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Anantrasirichai, N., Biggs, J., Albino, F., Bull, D. (2019) The Application of Convolutional Neural Networks to Detect Slow, Sustained Deformation in InSAR Time Series. Geophysical Research Letters, 46 (21) 11850-11858 doi:10.1029/2019gl084993

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Reference TypeJournal (article/letter/editorial)
TitleThe Application of Convolutional Neural Networks to Detect Slow, Sustained Deformation in InSAR Time Series
JournalGeophysical Research Letters
AuthorsAnantrasirichai, N.Author
Biggs, J.Author
Albino, F.Author
Bull, D.Author
Year2019 (November 16)Volume46
Issue21
PublisherAmerican Geophysical Union (AGU)
DOIdoi:10.1029/2019gl084993Search in ResearchGate
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Mindat Ref. ID860639Long-form Identifiermindat:1:5:860639:0
GUID0
Full ReferenceAnantrasirichai, N., Biggs, J., Albino, F., Bull, D. (2019) The Application of Convolutional Neural Networks to Detect Slow, Sustained Deformation in InSAR Time Series. Geophysical Research Letters, 46 (21) 11850-11858 doi:10.1029/2019gl084993
Plain TextAnantrasirichai, N., Biggs, J., Albino, F., Bull, D. (2019) The Application of Convolutional Neural Networks to Detect Slow, Sustained Deformation in InSAR Time Series. Geophysical Research Letters, 46 (21) 11850-11858 doi:10.1029/2019gl084993
In(2019, November) Geophysical Research Letters Vol. 46 (21) American Geophysical Union (AGU)

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Anantrasirichai, N., Biggs, J., Albino, F., Bull, D. (2019) A deep learning approach to detecting volcano deformation from satellite imagery using synthetic datasets. Remote Sensing of Environment, 230. 111179pp. doi:10.1016/j.rse.2019.04.032
Hill, P., Biggs, J., Ponce‐López, V., Bull, D. (2021) Time‐Series Prediction Approaches to Forecasting Deformation in Sentinel‐1 InSAR Data. Journal of Geophysical Research: Solid Earth, 126 (3) doi:10.1029/2020jb020176
Albino, F., Biggs, J., Yu, C., Li, Z. (2020) Automated Methods for Detecting Volcanic Deformation Using Sentinel‐1 InSAR Time Series Illustrated by the 2017–2018 Unrest at Agung, Indonesia. Journal of Geophysical Research: Solid Earth, 125 (2) doi:10.1029/2019jb017908
Anantrasirichai, Nantheera, Biggs, Juliet, Kelevitz, Krisztina, Sadeghi, Zahra, Wright, Tim, Thompson, James, Achim, Alin Marian, Bull, David (2021) Detecting Ground Deformation in the Built Environment Using Sparse Satellite InSAR Data With a Convolutional Neural Network. IEEE Transactions on Geoscience and Remote Sensing, 59 (4) 2940-2950 doi:10.1109/tgrs.2020.3018315
Popescu, Robert; Anantrasirichai, Nantheera; Biggs, Juliet (2025) Unsupervised Anomaly Detection for Volcanic Deformation in InSAR Imagery. Earth and Space Science, 12 (6). doi:10.1029/2024ea003892
Gonzålez, Pablo J., Fernåndez, José (2011) Error estimation in multitemporal InSAR deformation time series, with application to Lanzarote, Canary Islands. Journal of Geophysical Research, 116. doi:10.1029/2011jb008412
Yip, Stanley Tze Hou, Biggs, Juliet, Albino, Fabien (2019) Reevaluating Volcanic Deformation Using Atmospheric Corrections: Implications for the Magmatic System of Agung Volcano, Indonesia. Geophysical Research Letters, 46 (23) 13704-13711 doi:10.1029/2019gl085233
Gaddes, M. E., Hooper, A., Bagnardi, M., Inman, H., Albino, F. (2018) Blind Signal Separation Methods for InSAR: The Potential to Automatically Detect and Monitor Signals of Volcanic Deformation. Journal of Geophysical Research: Solid Earth, 123 (11) 10 doi:10.1029/2018jb016210
Biggs, Juliet, Dogru, Fikret, Dagliyar, Ayse, Albino, Fabien, Yip, Stanley, Brown, Sarah, Anantrasirichai, Nantheera, Atıcı, Gökhan (2021) Baseline monitoring of volcanic regions with little recent activity: application of Sentinel-1 InSAR to Turkish volcanoes. Journal of Applied Volcanology, 10 (1) doi:10.1186/s13617-021-00102-x
Yamaga, Norifumi, Mitsui, Yuta (2019) Machine Learning Approach to Characterize the Postseismic Deformation of the 2011 Tohoku‐Oki Earthquake Based on Recurrent Neural Network. Geophysical Research Letters, 46 (21) 11886-11892 doi:10.1029/2019gl084578
Albino, F., Biggs, J. (2021) Magmatic Processes in the East African Rift System: Insights From a 2015–2020 Sentinel‐1 InSAR Survey. Geochemistry, Geophysics, Geosystems, 22 (3) doi:10.1029/2020gc009488
 
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