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Park, Sang Seo
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Combined dust detection algorithm by using MODIS infrared channels over East Asia

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dc.contributor.author Park, Sang Seo ko
dc.contributor.author Kim, Jhoon ko
dc.contributor.author Lee, Jaehwa ko
dc.contributor.author Lee, Sukjo ko
dc.contributor.author Kim, Jeong Soo ko
dc.contributor.author Chang, Lim Seok ko
dc.contributor.author Ou, Steve ko
dc.date.available 2019-09-02T09:05:22Z -
dc.date.created 2019-08-30 ko
dc.date.issued 2014-02 ko
dc.identifier.citation REMOTE SENSING OF ENVIRONMENT, v.141, pp.24 - 39 ko
dc.identifier.issn 0034-4257 ko
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/27363 -
dc.description.abstract A new dust detection algorithm is developed by combining the results of multiple dust detection methods using IR channels onboard the MODerate resolution Imaging Spectroradiometer (MODIS). Brightness Temperature Difference (BTD) between two wavelength channels has been used widely in previous dust detection methods. However, BTD methods have limitations in identifying the offset values of the BTD to discriminate clear-sky areas. The current algorithm overcomes the disadvantages of previous dust detection methods by considering the Brightness Temperature Ratio (BTR) values of the dual wavelength channels with 30-day composite, the optical properties of the dust particles, the variability of surface properties, and the cloud contamination. Therefore, the current algorithm shows improvements in detecting the dust loaded region over land during daytime. Finally, the confidence index of the current dust algorithm is shown in 10 x 10 pixels of the MODIS observations. From January to June, 2006, the results of the current algorithm are within 64 to 81% of those found using the fine mode fraction (FMF) and aerosol index (AI) from the MODIS and Ozone Monitoring Instrument (OMI). The agreement between the results of the current algorithm and the OMI AI over the non-polluted land also ranges from 60 to 67% to avoid errors due to the anthropogenic aerosol. In addition, the developed algorithm shows statistically significant results at four AErosol RObotic NETwork (AERONET) sites in East Asia. (C) 2013 Elsevier Inc. All rights reserved. ko
dc.language 영어 ko
dc.publisher ELSEVIER SCIENCE INC ko
dc.title Combined dust detection algorithm by using MODIS infrared channels over East Asia ko
dc.type ARTICLE ko
dc.identifier.scopusid 2-s2.0-84887944164 ko
dc.identifier.wosid 000331662600003 ko
dc.type.rims ART ko
dc.identifier.doi 10.1016/j.rse.2013.09.019 ko
dc.identifier.url https://www.sciencedirect.com/science/article/pii/S0034425713003568?via%3Dihub ko
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