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Proceedings Paper

Trend analysis of the aerosol optical depth over China using fusion of MODIS and MISR aerosol products via adaptive weighted estimate algorithm
Author(s): Jing Guo; Xingfa Gu; Tao Yu; Tianhai Cheng; Hao Chen; Donghai Xie
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Paper Abstract

Atmospheric aerosol play an important role in the climate change, though direct and indirect processes1. To evaluate the effects of aerosols on climate it is necessary to estimate their spatial and temporal distributions2. Since 2000, the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) have been providing global aerosol products3. However, the uncertainties still exist in current satellite aerosol products attributable to the complex surface, cloud contamination, and aerosol models used in the retrieving process5. Comparing to AERONET AOD, the larger magnitude and different variation tendency in AOD for both sensors indicate that either individual aerosol product may not be good application over China. Combing multiple sensors is a method to reduce uncertainties and improve observational accuracy. An adaptive weighted estimate algorithm of multi-sensor data fusion was presented, which could adjust the fused sensor’s weight in time according to the variation in sensor’s variance. The combined AOD product using the fusion method is in better agreement with corresponding AOD from AERONET than single sensor, which illustrate the fusion method performs better applicability in China. The fusion method can reduce uncertainties both sensors and expand the scope of the distribution in AOD. Using the latest ten-year (2002-2010) fusion product, we study the trend analysis of the aerosol optical depth over typical regions in China. The increasing trend is found over Jingjintang and Yangtze River Delta, which are highly associated with human activities.

Paper Details

Date Published: 23 September 2013
PDF: 8 pages
Proc. SPIE 8866, Earth Observing Systems XVIII, 88661X (23 September 2013); doi: 10.1117/12.2024687
Show Author Affiliations
Jing Guo, Institute of Remote Sensing Applications (China)
Chinese National Space Administration (China)
Xingfa Gu, Institute of Remote Sensing Applications (China)
Chinese National Space Administration (China)
Tao Yu, Institute of Remote Sensing Applications (China)
Chinese National Space Administration (China)
Tianhai Cheng, Institute of Remote Sensing Applications (China)
Chinese National Space Administration (China)
Hao Chen, Institute of Remote Sensing Applications (China)
Chinese National Space Administration (China)
Donghai Xie, Institute of Remote Sensing Applications (China)
Chinese National Space Administration (China)


Published in SPIE Proceedings Vol. 8866:
Earth Observing Systems XVIII
James J. Butler; Xiaoxiong (Jack) Xiong; Xingfa Gu, Editor(s)

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