Title :
A semi-empirical optical data fusion technique for merging aerosol optical depth over China
Author :
Xu, Hui ; Xue, Yong ; Guang, Jie ; Li, Yingjie ; Yang, Leiku ; Hou, Tingting ; He, Xingwei ; Dong, Jing ; Chen, Ziqiang
Author_Institution :
State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China
Abstract :
MODIS and MISR are two main satellites provide aerosol observations. However, AOD products generated from these two sensors by different retrieval algorithms are inconsistent. In this paper, a semi-empirical optical fusion method was proposed to produce consistent AOD with different derived AOD datasets form MODIS and MISR. Using the semi-empirical optical algorithm, new merged AOD data sets were generated over China for 2010. We used level 2 cloud screened quality assured AERONET measurements to evaluate the merged AOD results. Our results showed that the combination of MODIS and MISR with this method could produce a more consistent, reliable AOD data with great improvement in spatial AOD coverage.
Keywords :
aerosols; atmospheric optics; atmospheric techniques; clouds; geophysical image processing; image fusion; quality assurance; AOD datasets; AOD products; China; MISR; MODIS; aerosol observations; aerosol optical depth; level 2 cloud screened quality assured AERONET measurements; retrieval algorithms; semiempirical optical algorithm; semiempirical optical data fusion technique; spatial AOD coverage; Adaptive optics; Aerosols; Integrated optics; MODIS; Optical imaging; Optical sensors; Satellites; MISR; MODIS; aerosol optical depth; satellite; semi-empirical optical;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2012.6350338
