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Remote Sens. 2016, 8(9), 702; doi:10.3390/rs8090702

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

1
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
2
Department of Computing and Mathematics, College of Engineering and Technology, University of Derby, Kedleston Road, Derby DE22 1GB, UK
3
New South Wales Office of Environment and Heritage, Sydney, NSW 2000, Australia
4
Griffith School of Environment, Griffith University, Brisbane, QLD 4111, Australia
5
Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
6
Hebei Key Laboratory of Environmental Change and Ecological Construction, College of Resources and Environment Science, Hebei Normal University, Shijiazhuang 050024, China
*
Author to whom correspondence should be addressed.
Academic Editors: Janet Nichol and Prasad S. Thenkabail
Received: 1 April 2016 / Revised: 7 August 2016 / Accepted: 18 August 2016 / Published: 26 August 2016
View Full-Text   |   Download PDF [14211 KB, uploaded 26 August 2016]   |  

Abstract

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 (R2 = 0.92). Ground validation using AERONET (Aerosol Robotic Network) AOD also shows a good correlation with R2 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 (R2 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. View Full-Text
Keywords: aerosol optical depth; aerosol type; dust storm; INSAT-3D; geostationary satellite aerosol optical depth; aerosol type; dust storm; INSAT-3D; geostationary satellite
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Di, A.; Xue, Y.; Yang, X.; Leys, J.; Guang, J.; Mei, L.; Wang, J.; She, L.; Hu, Y.; He, X.; Che, Y.; Fan, C. Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations. Remote Sens. 2016, 8, 702.

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