the SAGDs and their vicinity estimated to be a gradual land subsidence caused by melting of the permafrost. Considering the subsidence, it was expected that the uplift due to SAGD operation would be greater than that observed by the PSInSAR. The results of this study confirm that the PSInSAR can be used as an effective means for evaluating productivity and stability of SAGD in the extreme cold regions.

Mapping Paddy Rice Varieties Using Multi-temporal RADARSAT SAR Images

  • Jang, Min-Won;Kim, Yi-Hyun;Park, No-Wook;Hong, Suk-Young
    • Korean Journal of Remote Sensing
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    • v.28 no.6
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    • pp.653-660
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    • 2012
  • This study classified paddy fields according to rice varieties and monitored temporal changes in rice growth using SAR backscatter coefficients (${\sigma}^{\circ}$). A growing period time-series of backscatter coefficients was set up for nine fine-beam mode RADARSAT-1 SAR images from April to October 2005. The images were compared with field-measured rice growth parameters such as leaf area index (LAI), plant height, fresh and dry biomass, and water content in grain and plants for 45 parcels in Dangjin-gun, Chungnam Province, South Korea. The average backscatter coefficients for early-maturing rice varieties (13 parcels) ranged from -18.17 dB to -6.06 dB and were lower than those for medium-late maturing rice varieties during most of the growing season. Both crops showed the highest backscatter coefficient values at the heading stage (late July) for early-maturing rice, and the difference was greatest before harvest for early-maturing rice. The temporal difference in backscatter coefficients between rice varieties may play a key role in identifying early-maturing rice fields. On the other hand, comparisons with field-measured parameters of rice growth showed that backscatter coefficients decreased or remained on a plateau after the heading stage, even though the growth of the rice canopy had advanced.

A Study on the Traffic Volume Correction and Prediction Using SARIMA Algorithm (SARIMA 알고리즘을 이용한 교통량 보정 및 예측)

  • Han, Dae-cheol;Lee, Dong Woo;Jung, Do-young
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.6
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    • pp.1-13
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    • 2021
  • In this study, a time series analysis technique was applied to calibrate and predict traffic data for various purposes, such as planning, design, maintenance, and research. Existing algorithms have limitations in application to data such as traffic data because they show strong periodicity and seasonality or irregular data. To overcome and supplement these limitations, we applied the SARIMA model, an analytical technique that combines the autocorrelation model, the Seasonal Auto Regressive(SAR), and the seasonal Moving Average(SMA). According to the analysis, traffic volume prediction using the SARIMA(4,1,3)(4,0,3) 12 model, which is the optimal parameter combination, showed excellent performance of 85% on average. In addition to traffic data, this study is considered to be of great value in that it can contribute significantly to traffic correction and forecast improvement in the event of missing traffic data, and is also applicable to a variety of time series data recently collected.

Comparison of Observation Performance of Urban Displacement Using ALOS-1 L-band PALSAR and COSMO-SkyMed X-band SAR Time Series Images (ALOS-1 L-band PALSAR와 COSMO-SkyMed X-band SAR 시계열 영상을 이용한 도심지 변위관측 성능 비교 분석)

  • Choi, Jung-Hyun;Kim, Sang-Wan
    • Korean Journal of Remote Sensing
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    • v.34 no.2_1
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    • pp.283-293
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    • 2018
  • We applied PSInSAR to two SAR satellite (ALOS-1 and COSMO-SkyMed) images and analyzed the difference in displacement observation performance according to sensor characteristics. The building layer was extracted from the digital topographic map, and the PS extracted from the SAR image was classified into two groups(building structure and ground surface) for density analysis. The density of PS extracted from the research area was $0.023point/m^2$ for ALOS-1 PALSAR and $0.1point/m^2$ for COSMO-SkyMed, more than 4 times PS was extracted compared to ALOS-1. In addition, not only the PS density in the building, but also the density in the ground were greatly increased. The average displacement velocity of ALOS-1 PALSAR is within ${\pm}1cm/yr$, while for COSMO-SkyMed it is within ${\pm}0.3cm/yr$. Although it is difficult to make quantitative comparisons because it does not use the data for the same period, it can be said that the accuracy of X-band SAR system is very high compared to the L-band. In consideration of PS observation density and observation accuracy of displacement, X-band SAR data is very effective in research where it is important to acquire useful signals from the ground surface, such as ground subsidence and sinkhole.

A Design Method for Pre-Distortion Compensation of SAR Chirp Signal based on Envelop Sampling and Interpolation Filter (위성 탑재 영상레이다 첩 신호의 전치왜곡 보상을 위한 포락선 샘플링 및 보간 필터 기반의 설계 기법)

  • Lee, Young-Bok
    • Journal of the Korea Institute of Military Science and Technology
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    • v.25 no.4
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    • pp.347-354
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    • 2022
  • The synthetic aperture radar(SAR) is an equipment that can acquire images in all weathers day and night based on radar signals. The on-board processor of satellite SAR generates transmission signal by digital signal processing, converts it into an analog signal and transmits to antenna. Until the transmission signal generated by on-board processor is output, the signal passes the transmission cables and analog devices. At this time, these hardware distort the signal and makes SAR performance worse. To improve the performance, pre-distortion technique is used. But, general pre-distortion using taylor series is not sufficient to compensate for the distortion. This paper suggests transmit signal design method with improved pre-distortion. This paper uses envelop sampling method and interpolation filter for frequency domain compensation. The proposed method accurately compensates the hardware distortion and reduces resource usage of FPGA. To analyze proposed method's performance, IRF characteristics are compared when the proposed method applies to signal with errors.

