Retrieval of aerosol optical depth over bright targets in the urban areas of North China during winter View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2012-09

AUTHORS

ShenShen Li, LiangFu Chen, JinHua Tao, Dong Han, ZhongTing Wang, Lin Su, Meng Fan, Chao Yu

ABSTRACT

Two factors that affect satellite retrieval of Aerosol Optical Depth (AOD) are aerosol model assumptions and the separation of surface reflectance. NASA/MODIS Dense Dark Vegetation (DDV) algorithm has been proven valuable in deriving aerosol distribution and properties over land; however, it cannot be applied to bright targets. As a supplement to the DDV algorithm, an algorithm to retrieve AOD over urban areas in North China in winter is developed using MODIS data, including (1) the generation and analysis of adjacent clear-days surface reflectance using MOD09 product from 2007 to 2008, and (2) seasonal aerosol models derived from AERONET data in Beijing and Xianghe sites. Ground-based measurements using sun photometers were used to validate the retrieved AOD, and the correlation coefficient (r) is up to 0.931. Especially for high AOD values (AOD>0.4), more retrievals meet the inversion accuracy. The temporal variations of retrieval errors over urban, rural and mountain regions were examined, and the results indicated that the variation of blue-band surface reflectance is less than 0.02 in a short period except for unusual weather conditions, the retrieval bias is under 0.08, and the relative error decreases as the AOD increases. More... »

PAGES

1545-1553

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11430-012-4432-1

DOI

http://dx.doi.org/10.1007/s11430-012-4432-1

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https://app.dimensions.ai/details/publication/pub.1047502790


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