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Artykuły w czasopismach na temat „InSAR time series”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

Fattahi, Heresh, and Falk Amelung. "DEM Error Correction in InSAR Time Series." Geoscience and Remote Sensing, IEEE Transactions on 51, no. 7 (2013): 4249–59. http://dx.doi.org/10.1109/tgrs.2012.2227761.

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We present a mathematical formulation for the phase due to the errors in digital elevation models (DEMs) in synthetic aperture radar (SAR) interferometry (InSAR) time series obtained by the small baseline (SB) or the small baseline subset method. We show that the effect of the DEM error in the estimated displacement is proportional to the perpendicular baseline history of the set of SAR acquisitions. This effect at a given epoch is proportional to the perpendicular baseline between the SAR acquisition at that epoch and the reference acquisition. Therefore, the DEM error can significantly affec

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Xiaolei Lv, Birsen Yazici, Mourad Zeghal, Victoria Bennett, and Tarek Abdoun. "Joint-Scatterer Processing for Time-Series InSAR." IEEE Transactions on Geoscience and Remote Sensing 52, no. 11 (2014): 7205–21. http://dx.doi.org/10.1109/tgrs.2014.2309346.

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Agram, P. S., and M. Simons. "A noise model for InSAR time series." Journal of Geophysical Research: Solid Earth 120, no. 4 (2015): 2752–71. http://dx.doi.org/10.1002/2014jb011271.

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Zhou, Hao, Keren Dai, Xiaochuan Tang, et al. "Time-Series InSAR with Deep-Learning-Based Topography-Dependent Atmospheric Delay Correction for Potential Landslide Detection." Remote Sensing 15, no. 22 (2023): 5287. http://dx.doi.org/10.3390/rs15225287.

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Synthetic aperture radar interferometry (InSAR) has emerged as an effective technique for monitoring potentially unstable landslides and has found widespread application. Nevertheless, in mountainous reservoir regions, the precision of time-series InSAR outcomes is often constrained by topography-dependent atmospheric delay (TDAD) effects. To address this limitation, we propose a novel InSAR time-series method that integrates TDAD correction. This approach employs advanced deep learning algorithms to individually model and mitigate TDAD for each interferogram, thereby enhancing the accuracy of

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5

Barnhart, William D., and Rowena B. Lohman. "Characterizing and estimating noise in InSAR and InSAR time series with MODIS." Geochemistry, Geophysics, Geosystems 14, no. 10 (2013): 4121–32. http://dx.doi.org/10.1002/ggge.20258.

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Wirawan, Ade, and Noorlaila Hayati. "Pembuatan Platform Berbasis Cloud untuk Analisis Data Time Series Insar." Syntax Literate ; Jurnal Ilmiah Indonesia 9, no. 12 (2024): 7098–111. https://doi.org/10.36418/syntax-literate.v9i12.51693.

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Infrastruktur Data Spasial (IDS) adalah mekanisme terintegrasi untuk mempermudah pengguna data spasial dalam mengakses, mencari, berbagi pakai, hingga pemanfaatan data dan informasi spasial. Interferometric synthetic aperture radar (InSAR) adalah teknik pemetaan deformasi tanah menggunakan citra radar permukaan bumi yang dikumpulkan dari satelit yang mengorbit, dan telah menarik perhatian dalam beberapa tahun terakhir. Teknik InSAR multi-temporal (MT-InSAR), terutama persistent scatterer interferometry (PSI) dan small baseline method (SBAS) telah dikembangkan dengan menggunakan time series ana

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7

Li, Menghua, Hanfei Wu, Mengshi Yang, Cheng Huang, and Bo-Hui Tang. "Trend Classification of InSAR Displacement Time Series Using SAE–CNN." Remote Sensing 16, no. 1 (2023): 54. http://dx.doi.org/10.3390/rs16010054.