Measurement of Time-Series Surface Deformation at New Orleans Using Small Baseline Subset (SBAS) Method

  • Jo, Min-Jeong;Eom, Jin-Ah;Won, Joong-Sun
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.49-52
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    • 2008
  • New Orleans located in the estuary of the Mississippi River was attacked by Hurricane Katrina and suffered big flood on August 2005. Since unconsolidated Holocene to middle Miocene strata is the main basement rocks, land subsidence has been occurred steadily due to soil compaction and normal faulting. It was reported that the maximum subsidence rate from 2002 to 2005 was -29 mm/yr. Many studies in the area have been carried out for understanding the subsiding and potential risks caused by ground subsidence are weighted by the fact that a large area of the city is located below the mean sea level. A small baseline subset (SBAS) method is applied for effectively measuring time-series LOS (Line-of sight) surface deformation from differential synthetic aperture radar interferograms in this study. The time-series surface deformation at New Orleans was measured from RADARSAT-1 SAR images. The used dataset consists of twenty-one RADARSAT-1 fine beam mode images on descending orbits from February 2005 to February 2007 and another twenty-one RADARSAT-1 standard beam mode images on ascending orbits from January 2005 to February 2007. From this dataset, 25 and 38 differential interferograms on descending and ascending orbits were constructed, respectively. The vertical and horizontal components of surface deformation were extracted from ascending and descending LOS surface deformations. The result from vertical component of surface deformation indicates that subsidence is not significant with a mean rate of -3.1${\pm}$3.2 mm/yr.

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Improvement of Small Baseline Subset (SBAS) Algorithm for Measuring Time-series Surface Deformations from Differential SAR Interferograms (차분 간섭도로부터 지표변위의 시계열 관측을 위한 개선된 Small Baseline Subset (SBAS) 알고리즘)

  • Jung, Hyung-Sup;Lee, Chang-Wook;Park, Jung-Won;Kim, Ki-Dong;Won, Joong-Sun
    • Korean Journal of Remote Sensing
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    • v.24 no.2
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    • pp.165-177
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    • 2008
  • Small baseline subset (SBAS) algorithm has been recently developed using an appropriate combination of differential interferograms, which are characterized by a small baseline in order to minimize the spatial decorrelation. This algorithm uses the singular value decomposition (SVD) to measure the time-series surface deformation from the differential interferograms which are not temporally connected. And it mitigates the atmospheric effect in the time-series surface deformation by using spatially low-pass and temporally high-pass filter. Nevertheless, it is not easy to correct the phase unwrapping error of each interferogram and to mitigate the time-varying noise component of the surface deformation from this algorithm due to the assumption of the linear surface deformation in the beginning of the observation. In this paper, we present an improved SBAS technique to complement these problems. Our improved SBAS algorithm uses an iterative approach to minimize the phase unwrapping error of each differential interferogram. This algorithm also uses finite difference method to suppress the time-varying noise component of the surface deformation. We tested our improved SBAS algorithm and evaluated its performance using 26 images of ERS-1/2 data and 21 images of RADARSAT-1 fine beam (F5) data at each different locations. Maximum deformation amount of 40cm in the radar line of sight (LOS) was estimated from ERS-l/2 datasets during about 13 years, whereas 3 cm deformation was estimated from RADARSAT-1 ones during about two years.

A Study on Monitoring Surface Displacement Using SAR Data from Satellite to Aid Underground Construction in Urban Areas (위성 SAR 자료를 활용한 도심지 지하 교통 인프라 건설에 따른 지표 변위 모니터링 적용성 연구)

  • Woo-Seok Kim;Sung-Pil Hwang;Wan-Kyu Yoo;Norikazu Shimizu;Chang-Yong Kim
    • The Journal of Engineering Geology
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    • v.34 no.1
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    • pp.39-49
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    • 2024
  • The construction of underground infrastructure is garnering growing increasing research attention owing to population concentration and infrastructure overcrowding in urban areas. An important associated task is establishing a monitoring system to evaluate stability during infrastructure construction and operation, which relies on developing techniques for ground investigation that can evaluate ground stability, verify design validity, predict risk, facilitate safe operation management, and reduce construction costs. The method proposed here uses satellite imaging in a cost-effective and accurate ground investigation technique that can be applied over a wide area during the construction and operation of infrastructure. In this study, analysis was performed using Synthetic Aperture Radar (SAR) data with the time-series radar interferometric technique to observe surface displacement during the construction of urban underground roads. As a result, it was confirmed that continuous surface displacement was occurring at some locations. In the future, comparing and analyzing on-site measurement data with the points of interest would aid in confirming whether displacement occurs due to tunnel excavation and assist in estimating the extent of excavation impact zones.