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Open AccessArticle

Dust Detection and Intensity Estimation Using Himawari-8/AHI Observation

by Lu She 1,2, Yong Xue 1,3,*, Xihua Yang 4, Jie Guang 1, Ying Li 1,2, Yahui Che 1,2, Cheng Fan 1,2 and Yanqing Xie 1,2
1
State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
Department of Electronics, Computing and Mathematics, College of Engineering and Technology, University of Derby, Derby DE22 1GB, UK
4
New South Wales Office of Environment and Heritage, Parramatta, NSW 2050, Australia
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(4), 490; https://doi.org/10.3390/rs10040490
Received: 23 January 2018 / Revised: 16 March 2018 / Accepted: 20 March 2018 / Published: 21 March 2018
(This article belongs to the Section Atmosphere Remote Sensing)
In this study, simple dust detection and intensity estimation methods using Himawari-8 Advanced Himawari Imager (AHI) data are developed. Based on the differences of thermal radiation characteristics between dust and other typical objects, brightness temperature difference (BTD) among four channels (BT11–BT12, BT8–BT11, and BT3–BT11) are used together for dust detection. When considering the thermal radiation variation of dust particles over different land cover types, a dynamic threshold scheme for dust detection is adopted. An enhanced dust intensity index (EDII) is developed based on the reflectance of visible/near-infrared bands, BT of thermal-infrared bands, and aerosol optical depth (AOD), and is applied to the detected dust area. The AOD is retrieved using multiple temporal AHI observations by assuming little surface change in a short time period (i.e., 1–2 days) and proved with high accuracy using the Aerosol Robotic Network (AERONET) and cross-compared with MODIS AOD products. The dust detection results agree qualitatively with the dust locations that were revealed by AHI true color images. The results were also compared quantitatively with dust identification results from the AERONET AOD and Ångström exponent, achieving a total dust detection accuracy of 84%. A good agreement is obtained between EDII and the visibility data from National Climatic Data Center ground measurements, with a correlation coefficient of 0.81, indicating the effectiveness of EDII in dust monitoring. View Full-Text
Keywords: dust detection; aerosol optical depth; dust index; Himawari-8; geostationary satellite dust detection; aerosol optical depth; dust index; Himawari-8; geostationary satellite
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MDPI and ACS Style

She, L.; Xue, Y.; Yang, X.; Guang, J.; Li, Y.; Che, Y.; Fan, C.; Xie, Y. Dust Detection and Intensity Estimation Using Himawari-8/AHI Observation. Remote Sens. 2018, 10, 490.

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