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Combined Dust Detection Algorithm by Using MODIS Infrared Channels over East AsiaA new dust detection algorithm is developed by combining the results of multiple dust detectionmethods 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, BTDmethods have limitations in identifying the offset values of the BTDto 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 × 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.
Document ID
20140005405
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
doi:10.1016/j.rse.2013.09.019
Authors
Park, Sang Seo (Yonsei Univ. Seoul, Korea, Republic of)
Kim, Jhoon (Yonsei Univ. Seoul, Korea, Republic of)
Lee, Jaehwa (Yonsei Univ. Seoul, Korea, Republic of)
Lee, Sukjo (National Institute of Environmental Research Incheon, Korea, Republic of)
Kim, Jeong Soo (National Institute of Environmental Research Incheon, Korea, Republic of)
Chang, Lim Seok (National Institute of Environmental Research Incheon, Korea, Republic of)
Ou, Steve (California Univ. Los Angeles, CA, United States)
Date Acquired
May 9, 2014
Publication Date
February 1, 2014
Publication Information
Publication: Remote Sensing of Environment
Publisher: Elsevier
Volume: 141
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN13128
Funding Number(s)
CONTRACT_GRANT: NNX12AD03A
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
East Asia
MODIS
dust detection

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