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Aerosol Indices Derived from MODIS Data for Indicating Aerosol-Induced Air Pollution

Key Laboratory of Virtual Geographic Environment, Ministry of Education, College of Geographic Science, Nanjing Normal University, Nanjing 210097, China
Department of Resources and Environment, Shijiazhuang University, Shijiazhuang 050035, China
Lab. of Digital Earth Sciences, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
School of Environment, University of Auckland, Auckland 1008, New Zealand
Authors to whom correspondence should be addressed.
Remote Sens. 2014, 6(2), 1587-1604;
Received: 12 December 2013 / Revised: 29 January 2014 / Accepted: 12 February 2014 / Published: 20 February 2014
PDF [1145 KB, uploaded 19 June 2014]


Aerosol optical depth (AOD) is a critical variable in estimating aerosol concentration in the atmosphere, evaluating severity of atmospheric pollution, and studying their impact on climate. With the assistance of the 6S radiative transfer model, we simulated apparent reflectancein relation to AOD in each Moderate Resolution Imaging Spectroradiometer (MODIS) waveband in this study. The closeness of the relationship was used to identify the most and least sensitive MODIS wavebands. These two bands were then used to construct three aerosol indices (difference, ratio, and normalized difference) for estimating AOD quickly and effectively. The three indices were correlated, respectively, with in situ measured AOD at the Aerosol Robotic NETwork (AERONET) Lake Taihu, Beijing, and Xianghe stations. It is found that apparent reflectance of the blue waveband (band 3) is the most sensitive to AOD while the mid-infrared wavelength (band 7) is the least sensitive. The difference aerosol index is the most accurate in indicating aerosol-induced atmospheric pollution with a correlation coefficient of 0.585, 0.860, 0.685, and 0.333 at the Lake Taihu station, 0.721, 0.839, 0.795, and 0.629 at the Beijing station, and 0.778, 0.782, 0.837, and 0.643 at the Xianghe station in spring, summer, autumn and winter, respectively. It is concluded that the newly proposed difference aerosol index can be used effectively to study the level of aerosol-induced air pollution from MODIS satellite imagery with relative ease. View Full-Text
Keywords: aerosol indices; air pollution; 6S model; MODIS aerosol indices; air pollution; 6S model; MODIS
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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He, J.; Zha, Y.; Zhang, J.; Gao, J. Aerosol Indices Derived from MODIS Data for Indicating Aerosol-Induced Air Pollution. Remote Sens. 2014, 6, 1587-1604.

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