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Multi-temporal Interferometric Synthetic Aperture Radar technique (MTInSAR) has emerged as a valuable tool for measuring ground motion in a wide area. However, interpreting displacement time series and identifying dangerous signals from millions of InSAR coherent targets is challenging. In this study, we propose a method combining stacked autoencoder (SAE) and convolutional neural network (CNN) to classify InSAR time series and ease the interpretation of movements. The InSAR time series are classified into five categories, including stable, linear, accelerating, deceleration, and phase unwrapp

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8

He, Liming, Panke Pei, Xiangning Zhang, et al. "Sensitivity Evaluation of Time Series InSAR Monitoring Results for Landslide Detection." Remote Sensing 15, no. 15 (2023): 3906. http://dx.doi.org/10.3390/rs15153906.

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Spaceborne interferometric synthetic aperture radar (InSAR) techniques are important for landslide detection and monitoring; however, several limitations and uncertainties, such as the unique north–south flying direction and side-look radar observing geometry, currently limit the ability of InSAR to credibly detect landslides, especially those related to high and steep slopes. Here, we conducted experimental and statistical analysis on the feasibility of time-series InSAR monitoring for steep slopes using ascending and descending SAR images. First, the theoretical (TGNSS), practical (PGNSS), a

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9

Ferretti, Alessandro, Giuliano Savio, Riccardo Barzaghi, et al. "Submillimeter Accuracy of InSAR Time Series: Experimental Validation." IEEE Transactions on Geoscience and Remote Sensing 45, no. 5 (2007): 1142–53. http://dx.doi.org/10.1109/tgrs.2007.894440.

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10

Chang, Ling, and Ramon F. Hanssen. "A Probabilistic Approach for InSAR Time-Series Postprocessing." IEEE Transactions on Geoscience and Remote Sensing 54, no. 1 (2016): 421–30. http://dx.doi.org/10.1109/tgrs.2015.2459037.

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11

Ansari, Homa, Francesco De Zan, and Richard Bamler. "Sequential Estimator: Toward Efficient InSAR Time Series Analysis." IEEE Transactions on Geoscience and Remote Sensing 55, no. 10 (2017): 5637–52. http://dx.doi.org/10.1109/tgrs.2017.2711037.

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12

Yang, Mengshi, Saiwei Li, Hang Yu, Hao Wu, and Menghua Li. "Revealing Urban Deformation Patterns through InSAR Time Series Analysis with TCN and Transfer Learning." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1-2024 (May 11, 2024): 813–20. http://dx.doi.org/10.5194/isprs-archives-xlviii-1-2024-813-2024.

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Abstract. Current multi-epoch InSAR techniques heavily rely on the assumption of linear deformation. This can sometimes overlook crucial deformation signals when using velocities for evaluation. The process of interpreting InSAR time series is not only time-consuming and labor-intensive but also requires a certain level of expertise. This study refines existing InSAR deformation categories, such as stable, linear, step, piecewise linear, power, and undefined, to define 'canonical deformation time series patterns.' We propose an innovative approach for InSAR post-processing using Temporal Convo

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13

Yu, Dixiao. "Monitoring of Ground Deformation in Mining Region Based on Time-series InSAR." Theoretical and Natural Science 112, no. 1 (2025): 159–64. https://doi.org/10.54254/2753-8818/2025.au24071.

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Tailings ponds, essential for mining operations yet potential geological hazards, require rigorous safety monitoring. Conventional ground deformation methods are inadequate for contemporary precision and spatial coverage standards. InSAR technology, offering millimeter-level accuracy and robust spatio-temporal continuity, has become vital for monitoring deformation in mining areas. This study examines InSAR-based monitoring of ground deformation at the Baizhangzi Gold Mine's tailings pond and collapse zone in Lingyuan, Liaoning, China. Utilizing SBAS-InSAR, this study processes SAR image data

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14

Czikhardt, Richard, Hans van der Marel, and Juraj Papco. "GECORIS: An Open-Source Toolbox for Analyzing Time Series of Corner Reflectors in InSAR Geodesy." Remote Sensing 13, no. 5 (2021): 926. http://dx.doi.org/10.3390/rs13050926.

