DocumentCode
2194968
Title
Aerosol optical depth retrieval over China from NOAA AVHRR data
Author
Yingjie Li ; Yong Xue ; Tingting Hou ; Leiku Yang ; Chi Li ; Jia Liu
Author_Institution
State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China
fYear
2012
fDate
22-27 July 2012
Firstpage
3658
Lastpage
3661
Abstract
A new algorithm for Land Aerosol property and Bidirectional reflectance Inversion by Time Series technique (LABITS) is presented and applied to National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA AVHRR) data over China. Based on the assumptions that the surface bidirectional reflective property are not varying during one day and aerosol characteristics are constant in 0.1° × 0.1° window, we inverse the aerosol optical depth (AOD) and bidirectional reflectance distribution function (BRDF) parameters. Preliminary AOD validation with Aerosol Robotic Network (AERONET) data shows that the correlation coefficient, R2, is 0.79, the root-mean-square error, RMSE, is 0.13 and the uncertainty is Δτ= ±0.05 ± 0.20Δ. Comparing with MODIS AOD product, it is found that both the AOD results are consistent very well. The R2 is 0.80 and RMSE is 0.10. The algorithm is flexible and appropriate for aerosol retrieval over both dark and bright land surface. It is potential to retrieve long term global AOD over land from NOAA AVHRR data since 1980s and to study aerosol climatology and global climate change well.
Keywords
aerosols; atmospheric optics; atmospheric techniques; time series; AERONET data; Aerosol Robotic Network; China; LABITS; NOAA AVHRR data; aerosol optical depth retrieval; bidirectional reflectance distribution function; bidirectional reflectance inversion; land aerosol property; time series; Aerosols; MODIS; Optical reflection; Optical sensors; Remote sensing; Satellites; US Government agencies; Advanced Very High Resolution Radiometer (AVHRR); aerosol optical depth (AOD); remote sensing inversion; surface bidirectional reflectance; time series;
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.2012.6350623
Filename
6350623
Link To Document