{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T03:21:27Z","timestamp":1769743287218,"version":"3.49.0"},"reference-count":53,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:00:00Z","timestamp":1666310400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003604","name":"Korea Coast Guard","doi-asserted-by":"publisher","award":["Monitoring System of Spilled Oils Using Multiple Remote Sensing Techniques"],"award-info":[{"award-number":["Monitoring System of Spilled Oils Using Multiple Remote Sensing Techniques"]}],"id":[{"id":"10.13039\/501100003604","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Satellite remote sensing can measure large ocean surface areas, but the infrared-based sea surface temperature (SST) might not be correctly calculated for the pixels under clouds, resulting in missing values in satellite images. Early studies for the gap-free raster maps of satellite SST were based on spatial interpolation using in situ measurements. In this paper, however, an alternative spatial gap-filling method using regression residual kriging (RRK) for the Geostationary Korea Multi-Purpose Satellite-2A (GK2A) daily SST was examined for the seas around the Korean Peninsula. Extreme outliers were first removed from the in situ measurements and the GK2A daily SST images using multi-step statistical procedures. For the pixels on the in situ measurements after the quality control, a multiple linear regression (MLR) model was built using the selected meteorological variables such as daily SST climatology value, specific humidity, and maximum wind speed. The irregular point residuals from the MLR model were transformed into a residual grid by optimized kriging for the residual compensation for the MLR estimation of the null pixels. The RRK residual compensation method improved accuracy considerably compared with the in situ measurements. The gap-filled 18,876 pixels showed the mean bias error (MBE) of \u22120.001 \u00b0C, the mean absolute error (MAE) of 0.315 \u00b0C, the root mean square error (RMSE) of 0.550 \u00b0C, and the correlation coefficient (CC) of 0.994. The case studies made sure that the gap-filled SST with RRK had very similar values to the in situ measurements to those of the MLR-only method. This was more apparent in the typhoon case: our RRK result was also stable under the influence of typhoons because it can cope with the abrupt changes in marine meteorology.<\/jats:p>","DOI":"10.3390\/rs14205265","type":"journal-article","created":{"date-parts":[[2022,10,24]],"date-time":"2022-10-24T10:09:23Z","timestamp":1666606163000},"page":"5265","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Spatial Gap-Filling of GK2A Daily Sea Surface Temperature (SST) around the Korean Peninsula Using Meteorological Data and Regression Residual Kriging (RRK)"],"prefix":"10.3390","volume":"14","author":[{"given":"Jihye","family":"Ahn","sequence":"first","affiliation":[{"name":"Research Institute for Geomatics, Pukyong National University, Busan 48513, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5251-6100","authenticated-orcid":false,"given":"Yangwon","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University, Busan 48513, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5134","DOI":"10.1002\/2014JC010349","article-title":"Ensemble assimilation of ARGO temperature profile, sea surface temperature, and altimetric satellite data into an eddy permitting primitive equation model of the North Atlantic Ocean","volume":"120","author":"Yan","year":"2015","journal-title":"J. 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