Relevant bibliographies by topics / InSAR time series

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'InSAR time series'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "InSAR time series"

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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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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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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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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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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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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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Dissertations / Theses on the topic "InSAR time series"

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Shirzaei, Manoochehr. "Crustal deformation source monitoring using advanced InSAR time series and time dependent inverse modeling." Phd thesis, Universität Potsdam, 2010. http://opus.kobv.de/ubp/volltexte/2011/5077/.

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Crustal deformation can be the result of volcanic and tectonic activity such as fault dislocation and magma intrusion. The crustal deformation may precede and/or succeed the earthquake occurrence and eruption. Mitigating the associated hazard, continuous monitoring of the crustal deformation accordingly has become an important task for geo-observatories and fast response systems. Due to highly non-linear behavior of the crustal deformation fields in time and space, which are not always measurable using conventional geodetic methods (e.g., Leveling), innovative techniques of monitoring and anal
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Yang, Ziyi. "Monitoring and predicting railway subsidence using InSAR and time series prediction techniques." Thesis, University of Birmingham, 2015. http://etheses.bham.ac.uk//id/eprint/6377/.

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Improvements in railway capabilities have resulted in heavier axle loads and higher speed operations, which increase the dynamic loads on the track. As a result, railway subsidence has become a threat to good railway performance and safe railway operation. The author of this thesis provides an approach for railway performance assessment through the monitoring and prediction of railway subsidence. The InSAR technique, which is able to monitor railway subsidence over a large area and long time period, was selected for railway subsidence monitoring. Future trends of railway subsidence should also
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Bui, Luyen Khac. "Small baseline subset InSAR data processing: design of interferogram networks and noise analysis in InSAR-derived deformation time series." Thesis, Curtin University, 2021. http://hdl.handle.net/20.500.11937/83668.

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This dissertation assesses the influence of residual interferometric noise on SBAS InSAR, utilises redundancy numbers to design a SBAS network and analyses the noise in the SBAS-derived deformation time-series. The simulation results indicated that a contradictory trend may be derived if a network with fewer interferograms is applied to low-magnitude deformation and a network with redundancy number between ~0.8 and ~0.9 is “optimal”. A white plus flicker model best describes the noise model of deformation time-series.
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Osmanoglu, Batuhan. "Applications and Development of New Algorithms for Displacement Analysis Using InSAR Time Series." Scholarly Repository, 2011. http://scholarlyrepository.miami.edu/oa_dissertations/622.

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Time series analysis of Synthetic Aperture Radar Interferometry (InSAR) data has become an important scientific tool for monitoring and measuring the displacement of Earth’s surface due to a wide range of phenomena, including earthquakes, volcanoes,landslides, changes in ground water levels, and wetlands. Time series analysis is a product of interferometric phase measurements, which become ambiguous when the observed motion is larger than half of the radar wavelength. Thus, phase observations must first be unwrapped in order to obtain physically meaningful results. Persistent Scatterer Interfe
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Riddick, Susan Nancy 1987. "A Time Series Analysis of Volcanic Deformation near Three Sisters, Oregon, using InSAR." Thesis, University of Oregon, 2011. http://hdl.handle.net/1794/11479.

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x, 57 p. : ill. (mostly col.)<br>An extensive area west of the Three Sisters volcanoes of Oregon has been actively uplifting for over a decade. Examining the deformation is imperative to improve understanding of the potential hazards of Cascade volcanism and the emplacement of magma. I refine the timing of the onset of the deformation, resolve the change in uplift rates through time, and quantify the current deformation rate using Interferometric Synthetic Aperture Radar. The deformation is assessed in time and space using single interferogram InSAR, stacks of interferograms, and line-of-sight
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Zhou, Zhiwei. "The applications of InSAR time series analysis for monitoring long-term surface change in peatlands." Thesis, University of Glasgow, 2013. http://theses.gla.ac.uk/4875/.

