Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations

	Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations
	Di, Aojie 1; Xue, Yong 1; Yang, Xihua 1; Leys, John 1; Guang, Jie 1; Mei, Linlu 1; Wang, Jingli 1; She, Lu 1; Hu, Yincui 1; He, Xingwei 1
刊名	REMOTE SENSING
	2016
卷号	8 期号:9
关键词	DIRECTIONAL REFLECTANCE EOS-MODIS LAI SURFACE FOREST RETRIEVAL INVERSION VALIDATION ALGORITHM MODEL
通讯作者	Xue, Y (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China. ; Xue, Y (reprint author), Univ Derby, Dept Comp & Math, Coll Engn & Technol, Kedleston Rd, Derby DE22 1GB, England.
英文摘要	The Xinjiang Uyghur Autonomous Region (Xinjiang) is located near the western border of China. Xinjiang has a high frequency of dust storms, especially in late winter and early spring. Geostationary satellite remote sensing offers an ideal way to monitor the regional distribution and intensity of dust storms, which can impact the regional climate. In this study observations from the Indian National Satellite (INSAT) 3D are used for dust storm detection in Xinjiang because of the frequent 30-min observations with six bands. An analysis of the optical properties of dust and its quantitative relationship with dust storms in Xinjiang is presented for dust events in April 2014. The Aerosol Optical Depth (AOD) derived using six predefined aerosol types shows great potential to identify dust events. Cross validation between INSAT-3D retrieved AOD and MODIS AOD shows a high coefficient of determination (R-2 = 0.92). Ground validation using AERONET (Aerosol Robotic Network) AOD also shows a good correlation with R-2 of 0.77. We combined the apparent reflectance (top-of-atmospheric reflectance) of visible and shortwave infrared bands, brightness temperature of infrared bands and retrieved AOD into a new Enhanced Dust Index (EDI). EDI reveals not only dust extent but also the intensity. EDI performed very well in measuring the intensity of dust storms between 22 and 24 April 2014. A visual comparison between EDI and Feng Yun-2E (FY-2E) Infrared Difference Dust Index (IDDI) also shows a high level of similarity. A good linear correlation (R-2 of 0.78) between EDI and visibility on the ground demonstrates good performance of EDI in estimating dust intensity. A simple threshold method was found to have a good performance in delineating the extent of the dust plumes but inadequate for providing information on dust plume intensity.
学科主题	Remote Sensing
类目[WOS]	Remote Sensing
收录类别	SCI
语种	英语
WOS记录号	WOS:000385488000012
内容类型	期刊论文
源URL	[http://ir.radi.ac.cn/handle/183411/39219]
专题	遥感与数字地球研究所_SCI/EI期刊论文_期刊论文
作者单位	1.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China 2.Univ Derby, Dept Comp & Math, Coll Engn & Technol, Kedleston Rd, Derby DE22 1GB, England 3.New South Wales Off Environm & Heritage, Sydney, NSW 2000, Australia 4.Griffith Univ, Griffith Sch Environm, Brisbane, Qld 4111, Australia 5.China Meteorol Adm, Inst Urban Meteorol, Beijing 100089, Peoples R China 6.Hebei Normal Univ, Coll Resources & Environm Sci, Hebei Key Lab Environm Change & Ecol Construct, Shijiazhuang 050024, Peoples R China
推荐引用方式 GB/T 7714	Di, Aojie,Xue, Yong,Yang, Xihua,et al. Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations[J]. REMOTE SENSING,2016,8(9).
APA	Di, Aojie.,Xue, Yong.,Yang, Xihua.,Leys, John.,Guang, Jie.,...&Fan, Cheng.(2016).Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations.REMOTE SENSING,8(9).
MLA	Di, Aojie,et al."Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations".REMOTE SENSING 8.9(2016).