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Artificial radar reflectors, such as corner reflectors or transponders, are commonly used for radiometric and geometric Synthetic Aperture Radar (SAR) sensor calibration, SAR interferometry (InSAR) applications over areas with few natural coherent scatterers, and InSAR datum connection and geodetic integration. Despite the current abundance of regular SAR time series, no free and open-source software (FOSS) dedicated to analyzing SAR time series of artificial radar reflectors exists. In this paper, we present a FOSS Python toolbox for efficient and automatic estimation of: (i) the clutter leve

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15

Xiang, Wei, Rui Zhang, Guoxiang Liu, et al. "Saline-Soil Deformation Extraction Based on an Improved Time-Series InSAR Approach." ISPRS International Journal of Geo-Information 10, no. 3 (2021): 112. http://dx.doi.org/10.3390/ijgi10030112.

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Significant seasonal fluctuations could occur in the regional scattering characteristics and surface deformation of saline soil, and cause decorrelation, which limits the application of the conventional time-series InSAR (TS-InSAR). For extending the saline-soil deformation monitoring capability, this paper presents an improved TS-InSAR approach, based on the interferometric coherence statistics and high-coherence interferogram refinement. By constructing a network of the refined interferograms, high-accuracy ground deformation can be extracted through the weighted least square estimation and

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16

Li, Jiancun, Zhao Yan, Liqiang Tong, Yi Wang, and Shangyuan Yu. "Geological Hazard Risk Assessment Based on Time-Series InSAR Deformation: A Case Study of Xiaojin County, China." Applied Sciences 15, no. 8 (2025): 4143. https://doi.org/10.3390/app15084143.

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Geological hazard risk assessment provides essential scientific support for geological disaster prevention and governance. The selection of appropriate evaluation factors is crucial to the accuracy and practicality of the risk assessment results. The existing factors for geological hazard risk assessment often suffer from issues such as poor timeliness and insufficient completeness. Interferometric Synthetic Aperture Radar (InSAR) technology, which offers large-scale, high spatiotemporal resolution monitoring of surface deformation, can effectively compensate for the shortcomings of existing r

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17

Sun, N., and Y. J. Wang. "ANALYSIS OF LAND SUBSIDENCE MONITORING IN MINING AREA WITH TIME-SERIES INSAR TECHNOLOGY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1589–95. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1589-2018.

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Time-series InSAR technology has become a popular land subsidence monitoring method in recent years, because of its advantages such as high accuracy, wide area, low expenditure, intensive monitoring points and free from accessibility restrictions. In this paper, we applied two kinds of satellite data, ALOS PALSAR and RADARSAT-2, to get the subsidence monitoring results of the study area in two time periods by time-series InSAR technology. By analyzing the deformation range, rate and amount, the time-series analysis of land subsidence in mining area was realized. The results show that InSAR tec

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18

Yun, Hye Won, Yun Soo Choi, Ha Su Yoon, Jong Sik Ko, and Seong Kil Cho. "The Application of InSAR Signature Time Series for Landcover Classification." Journal of Korea Spatial Information Society 22, no. 1 (2014): 27–33. http://dx.doi.org/10.12672/ksis.2014.22.1.027.

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Liu, Zijing, Haijun Qiu, Yaru Zhu, et al. "Efficient Identification and Monitoring of Landslides by Time-Series InSAR Combining Single- and Multi-Look Phases." Remote Sensing 14, no. 4 (2022): 1026. http://dx.doi.org/10.3390/rs14041026.

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Identification and monitoring of unstable slopes across wide regions using Synthetic Aperture Radar Interferometry (InSAR) can further help to prevent and mitigate geological hazards. However, the low spatial density of measurement points (MPs) extracted using the traditional time-series InSAR method in topographically complex mountains and vegetation-covered slopes makes the final result unreliable. In this study, a method of time-series InSAR analysis using single- and multi-look phases were adopted to solve this problem, which exploited single- and multi-look phases to increase the number o

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20

He, Kuan, Youfeng Zou, Zhigang Han, and Jilei Huang. "Time-Series InSAR Technology for Monitoring and Analyzing Surface Deformations in Mining Areas Affected by Fault Disturbances." Remote Sensing 16, no. 24 (2024): 4811. https://doi.org/10.3390/rs16244811.

