{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T10:16:04Z","timestamp":1773310564154,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2019,1,18]],"date-time":"2019-01-18T00:00:00Z","timestamp":1547769600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) and National Oceanic and Atmospheric Administration (NOAA)-20 has been providing a large amount of global ocean color data, which are critical for monitoring and understanding of ocean optical, biological, and ecological processes and phenomena. However, VIIRS-derived daily ocean color images on either SNPP or NOAA-20 have some limitations in ocean coverage due to its swath width, high sensor-zenith angle, high sun glint, and cloud, etc. Merging VIIRS ocean color products derived from the SNPP and NOAA-20 significantly increases the spatial coverage of daily images. The two VIIRS sensors on the SNPP and NOAA-20 have similar sensor characteristics, and global ocean color products are generated using the same Multi-Sensor Level-1 to Level-2 (MSL12) ocean color data processing system. Therefore, the merged VIIRS ocean color data from the two sensors have high data quality with consistent statistical property and accuracy globally. Merging VIIRS SNPP and NOAA-20 ocean color data almost removes the gaps of missing pixels due to high sensor-zenith angles and high sun glint contamination, and also significantly reduces the gaps due to cloud cover. However, there are still gaps of missing pixels in the merged ocean color data. In this study, the Data Interpolating Empirical Orthogonal Functions (DINEOF) are applied on the merged VIIRS SNPP\/NOAA-20 global Level-3 ocean color data to completely reconstruct the missing pixels. Specifically, DINEOF is applied to 30 days of daily merged global Level-3 chlorophyll-a (Chl-a) data of 9-km spatial resolution from 19 June to 18 July 2018. To quantitatively evaluate the accuracy of the DINEOF reconstructed data, a set of valid pixels are intentionally treated as \u201cmissing pixels\u201d, so that reconstructed data can be compared with the original data. Results show that mean ratios of the reconstructed\/original are 1.012, 1.012, 1.015, and 0.997 for global ocean, oligotrophic waters, deep waters, and coastal and inland waters, respectively. The corresponding standard deviation (SD) of the ratios are 0.200, 0.164, 0.182, and 0.287, respectively. Gap-filled daily Chl-a images reveal many large-scale and meso-scale ocean features that are invisible in the original SNPP or NOAA-20 Chl-a images. It is also demonstrated that the gap-filled data based on the merged products show more details in the dynamic ocean features than those based on SNPP or NOAA-20 alone.<\/jats:p>","DOI":"10.3390\/rs11020178","type":"journal-article","created":{"date-parts":[[2019,1,18]],"date-time":"2019-01-18T03:00:37Z","timestamp":1547780437000},"page":"178","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":72,"title":["Filling the Gaps of Missing Data in the Merged VIIRS SNPP\/NOAA-20 Ocean Color Product Using the DINEOF Method"],"prefix":"10.3390","volume":"11","author":[{"given":"Xiaoming","family":"Liu","sequence":"first","affiliation":[{"name":"National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, Center for Satellite Applications and Research, E\/RA3, 5830 University Research Ct., College Park, MD 20740, USA"},{"name":"Cooperative Institute for Research in the Atmosphere at Colorado State University, Fort Collins, CO 80523, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7019-3125","authenticated-orcid":false,"given":"Menghua","family":"Wang","sequence":"additional","affiliation":[{"name":"National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, Center for Satellite Applications and Research, E\/RA3, 5830 University Research Ct., College Park, MD 20740, USA"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"104","DOI":"10.5670\/oceanog.2010.09","article-title":"Study of marine ecosystem and biogeochemistry now and in the future: Example of the unique contributions from the space","volume":"23","author":"Yoder","year":"2010","journal-title":"Oceanography"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"13463","DOI":"10.1002\/2013JD020389","article-title":"Joint Polar Satellite System: The United States next generation civilian polar-orbiting environmental satellite system","volume":"118","author":"Goldberg","year":"2013","journal-title":"J. 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