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In the past three decades, peatlands all over the world such as upland bogs, tropical fens, have been undergoing significant and rapid degradations. These degradations cause carbon loss and CO2 emissions, and also fuel climate change. In this research, I present three case studies on how space geodetic tools, especially Radar Interferometry (InSAR), can be used to monitor and to advance our understanding of the long-term surface changes in peatlands. First, I investigate the eroding extent and severity of upland UK peatlands using InSAR. Both short wavelength C-band and long wavelength L-band
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Bouraoui, Seyfallah. "Time series analysis of SAR images using persistent scatterer (PS), small baseline (SB) and merged approaches in regions with small surface deformation." Phd thesis, Université de Strasbourg, 2013. http://tel.archives-ouvertes.fr/tel-01019429.

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This thesis aims at the study of small to large surface deformation that can be detected using the remote sensing interferometric synthetic aperture radar (InSAR) methods. The new developments of InSAR processing techniques allow the monitoring of surface deformation with millimeter surface change accuracy. Conventional InSAR use a pair of SAR images ("Master" and "Slave" images) in order to measure the phase difference between the two images taken at different times. The uncertainties in measurements using the conventional InSAR due to the atmospheric delay, the topographic changes and the or
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Cetin, Esra. "Analysis and modeling of crustal deformation using InSAR time series along selected active faults within the Africa-Eurasia convergence zone." Thesis, Strasbourg, 2015. http://www.theses.fr/2015STRAH010/document.

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Les travaux de cette thèse de Doctorat ont été menés dans le cadre de l'accord en co-tutelle entre l'Université de Strasbourg (EOST) et Istanbul Technical University (Dept. of Geology), avec l'octroi d'une bourse d'étude annuelle de !'Ambassade de France à Ankara, une bourse d'excellence EIFFEL de 10 mois, et un support financier de 8 mois de« TUBITAK 22148 - joint Ph.D. ». La zone de convergence de plaques Afrique - Eurasie comporte des failles capables de générer de forts séismes destructeurs. L'objectif de cette thèse est une meilleure compréhension du comportement de ces failles, et du cyc
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Tamer, Ibrahim Mahmoud Mosaad ElGharbawi. "Geodetic accuracy observations of regional land deformations caused by the 2011 Tohoku Earthquake using SAR interferometry and GEONET data." 京都大学 (Kyoto University), 2015. http://hdl.handle.net/2433/202686.

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Heimlich, Christine. "Méthodes géodésiques appliquées à la géothermie et mesures de déformations locales dans le Fossé rhénan supérieur." Thesis, Strasbourg, 2016. http://www.theses.fr/2016STRAH011/document.

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Le Fossé rhénan bénéficie de circulations naturelles d’eau géothermale, ce qui le rend propice à l’exploitation géothermique. Comment et où les fluides géothermaux circulent-ils ? Quels liens ont-ils avec la tectonique et la sismicité induite ? La géodésie spatiale pourrait-elle apporter de nouveaux éclairages à ces questionnements ? L’objectif de cette thèse est la réalisation d’un suivi géodésique des sites géothermiques de Soultz-sous-Forêts et de Rittershoffen (Alsace, France). Les observations permettent de faire un état des lieux des déplacements de surface des environs des sites pendant
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Books on the topic "InSAR time series"

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Moulds, Maxwell, James Tuttle, and David Lane. Hawkmoths of Australia. CSIRO Publishing, 2020. http://dx.doi.org/10.1071/9781486302826.

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Hawkmoths are large charismatic insects with highly variable and colourful larvae. Some species are specialised in their habitat preferences, but others are widespread and often encountered in gardens. However, little is known about most species, and associating the adults with their larvae has previously been difficult or impossible.&#x0D; Hawkmoths of Australia allows identification of all of the Australian hawkmoths for the first time and treats species found on mainland Australia, Tasmania and all offshore islands within Australian limits. It presents previously undescribed life histories
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Book chapters on the topic "InSAR time series"

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Gou, Jisong, Xianlin Shi, Keren Dai, Leyin Hu, and Peilian Ran. "Revealing Land Subsidence in Beijing by Sentinel-1 Time Series InSAR." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2568-1_85.

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Liu, Hao, and Qin Yuan. "Research on urban land subsidence based on time series SBAS-InSAR." In Advances in Geology and Resources Exploration. CRC Press, 2022. http://dx.doi.org/10.1201/9781003308584-112.

