{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T02:53:41Z","timestamp":1781751221411,"version":"3.54.5"},"reference-count":56,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,3,5]],"date-time":"2023-03-05T00:00:00Z","timestamp":1677974400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Union\u2019s Horizon 2020 European Green Deal Research and Innovation Program (H2020-LC-GD2020-4)","award":["101037643"],"award-info":[{"award-number":["101037643"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Monitoring, assessing, and measuring oil spills is essential in protecting the marine environment and in efforts to clean oil spills. One of the most recent oil spills happened near Port Fourchon, Louisiana, caused by Hurricane Ida (Category 4), that had a wind speed of 240 km\/h. In this regard, Earth Observation (EO) Satellite Remote Sensing (SRS) images can effectively highlight oil spills in marine areas as a \u201cfast and no-cost\u201d technique. However, clouds and the sea surface spectral signature complicate the interpretation of oil spill areas in the optical images. In this study, Principal Component Analysis (PCA) has been applied of Landsat-8 and Sentinel-2 SRS images to improve information from the optical sensor bands. The PCA produces an output unrelated to the main bands, making it easier to distinguish oil spills from clouds and seawater due to the spectral diversity between oil, clouds, and the seawater surface. Then, an additional step has been applied to highlight the oil spill area using PCAs with different band combinations. Furthermore, Sentinel-1 (SAR), Sentinel-2 (optical), and Landsat-8 (optical) SRS images have been analyzed with cross-sections to suppress the \u201clook-alike\u201d effect of marine oil spill areas. Finally, mean and high-pass filters were used for Land Surface Temperature (LST) SRS images estimated from the Landsat thermal band. The results show that the seawater value is about \u221217.5 db and the oil spill area shows a value between \u221222.5 db and \u221225 db; the Landsat 8 satellites thermal band 10, depicting contrast at some areas for oil spill, can be determined by the 3 \u00d7 3 and 5 \u00d7 5 Kernel High pass and the 3 \u00d7 3 Mean filter. The results demonstrate that the SRS images should be used together to improve oil spill detection studies results.<\/jats:p>","DOI":"10.3390\/rs15051460","type":"journal-article","created":{"date-parts":[[2023,3,6]],"date-time":"2023-03-06T01:35:30Z","timestamp":1678066530000},"page":"1460","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["A Principal Component Analysis Methodology of Oil Spill Detection and Monitoring Using Satellite Remote Sensing Sensors"],"prefix":"10.3390","volume":"15","author":[{"given":"Niyazi","family":"Arslan","sequence":"first","affiliation":[{"name":"Department of Mining Engineering, Cukurova University, Adana 01330, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meysam","family":"Majidi Nezhad","sequence":"additional","affiliation":[{"name":"Department of Sustainable Energy Systems, M\u00e4lardalen University, SE 72123 V\u00e4ster\u00e5s, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1352-3209","authenticated-orcid":false,"given":"Azim","family":"Heydari","sequence":"additional","affiliation":[{"name":"Department of Astronautics, Electrical and Energy Engineering (DIAEE), Sapienza University of Rome, 00184 Rome, Italy"},{"name":"Department of Energy Management and Optimization, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman 7631133131, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0752-2146","authenticated-orcid":false,"given":"Davide","family":"Astiaso Garcia","sequence":"additional","affiliation":[{"name":"Department of Planning, Design, Technology of Architecture, Sapienza University of Rome, 00185 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2327-4015","authenticated-orcid":false,"given":"Georgios","family":"Sylaios","sequence":"additional","affiliation":[{"name":"Laboratory of Ecological Engineering and Technology, Department of Environmental Engineering, Democritus University of Thrace, 67100 Xanthi, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1016\/j.scitotenv.2017.02.221","article-title":"Identification and prioritization of areas with high environmental risk in Mediterranean coastal areas: A flexible approach","volume":"590\u2013591","author":"Marignani","year":"2017","journal-title":"Sci. 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