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Due to sparse ground sensors, particularly in source regions, dust monitoring relies mainly on remote sensing through Aerosol Optical Depth (AOD) retrievals from polar-orbiting satellite optical instruments. These are valuable but lack the temporal resolution for precise plume tracking and source characterization. We introduce DustSCAN, a five-year, hourly dust plume dataset derived from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) images on geostationary-orbit Meteosat satellites. Using multi-channel infrared images, we detect atmospheric dust and track hourly dust-affected pixels. These are clustered into discrete plumes using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. DustSCAN includes 9950 discrete plumes over 2018-2022 across the Sahara, the Arabian Desert, and Western and Central Asia. It complements existing resources and provides a framework for detailed analysis of dust sources, trajectories, and impacts. Its distinctive event-based and spatio-temporal detail offers an advancement in unraveling the complexities of dust storm dynamics.<\/jats:p>","DOI":"10.1038\/s41597-024-03452-4","type":"journal-article","created":{"date-parts":[[2024,6,8]],"date-time":"2024-06-08T07:01:33Z","timestamp":1717830093000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["DustSCAN: A Five Year (2018-2022) Hourly Dataset of Dust Plumes From SEVIRI"],"prefix":"10.1038","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-1909-4646","authenticated-orcid":false,"given":"Faisal","family":"AlNasser","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dara","family":"Entekhabi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,6,8]]},"reference":[{"key":"3452_CR1","doi-asserted-by":"publisher","unstructured":"Knippertz, P. & Stuut, J.-B. 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