{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T00:02:30Z","timestamp":1777420950174,"version":"3.51.4"},"reference-count":35,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,4,30]],"date-time":"2020-04-30T00:00:00Z","timestamp":1588204800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006595","name":"Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii","doi-asserted-by":"publisher","award":["PN-III-P1-1.1-PD-2016-1579"],"award-info":[{"award-number":["PN-III-P1-1.1-PD-2016-1579"]}],"id":[{"id":"10.13039\/501100006595","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Institute of Computer Science of the Czech Academy of Sciences","award":["Czech Republic RVO 67985807"],"award-info":[{"award-number":["Czech Republic RVO 67985807"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>A reliable and practically useable method for gap filling in hourly Spinning Enhanced Visible and Infrared Imager (SEVIRI LST) data using ERA5 Land Skin Temperature (ERA5ST) co-variate and additional easily accessible data (elevation, time, solar radiation info) is proposed. The suggested approach provides estimates to all weather conditions and it is based on a probabilistic model via modern regression models. We have tested two classes of regression models of different complexity and flexibility, namely multiple linear regression (MLR), and generalized additive model (GAM). This analysis uses as main input the hourly LST data set over Romania, through 2016 and 2017, extracted from MSG-SEVIRI images, which is an operational product of the Land Surface Analysis\u2013Satellite Application Facility (LSA-SAF). The comparison between the estimated LST and the original LST values shows that GAM model, that takes into account the distance between missing LST locations and the nearest non-missing locations (GAM2), provides the best results, hence this was used to fill the gaps from the analyzed remote sensing product. Considering the fact that the best covariate (ERA5ST) has global coverage and it is available at high spatial resolution and temporal resolution, the proposed approach could be also used to perform the gap-filling of other existing LST remote sensing products.<\/jats:p>","DOI":"10.3390\/rs12091423","type":"journal-article","created":{"date-parts":[[2020,5,4]],"date-time":"2020-05-04T14:00:43Z","timestamp":1588600843000},"page":"1423","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Statistical Gap-Filling of SEVIRI Land Surface Temperature"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3361-483X","authenticated-orcid":false,"given":"Alexandru","family":"Dumitrescu","sequence":"first","affiliation":[{"name":"Meteo Romania (National Meteorological Administration), 013686 Bucharest, Romania"},{"name":"Research Institute of the University of Bucharest, 030018 Bucharest, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marek","family":"Brabec","sequence":"additional","affiliation":[{"name":"Department of Statistical Modeling, Institute of Computer Science of the Czech Academy of Sciences, Pod Vodarenskou vezi 2, 182 07 Prague 8, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sorin","family":"Cheval","sequence":"additional","affiliation":[{"name":"Meteo Romania (National Meteorological Administration), 013686 Bucharest, Romania"},{"name":"Research Institute of the University of Bucharest, 030018 Bucharest, Romania"},{"name":"Department of Aviation, \u201cHenri Coand\u0103\u201d Air Force Academy, 500187 Bra\u0219ov, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,30]]},"reference":[{"key":"ref_1","unstructured":"Copernicus Land Service (2019, December 19). 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