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Huntley, David, Drew Rotheram-Clarke, Roger MacLeod, Robert Cocking, Jamel Joseph, and Philip LeSueur. "Landslide Monitoring with RADARSAT Constellation Mission InSAR, RPAS-Derived Point-Clouds and RTK-GNSS Time-Series in the Thompson River Valley, British Columbia, Canada." In Progress in Landslide Research and Technology, Volume 2 Issue 1, 2023. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-39012-8_19.

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AbstractIn this paper, we evaluate the effectiveness of four land-deformation measurement techniques for monitoring slow-moving landslides along a high-risk section of the national railway corridor traversing the Thompson River valley, British Columbia, Canada. The geomorphically active North Slide acts as an ideal field laboratory for testing and evaluating novel monitoring techniques and methods. We compare differential processing of Structure from Motion (SfM) products such as point-cloud elevation models and orthophotos derived from Remotely Piloted Aircraft Systems (RPAS), along with sate
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Qian, Dongsheng, Hongxiang Wang, Xuewen Huang, et al. "Potential Geohazards Identification and Deformation Monitoring by Time-Series InSAR Along Anhui Ningwu Expressway." In Environmental Science and Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-9061-0_36.

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Iannacone, Jean Pascal, Alessandro Corsini, Matteo Berti, Jessica Morgan, and Giacomo Falorni. "Characterization of Longwall Mining Induced Subsidence by Means of Automated Analysis of InSAR Time-Series." In Engineering Geology for Society and Territory - Volume 5. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09048-1_187.

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Tang, Yang, Like Huang, Songmei Lv, et al. "Prediction of landslide deformation trend of a substation access road based on time-series InSAR." In Constructional Engineering and Ecological Environment. CRC Press, 2023. http://dx.doi.org/10.1201/9781003410843-38.

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Ghaderpour, Ebrahim, Claudia Masciulli, Marta Zocchi, et al. "Least-Squares Wavelet Analysis of Rainfalls and Landslide Displacement Time Series Derived by PS-InSAR." In Contributions to Statistics. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-40209-8_9.

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Liu, Xianlin, Tao Yin, Youdong Chen, Yu Shao, and Keren Dai. "Identifying the Potential Landslides Along Duba Highway (Guangxi, China) in Dense Vegetation Environment by Time Series InSAR." In Environmental Science and Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-9061-0_32.

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Montisci, Augusto, and Maria Cristina Porcu. "Self-organizing-Map Analysis of InSAR Time Series for the Early Warning of Structural Safety in Urban Areas." In Computational Science and Its Applications – ICCSA 2020. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58820-5_62.

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Poggi, Francesco, Roberto Montalti, Emanuele Intrieri, Alessandro Ferretti, Filippo Catani, and Federico Raspini. "Spatial and Temporal Characterization of Landslide Deformation Pattern with Sentinel-1." In Progress in Landslide Research and Technology, Volume 2 Issue 1, 2023. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-39012-8_15.

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AbstractThe results of multi-interferometric processing applied to radar images acquired by the European Space Agency (ESA) Sentinel-1 constellation, obtained in the framework of the IPL (International Programme on Landslides) project n.221, are presented in this manuscript. The target area is the Hunza-Nagar River valley, a remote area in northern Pakistan. The Humarri slide, a massive landslide located along the left side of the valley, is the most active phenomenon in the area, and poses a very high risk to the Humarri village built in the lowest part of the landslide, and a threat of dammi
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Conference papers on the topic "InSAR time series"

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Aobpaet, Anuphao, Intira Thanomsin, Chanikan Yodya, and Suchanpong Obnam. "Advancing Airport Land Subsidence Monitoring Through Time-Series InSAR Technology." In 11th International Conference on Geographical Information Systems Theory, Applications and Management. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013359500003935.

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Hourston, Holly, Itahisa González Álvarez, Luke Bateson, Ekbal Hussain, and Alessandro Novellino. "Automated Insar Time-Series Analysis Tool for Geological Interpretations in Near-Real Time." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10641304.