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Faults, as unique geological structures, disrupt the mechanical connections between rock masses. During coal mining, faults in the overlying strata can disturb the original stress balance, leading to fault activation and altering the typical subsidence patterns. This can result in abnormal ground deformation and significant damage to surface structures, posing a serious geological hazard in mining areas. This study examines the influence of a known fault (F13 fault) on ground subsidence in the Wannian Mine of the Fengfeng Mining Area. We utilized 12 Sentinel-1A images and applied SBAS-InSAR, S

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21

HO TONG MINH, Dinh, Ramon Hanssen, and Fabio Rocca. "Radar Interferometry: 20 Years of Development in Time Series Techniques and Future Perspectives." Remote Sensing 12, no. 9 (2020): 1364. http://dx.doi.org/10.3390/rs12091364.

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The research and improvement of methods to be used for deformation measurements from space is a challenge. From the previous 20 years, time series Synthetic Aperture Radar (SAR) interferometry techniques have proved for their ability to provide millimeter-scale deformation measurements over time. This paper aims to provide a review of such techniques developed in the last twenty years. We first recall the background of interferometric SAR (InSAR). We then provide an overview of the InSAR time series methods developed in the literature, describing their principles and advancements. Finally, we

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22

Liu, Peng, Qingquan Li, Zhenhong Li, et al. "Anatomy of Subsidence in Tianjin from Time Series InSAR." Remote Sensing 8, no. 3 (2016): 266. http://dx.doi.org/10.3390/rs8030266.

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Perissin, Daniele, and Teng Wang. "Time-Series InSAR Applications Over Urban Areas in China." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 4, no. 1 (2011): 92–100. http://dx.doi.org/10.1109/jstars.2010.2046883.

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Hetland, E. A., P. Musé, M. Simons, Y. N. Lin, P. S. Agram, and C. J. DiCaprio. "Multiscale InSAR Time Series (MInTS) analysis of surface deformation." Journal of Geophysical Research: Solid Earth 117, B2 (2012): n/a. http://dx.doi.org/10.1029/2011jb008731.

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Shanker, A. Piyush, and Howard Zebker. "Edgelist phase unwrapping algorithm for time series InSAR analysis." Journal of the Optical Society of America A 27, no. 3 (2010): 605. http://dx.doi.org/10.1364/josaa.27.000605.

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Osmanoğlu, Batuhan, Filiz Sunar, Shimon Wdowinski, and Enrique Cabral-Cano. "Time series analysis of InSAR data: Methods and trends." ISPRS Journal of Photogrammetry and Remote Sensing 115 (May 2016): 90–102. http://dx.doi.org/10.1016/j.isprsjprs.2015.10.003.

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Neely, Wesley R., Adrian A. Borsa, and Francesca Silverii. "GInSAR: A cGPS Correction for Enhanced InSAR Time Series." IEEE Transactions on Geoscience and Remote Sensing 58, no. 1 (2020): 136–46. http://dx.doi.org/10.1109/tgrs.2019.2934118.

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Wang, Guanya, Zhiwei Li, Han Gao, et al. "Adaptive sequential estimator for InSAR time series phase estimation." International Journal of Applied Earth Observation and Geoinformation 139 (May 2025): 104552. https://doi.org/10.1016/j.jag.2025.104552.

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Zhu, Shasha, Xiaoqing Zuo, Ke Shi, Yongfa Li, Shipeng Guo, and Chen Li. "Surface Subsidence Monitoring in Kunming City with Time-Series InSAR and GNSS." Applied Sciences 12, no. 24 (2022): 12752. http://dx.doi.org/10.3390/app122412752.

