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《Journal of Shandong University of Science and Technology(Natural Science)》 2016-05
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Verification of MODIS C5 and C6 and Their Regional Adaptability Evaluation

YANG Yikun;SUN Lin;WEI Jing;TIAN Xinpeng;JIA Chen;College of Geomatics,Shandong University of Science and Technology;  
MODIS Collection 5(C5)and Collection 6(C6),the two current daily Aerosol Optical Depth(AOD)products based on the Dark Target(DT)and Deep Blue(DB)algorithms provided by NASA,provide important data support for the evaluation of atmospheric particulate matter and the effects of climate change.Because they are based on different aerosol retrieval methods,to make clear the precision and regional adaptability of the two products is of great significance for users in selecting reasonable data products.In this paper,the accuracy and regional adaptability of the two products in several typical regions were analyzed based on the data of AERONET distibuted in China.The results show that:1The overall retrieval accuracy of DT C6 algorithm is slightly better than that of DT C5algorithm;2Compared with DT algorithm,DB algorithm has an overall higher retrieval accuracy(R=0.91,RMSE~0.166,MAE~0.116)with significantly increased effective observation days and can reduce approximately 15%aerosol overestimation;3With higher accuracy in vegetation areas but poorer adaptability in bright areas,C6 DT algorithm has large missing values,while DB algorithm,with the capability of retrieving aerosol over both dark and bright surfaces,has higher aerosol accuracy in urban and sparse vegetated areas,thus improving the spatial continuity significantly.
【Fund】: 国家自然科学基金项目(41171270);; 山东省杰出青年基金项目(2012JQB01025)
【CateGory Index】: X513
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