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

fYear

2012

fDate

22-27 July 2012

Firstpage

2524

Lastpage

2527

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International

Conference_Location

Munich

ISSN

2153-6996

Print_ISBN

978-1-4673-1160-1

Electronic_ISBN

2153-6996

Type

conf

DOI

10.1109/IGARSS.2012.6350338

Filename

6350338