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Kunming city is located in the middle of Yunnan Province. Due to large-scale groundwater exploitation and urban development in recent years, this area has been affected by surface subsidence. In this paper, Interferometric Synthetic Aperture Radar (InSAR) and Global Navigation Satellite System (GNSS) data are used to monitor the surface subsidence in Kunming city area for better analysis and understanding. The study used data of Sentinel-1A from 2018 to 2020 with atmospheric correction based on GACOS to calculate the average annual subsidence rate in Kunming city area, and the results show tha

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Fattah, Erlangga Ibrahim, Asep Saepuloh, and Andri Dian Nugraha. "Observing Near-Real-Time Volcanoes Deformation Using InSAR – Time Series of LiCSBAS in Indonesia." IOP Conference Series: Earth and Environmental Science 1227, no. 1 (2023): 012026. http://dx.doi.org/10.1088/1755-1315/1227/1/012026.

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Abstract The Synthetic Aperture Radar (SAR) sensors onboard satellites are leading in advance to monitor physical changes of volcano edifices such as deformation. A few days of temporal resolution imageries provided by Sentinel-1 SAR make it possible to monitor volcanoes worldwide in near-real-time monitoring. The Sentinel-1 constellation produces a large amount of SAR images valuable for monitoring volcano deformation and hazard mitigation. However, processing the Interferometric SAR (InSAR) for a large SAR dataset is time-consuming and requires high-performance computers. Overcoming the prob

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Yu, Zhigang, Guanghui Zhang, Guoman Huang, Chunquan Cheng, Zhuopu Zhang, and Chenxi Zhang. "SSBAS-InSAR: A Spatially Constrained Small Baseline Subset InSAR Technique for Refined Time-Series Deformation Monitoring." Remote Sensing 16, no. 18 (2024): 3515. http://dx.doi.org/10.3390/rs16183515.

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SBAS-InSAR technology is effective in obtaining surface deformation information and is widely used in monitoring landslides and mining subsidence. However, SBAS-InSAR technology is susceptible to various errors, including atmospheric, orbital, and phase unwrapping errors. These multiple errors pose significant challenges to precise deformation monitoring over large areas. This paper examines the spatial characteristics of these errors and introduces a spatially constrained SBAS-InSAR method, termed SSBAS-InSAR, which enhances the accuracy of wide-area surface deformation monitoring. The method

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Qu, T., Q. Xu, W. Shan, Z. Li, M. Shan, and K. Dai. "DEFORMATION MONITORING OF HIGH-LATITUDE PERMAFROST REGION OF NORTHEASTERN CHINA WITH TIME SERIES INSAR TECHNIQUE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 1777–80. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-1777-2019.

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<p><strong>Abstract.</strong> Permafrost distributed in northeast China is the only high-altitude permafrost in China. The deformation monitoring over this permafrost region is of great importance to local climate change and ecological environments. This study focuses on the deformation monitoring of high-latitude permafrost in northeast China with time series InSAR technique. The spatial distribution characteristics, the annual deformation rates and the temporal deformation evolutions of permafrost could be retrieved from multi-temporal InSAR processing with Sentinel-1 TOPS

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Hussain, Ekbal, Alessandro Novellino, Colm Jordan, and Luke Bateson. "Offline-Online Change Detection for Sentinel-1 InSAR Time Series." Remote Sensing 13, no. 9 (2021): 1656. http://dx.doi.org/10.3390/rs13091656.

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Traditional applications of Interferometric Synthetic Aperture Radar (InSAR) data involved inverting an interferogram stack to determine the average displacement velocity. While this approach has useful applications in continuously deforming regions, much information is lost by simply fitting a line through the time series. Thanks to regular acquisitions across most of the the world by the ESA Sentinel-1 satellite constellation, we are now in a position to explore opportunities for near-real time deformation monitoring. In this paper we present a statistical approach for detecting offsets and

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Yun, Hye-Won, Jung-Rack Kim, Yun-Soo Choi, and Shih-Yuan Lin. "Analyses of Time Series InSAR Signatures for Land Cover Classification: Case Studies over Dense Forestry Areas with L-Band SAR Images." Sensors 19, no. 12 (2019): 2830. http://dx.doi.org/10.3390/s19122830.

