{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T18:15:53Z","timestamp":1780337753634,"version":"3.54.1"},"reference-count":29,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2017,8,22]],"date-time":"2017-08-22T00:00:00Z","timestamp":1503360000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China(NSFC)","award":["41671345"],"award-info":[{"award-number":["41671345"]}]},{"name":"National Key Research Program of China","award":["2016YFB0502500"],"award-info":[{"award-number":["2016YFB0502500"]}]},{"name":"Scientific Research Foundation for the talent, Nanjing University of Information Science &amp; Technology"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Every year, a large number of aerosols are released from dust storms into the atmosphere, which may have potential impacts on the climate, environment, and air quality. Detecting dust aerosols and monitoring their movements and evolutions in a timely manner is a very significant task. Satellite remote sensing has been demonstrated as an effective means for observing dust aerosols. In this paper, an algorithm based on the multi-spectral technique for detecting dust aerosols was developed by combining measurements of moderate resolution imaging spectroradiometer (MODIS) reflective solar bands and thermal emissive bands. Data from dust events that occurred during the past several years were collected as training data for spectral and statistical analyses. According to the spectral curves of various scene types, a series of spectral bands was selected individually or jointly, and corresponding thresholds were defined for step-by-step scene classification. The multi-spectral algorithm was applied mainly to detect dust storms in Asia. The detection results were validated not only visually with MODIS true color images, but also quantitatively with products of Ozone Monitoring Instrument (OMI) and Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP). The validations showed that this multi-spectral detection algorithm was suitable to monitor dust aerosols in the selected study areas.<\/jats:p>","DOI":"10.3390\/rs9080869","type":"journal-article","created":{"date-parts":[[2017,8,22]],"date-time":"2017-08-22T11:08:25Z","timestamp":1503400105000},"page":"869","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Detection of Asian Dust Storm Using MODIS Measurements"],"prefix":"10.3390","volume":"9","author":[{"given":"Yong","family":"Xie","sequence":"first","affiliation":[{"name":"School of Geography and Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8762-1878","authenticated-orcid":false,"given":"Wenhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and digital Earth, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6978-2018","authenticated-orcid":false,"given":"John","family":"Qu","sequence":"additional","affiliation":[{"name":"Environmental Science and Technology Center (ESTC) and Department of Geography and GeoInformation Science (GGS), George Mason University, Fairfax, VA 22030, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,8,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Estell\u00e9s, V., Mart\u00ednez-Lozano, J.A., Utrillas, M.P., and Campanelli, M. 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