{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T18:01:19Z","timestamp":1774548079379,"version":"3.50.1"},"reference-count":53,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,2,8]],"date-time":"2022-02-08T00:00:00Z","timestamp":1644278400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1835566"],"award-info":[{"award-number":["1835566"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>With approximately 800 million people globally living within 100 km of a volcano, it is essential that we build a reliable observation system capable of delivering early warnings to potentially impacted nearby populations. Global Navigation Satellite System (GNSS) and satellite Synthetic Aperture Radar (SAR) document comprehensive ground motions or ruptures near, and at, the Earth\u2019s surface and may be used to detect and analyze natural hazard phenomena. These datasets may also be combined to improve the accuracy of deformation results. Here, we prepare a differential interferometric SAR (DInSAR) time series and integrate it with GNSS data to create a fused dataset with enhanced accuracy of 3D ground motions over Hawaii island from November 2015 to April 2021. We present a comparison of the raw datasets against the fused time series and give a detailed account of observed ground deformation leading to the May 2018 and December 2020 volcanic eruptions. Our results provide important new estimates of the spatial and temporal dynamics of the 2018 Kilauea volcanic eruption. The methodology presented here can be easily repeated over any region of interest where an SAR scene overlaps with GNSS data. The results will contribute to diverse geophysical studies, including but not limited to the classification of precursory movements leading to major eruptions and the advancement of early warning systems.<\/jats:p>","DOI":"10.3390\/rs14030784","type":"journal-article","created":{"date-parts":[[2022,2,8]],"date-time":"2022-02-08T23:42:20Z","timestamp":1644363740000},"page":"784","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Integration of DInSAR Time Series and GNSS Data for Continuous Volcanic Deformation Monitoring and Eruption Early Warning Applications"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7208-8070","authenticated-orcid":false,"given":"Brianna","family":"Corsa","sequence":"first","affiliation":[{"name":"Department of Geological Sciences, The Collaborative Institute of Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, CO 80309, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3219-7069","authenticated-orcid":false,"given":"Magali","family":"Barba-Sevilla","sequence":"additional","affiliation":[{"name":"Department of Geological Sciences, The Collaborative Institute of Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, CO 80309, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5500-7600","authenticated-orcid":false,"given":"Kristy","family":"Tiampo","sequence":"additional","affiliation":[{"name":"Department of Geological Sciences, The Collaborative Institute of Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, CO 80309, USA"}]},{"given":"Charles","family":"Meertens","sequence":"additional","affiliation":[{"name":"Department of Geological Sciences, The Collaborative Institute of Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, CO 80309, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1115","DOI":"10.1130\/G24149A.1","article-title":"Forecasting Etna eruptions by real-time observation of volcanic gas composition","volume":"35","author":"Aiuppa","year":"2007","journal-title":"Geology"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"6592","DOI":"10.1029\/2018JB015911","article-title":"Application of machine learning to classification of volcanic deformation in routinely generated InSAR data","volume":"123","author":"Anantrasirichai","year":"2018","journal-title":"J. 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