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As demonstrated in prior studies, InSAR holds great potential for land cover classification, especially considering its wide coverage and transparency to climatic conditions. In addition to features such as backscattering coefficient and phase coherence, the temporal migration in InSAR signatures provides information that is capable of discriminating types of land cover in target area. The exploitation of InSAR signatures was expected to provide merits to trace land cover change in extensive areas; however, the extraction of suitable features from InSAR signatures was a challenging task. Combi

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Thapa, S., R. S. Chatterjee, K. B. Singh, and D. Kumar. "LAND SUBSIDENCE MONITORING USING PS-InSAR TECHNIQUE FOR L-BAND SAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (October 14, 2016): 995–97. http://dx.doi.org/10.5194/isprs-archives-xli-b7-995-2016.

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Differential SAR-Interferometry (D-InSAR) is one of the potential source to measure land surface motion induced due to underground coal mining. However, this technique has many limitation such as atmospheric in homogeneities, spatial de-correlation, and temporal decorrelation. Persistent Scatterer Interferometry synthetic aperture radar (PS-InSAR) belongs to a family of time series InSAR technique, which utilizes the properties of some of the stable natural and anthropogenic targets which remain coherent over long time period. In this study PS-InSAR technique has been used to monitor land subs

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Liu, Yuzhou, Wenxi Cao, Zhongqi Shi, et al. "Evaluation of Post-Tunneling Aging Buildings Using the InSAR Nonuniform Settlement Index." Remote Sensing 15, no. 14 (2023): 3467. http://dx.doi.org/10.3390/rs15143467.

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Tunneling work, including the construction of municipal tunnels and metro lines, may disturb the structural health of aging buildings in densely built urban areas. Deformation monitoring and risk assessments of aging buildings are crucial to mitigate incidents and prevent losses of people’s lives and properties. Time-series InSAR reveals spatio-temporal information about observed targets by extracting persistent scatterers of the structures, which can achieve the wide-range monitoring of buildings and infrastructure. However, solely relying on InSAR-derived general parameters (deformation rate

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Zheng, Yueze, Junhuan Peng, Chuyu Li, et al. "Long-Term SAR Data Analysis for Subsidence Monitoring and Correlation Study at Beijing Capital Airport." Remote Sensing 16, no. 3 (2024): 445. http://dx.doi.org/10.3390/rs16030445.

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Land subsidence, resulting from natural or human activities, is a global environmental geological disaster. The Interferometric Synthetic Aperture Radar (InSAR) time-series analysis technique offers high spatial and continuous temporal resolution, providing data and a foundation for investigating regional land subsidence and its evolution mechanism. Beijing Capital International Airport (BCIA) has experienced uneven land subsidence since 1935, together with severe fissures significantly affecting its normal operations. In this study, the time-series InSAR method was successfully applied to mon

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Çomut, F. C., A. Ustun, M. Lazecky, and M. M. Aref. "MULTI BAND INSAR ANALYSIS OF SUBSIDENCE DEVELOPMENT BASED ON THE LONG PERIOD TIME SERIES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1-W5 (December 10, 2015): 115–21. http://dx.doi.org/10.5194/isprsarchives-xl-1-w5-115-2015.

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The SAR Interferometry (InSAR) application has shown great potential in monitoring of land terrain changes and in detection of land deformations such as subsidence. Longer time analysis can lead to understand longer trends and changes. Using different bands of SAR satellite (C- from ERS 1-2 and Envisat, L- from ALOS) over the study area, we achieve knowledge of movements in long-term and evaluation of its dynamic changes within observed period of time. Results from InSAR processing fit with the position changes in vertical direction based on GPS network established over the basin as an effecti

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Mirmazloumi, S. M., Á. F. Gambin, Y. Wassie, et al. "INSAR DEFORMATION TIME SERIES CLASSIFICATION USING A CONVOLUTIONAL NEURAL NETWORK." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (May 30, 2022): 307–12. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-307-2022.