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Wig, Elizabeth, Roger Michaelides, and Howard Zebker. "Measuring Changes in Vegetation Moisture from Insar Closure Phase Time Series." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10641076.

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Huang, Hengwei, Alex Hay-Man Ng, Hua Wang, Zheyuan Du, and Linlin Ge. "An Approch for Enhancing Time-Series InSAR with Multi-Polarization Data." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10640862.

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Manders, Ted, and Joana E. Martins. "Identification of Potential Sinkhole Signatures: Employing Time Series Clustering for Anomaly Detection in InSAR Time Series Over Limburgs Mining District." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10642578.

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Li, Guangrong, Chaoying Zhao, and Ming Yan. "Dynamic Estimation of Surface Height Changes and Deformation Time Series with Multitemporal InSAR." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10640449.

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Chen, Lei, Ye Tian, Jianyu Wang, Siao Liu, Ning Wang, and Ningning Zhang. "Evaluation of geological hazard risk in Xiaojin County with time series InSAR deformation." In 2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP). IEEE, 2024. https://doi.org/10.1109/icsidp62679.2024.10868987.

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Chen, Rongsheng, and Juntao Zhu. "Spatiotemporal evolution analysis of land subsidence in Nanjing based on time-series InSAR." In 2024 International Conference on Remote Sensing and Digital Earth, edited by Jie Cheng, Kegen Yu, and Mahmoud Reza Delavar. SPIE, 2025. https://doi.org/10.1117/12.3059005.

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Shastri, Arpan, K. M. Sreejith, and Chandrakanta Ojha. "Assessing Land Deformation in Trivandrum City, Southwest India, Using Time Series InSAR Analysis." In 2024 IEEE India Geoscience and Remote Sensing Symposium (InGARSS). IEEE, 2024. https://doi.org/10.1109/ingarss61818.2024.10984404.

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Xu, Leilei, Jingxian Sun, Cheng Zhang, et al. "Application of Time-Series InSAR for Foundation Stability Monitoring of Power Transmission Equipment." In 2025 4th International Conference on Green Energy and Power Systems (ICGEPS). IEEE, 2025. https://doi.org/10.1109/icgeps65133.2025.11034478.

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Reports on the topic "InSAR time series"

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Samsonov, S. V., A. Trishchenko, K. F. Tiampo, P. J. González, J. Fernández, and Y. Zhang. Seasonal tropospheric oscillations observed in InSAR time series. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2015. http://dx.doi.org/10.4095/296137.

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Deschamps, Henschel, and Robert. PR-420-123712-R01 Lateral Ground Movement Detection Capabilities Derived from Synthetic Aperture Radar. Pipeline Research Council International, Inc. (PRCI), 2014. http://dx.doi.org/10.55274/r0010831.

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The objective of this research was to quantify long-term ground deformation at the Belridge Oil Field, in the San Joaquin Valley (SJV), California using operational Interferometric Synthetic Aperture Radar (InSAR) monitoring techniques. A high spatial and temporal resolution, millimeter-precision time-series of ground deformation measurements was produced for the entire oil field from 2000 to 2012 using imagery from multiple satellites and beam modes. Trihedral Corner Reflectors (CRs) with co-located Global Navigation Satellite System (GNSS) units were used to validate the wide-area measuremen
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Huntley, D., D. Rotheram-Clarke, R. Cocking, J. Joseph, and P. Bobrowsky. Current research on slow-moving landslides in the Thompson River valley, British Columbia (IMOU 5170 annual report). Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/331175.

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Interdepartmental Memorandum of Understanding (IMOU) 5170 between Natural Resources Canada (NRCAN), the Geological Survey of Canada (GSC) and Transport Canada Innovation Centre (TC-IC) aims to gain new insight into slow-moving landslides, and the influence of climate change, through testing conventional and emerging monitoring technologies. IMOU 5107 focuses on strategically important sections of the national railway network in the Thompson River valley, British Columbia (BC), and the Assiniboine River valley along the borders of Manitoba (MN) and Saskatchewan (SK). Results of this research ar
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