Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations
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 dus...
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ftdoajarticles:oai:doaj.org/article:b02cc70f7cab4147a2cb70c3c5ba8a44 2023-05-15T13:06:55+02:00 Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations Aojie Di Yong Xue Xihua Yang John Leys Jie Guang Linlu Mei Jingli Wang Lu She Yincui Hu Xingwei He Yahui Che Cheng Fan 2016-08-01T00:00:00Z https://doi.org/10.3390/rs8090702 https://doaj.org/article/b02cc70f7cab4147a2cb70c3c5ba8a44 EN eng MDPI AG http://www.mdpi.com/2072-4292/8/9/702 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs8090702 https://doaj.org/article/b02cc70f7cab4147a2cb70c3c5ba8a44 Remote Sensing, Vol 8, Iss 9, p 702 (2016) aerosol optical depth aerosol type dust storm INSAT-3D geostationary satellite Science Q article 2016 ftdoajarticles https://doi.org/10.3390/rs8090702 2022-12-31T03:20:03Z 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. Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Indian Remote Sensing 8 9 702 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
aerosol optical depth aerosol type dust storm INSAT-3D geostationary satellite Science Q |
spellingShingle |
aerosol optical depth aerosol type dust storm INSAT-3D geostationary satellite Science Q Aojie Di Yong Xue Xihua Yang John Leys Jie Guang Linlu Mei Jingli Wang Lu She Yincui Hu Xingwei He Yahui Che Cheng Fan Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations |
topic_facet |
aerosol optical depth aerosol type dust storm INSAT-3D geostationary satellite Science Q |
description |
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. |
format |
Article in Journal/Newspaper |
author |
Aojie Di Yong Xue Xihua Yang John Leys Jie Guang Linlu Mei Jingli Wang Lu She Yincui Hu Xingwei He Yahui Che Cheng Fan |
author_facet |
Aojie Di Yong Xue Xihua Yang John Leys Jie Guang Linlu Mei Jingli Wang Lu She Yincui Hu Xingwei He Yahui Che Cheng Fan |
author_sort |
Aojie Di |
title |
Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations |
title_short |
Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations |
title_full |
Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations |
title_fullStr |
Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations |
title_full_unstemmed |
Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations |
title_sort |
dust aerosol optical depth retrieval and dust storm detection for xinjiang region using indian national satellite observations |
publisher |
MDPI AG |
publishDate |
2016 |
url |
https://doi.org/10.3390/rs8090702 https://doaj.org/article/b02cc70f7cab4147a2cb70c3c5ba8a44 |
geographic |
Indian |
geographic_facet |
Indian |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Remote Sensing, Vol 8, Iss 9, p 702 (2016) |
op_relation |
http://www.mdpi.com/2072-4292/8/9/702 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs8090702 https://doaj.org/article/b02cc70f7cab4147a2cb70c3c5ba8a44 |
op_doi |
https://doi.org/10.3390/rs8090702 |
container_title |
Remote Sensing |
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8 |
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9 |
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702 |
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1766027041607516160 |