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Abstract. Temporal analysis of deformations Time Series (TS) provides detailed information of various natural and humanmade displacements. Interferometric Synthetic Aperture Radar (InSAR) generates millimetre-scale products, indicating the chronicle behaviour of detected targets via TS products. Deep Learning (DL) can handle a massive load of InSAR TS to categorize significant movements from non-moving targets. To this end, we employed a supervised Convolutional Neural Network (CNN) model to distinguish five deformations trends, including Stable, Linear, Quadratic, Bilinear, and Phase Unwrappi

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He, Yuanrong, Zhiheng Qian, Bingning Chen, Weijie Yang, and Panlin Hao. "Surface Deformation of Xiamen, China Measured by Time-Series InSAR." Sensors 24, no. 16 (2024): 5329. http://dx.doi.org/10.3390/s24165329.

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Due to its unique geographical location and rapid urbanization, Xiamen is particularly susceptible to geological disasters. This study employs 80 Sentinel-1A SAR images covering Xiamen spanning from May 2017 to December 2023 for comprehensive dynamic monitoring of the land subsidence. PS-InSAR and SBAS-InSAR techniques were utilized to derive the surface deformation field and time series separately, followed by a comparative analysis of their results. SBAS-InSAR was finally chosen in this study for its higher coherence. Based on its results, we conducted cause analysis and obtained the followi

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Ji, Panfeng, Xiaolei Lv, and Rui Wang. "Deriving 3-D Surface Deformation Time Series with Strain Model and Kalman Filter from GNSS and InSAR Data." Remote Sensing 14, no. 12 (2022): 2816. http://dx.doi.org/10.3390/rs14122816.

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This study proposes a new set of processing procedures based on the strain model and the Kalman filter (SM-Kalman) to obtain high-precision three-dimensional surface deformation time series from interferometric synthetic aperture radar (InSAR) and global navigation satellite system (GNSS) data. Implementing the Kalman filter requires the establishment of state and observation equations. In the time domain, the state equation is generated by fitting the pre-existing deformation time series based on a deformation model containing linear and seasonal terms. In the space domain, the observation eq

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Abdikan, S., S. Coskun, O. G. Narin, et al. "PREDICTION OF LONG-TERM SENTINEL-1 INSAR TIME SERIES ANALYSIS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-M-1-2023 (April 21, 2023): 3–8. http://dx.doi.org/10.5194/isprs-archives-xlviii-m-1-2023-3-2023.

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Abstract. This paper presents an initial analysis of predicting time series derived from long-term interferometric Synthetic Aperture Radar (InSAR) data. Time series analysis provides insights into the temporal evolution, variation, and dynamic nature of events. In this study, we focus on the Istanbul region, which is the most populous city in Turkey and spans both Europe and Asia. While the area is prone to seismic risks caused by active tectonic faults, it is also susceptible to other risks due to various phenomena. Therefore, this study investigates landslides triggered by geological struct

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Rygus, Michelle, Alessandro Novellino, Ekbal Hussain, Fifik Syafiudin, Heri Andreas, and Claudia Meisina. "A Clustering Approach for the Analysis of InSAR Time Series: Application to the Bandung Basin (Indonesia)." Remote Sensing 15, no. 15 (2023): 3776. http://dx.doi.org/10.3390/rs15153776.

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Interferometric Synthetic Aperture (InSAR) time series measurements are widely used to monitor a variety of processes including subsidence, landslides, and volcanic activity. However, interpreting large InSAR datasets can be difficult due to the volume of data generated, requiring sophisticated signal-processing techniques to extract meaningful information. We propose a novel framework for interpreting the large number of ground displacement measurements derived from InSAR time series techniques using a three-step process: (1) dimensionality reduction of the displacement time series from an In

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Zhao, Fumeng, Wenping Gong, Tianhe Ren, Jun Chen, Huiming Tang, and Tianzheng Li. "Permafrost Stability Mapping on the Tibetan Plateau by Integrating Time-Series InSAR and the Random Forest Method." Remote Sensing 15, no. 9 (2023): 2294. http://dx.doi.org/10.3390/rs15092294.

