{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T06:27:50Z","timestamp":1773296870816,"version":"3.50.1"},"reference-count":70,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2024,7,28]],"date-time":"2024-07-28T00:00:00Z","timestamp":1722124800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Sciences and Engineering Research Council of Canada (NSERC)"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study investigates the relationship between geomagnetic activities and ionospheric scintillations, focusing on how solar and geomagnetic parameters influence ionospheric disturbances across varying time frames and latitudes. Utilizing indices such as Kp, Dst, sunspot numbers, and the F10.7 solar flux, we elucidate the dynamics influencing ionospheric conditions, which are vital for the reliability of satellite communications, particularly in low-latitude regions. Our analysis demonstrates a clear correlation between periods of high solar activity and increased geomagnetic disturbances, leading to heightened ionospheric scintillations, such as occurred during the solar maximum of 2015. In contrast, 2020\u2014a solar minimum period\u2014exhibited fewer disturbances, highlighting the impact of solar activity levels on ionospheric conditions. Innovatively employing ConvGRU networks, this research advances the modeling and prediction of ionospheric scintillations by integrating deep learning techniques suited to the spatiotemporal complexities of ionospheric data. The ConvGRU model effectively captures both temporal sequences and spatial distributions, offering enhanced accuracy in depicting ionospheric scintillation patterns crucial for satellite-based navigation and communication systems. Ground-based GNSS data from 121 stations across South America, collected during 2015 and 2020, provide a robust dataset for our analysis. The study highlights the influence of the solar cycle on ionospheric scintillations, with the years of maximum and minimum solar activity showing significant differences in scintillation intensity and frequency. Our evaluation of the ConvGRU models using statistical parameters demonstrated their potential for reliable ionospheric scintillation prediction. The research underscores the necessity of integrating adaptive mechanisms within models to effectively handle the dynamic nature of ionospheric disturbances influenced by external geomagnetic and solar factors. This study enhances the understanding of ionospheric scintillations and significantly advances predictive modeling capabilities using advanced machine learning techniques. The potential establishment of real-time alert systems for ionospheric disturbances could significantly benefit civilian applications, enhancing the operational efficiency of technologies reliant on accurate ionospheric information.<\/jats:p>","DOI":"10.3390\/rs16152757","type":"journal-article","created":{"date-parts":[[2024,7,29]],"date-time":"2024-07-29T09:50:05Z","timestamp":1722246605000},"page":"2757","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Prediction of Ionospheric Scintillation with ConvGRU Networks Using GNSS Ground-Based Data across South America"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3135-3613","authenticated-orcid":false,"given":"Alireza","family":"Atabati","sequence":"first","affiliation":[{"name":"Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran 19697, Iran"},{"name":"Department of Geodesy and Geomatics Engineering, University of New Brunswick, Fredericton, NB E3B 5A3, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2564-7356","authenticated-orcid":false,"given":"Iraj","family":"Jazireeyan","sequence":"additional","affiliation":[{"name":"Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran 19697, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5721-5561","authenticated-orcid":false,"given":"Mahdi","family":"Alizadeh","sequence":"additional","affiliation":[{"name":"Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran 19697, Iran"},{"name":"German Research Centre for Geosciences (GFZ), 14473 Potsdam, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7228-6509","authenticated-orcid":false,"given":"Richard B.","family":"Langley","sequence":"additional","affiliation":[{"name":"Department of Geodesy and Geomatics Engineering, University of New Brunswick, Fredericton, NB E3B 5A3, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1109\/TAES.1987.310829","article-title":"Ionospheric time-delay algorithm for single-frequency GPS users","volume":"3","author":"Klobuchar","year":"1987","journal-title":"IEEE Trans. Aerosp. Electron. 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