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The ground deformation rate is an important index for evaluating the stability and degradation of permafrost. Due to limited accessibility, in-situ measurement of the ground deformation of permafrost areas on the Tibetan Plateau is a challenge. Thus, the technique of time-series interferometric synthetic aperture radar (InSAR) is often adopted for measuring the ground deformation rate of the permafrost area, the effectiveness of which is, however, degraded in areas with geometric distortions in synthetic aperture radar (SAR) images. In this study, a method that integrates InSAR and the random

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Duan, Wei, Hong Zhang, and Chao Wang. "Deformation Estimation for Time Series InSAR Using Simulated Annealing Algorithm." Sensors 19, no. 1 (2018): 115. http://dx.doi.org/10.3390/s19010115.

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Time series interferometric synthetic aperture radar SAR (TSInSAR) is one of the most important surface deformation monitoring techniques, and has been widely used in geodesy. Deformation estimation is one of the main steps of TSInSAR processing, so an effective and efficient algorithm is necessary. Present algorithms have some limitations such as computing c osts or errors caused by local extremums. In this work, a novel deformation estimation method based on the simulated annealing (SA) algorithm is proposed to handle this problem. The SA algorithm uses a random search to avoid local extremu

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Piter, A., M. Vassileva, M. Haghshenas Haghighi, and M. Motagh. "EXPLORING CLOUD-BASED PLATFORMS FOR RAPID INSAR TIME SERIES ANALYSIS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (June 28, 2021): 171–76. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-171-2021.

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Abstract. The idea of near real-time deformation analysis using Synthetic Aperture Radar (SAR) data as a response to natural and anthropogenic disasters has been an interesting topic in the last years. A major limiting factor for this purpose has been the non-availability of both spatially and temporally homogeneous SAR datasets. This has now been resolved thanks to the SAR data provided by the Sentinel-1A/B missions, freely available at a global scale via the Copernicus program of the European Space Agency (ESA). Efficient InSAR analysis in the era of Sentinel demands working with cloud-based

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Wu, Zhouhang, Wenjun Zhang, Jialun Cai, Hongyao Xiang, Jing Fan, and Xiaomeng Wang. "The Deformation Monitoring Capability of Fucheng-1 Time-Series InSAR." Sensors 24, no. 23 (2024): 7604. http://dx.doi.org/10.3390/s24237604.

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The Fucheng-1 (FC-1) satellite has successfully transitioned from its initial operational phase and is now undergoing a detailed performance assessment for time-series deformation monitoring. This study evaluates the surface deformation monitoring capabilities of the newly launched FC-1 satellite using the interferometric synthetic aperture radar (InSAR) technique, particularly in urban applications. By analyzing the observation data from 20 FC-1 scenes and 20 Sentinel-1 scenes, deformation velocity maps of a university in Mianyang city were obtained using persistent scatterer interferometry (

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Aobpaet, Anuphao, Miguel Caro Cuenca, Andrew Hooper, and Itthi Trisirisatayawong. "InSAR time-series analysis of land subsidence in Bangkok, Thailand." International Journal of Remote Sensing 34, no. 8 (2013): 2969–82. http://dx.doi.org/10.1080/01431161.2012.756596.

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ZHANG, Yadi, Yudong LI, Jie DONG, et al. "Landslide hazard detection in Markam with time-series InSAR analyses." National Remote Sensing Bulletin 23, no. 5 (2019): 987–96. http://dx.doi.org/10.11834/jrs.20198025.

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赵, 艳丽. "Research on InSAR Technology Monitoring of Ground Subsidence Time Series." Geomatics Science and Technology 12, no. 02 (2024): 109–15. http://dx.doi.org/10.12677/gst.2024.122014.

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