DocumentCode :
144047
Title :
Quality assurance plan for China collection 2.0 aerosol datasets
Author :
Lu She ; Yong Xue ; Jie Guang ; Xingwei He ; Chi Li
Author_Institution :
Key Lab. of Digital Earth Sci., Inst. of Remote Sensing & Digital Earth, Beijing, China
fYear :
2014
fDate :
13-18 July 2014
Firstpage :
4161
Lastpage :
4164
Abstract :
The inversion of atmospheric aerosol optical depth (AOD) using satellite data has always been a challenge topic in atmospheric research. In order to solve the aerosol retrieval problem over bright land surface, the Synergetic Retrieval of Aerosol Properties (SRAP) algorithm has been developed based on the synergetic using of the MODIS data of TERRA and AQUA satellites [1, 2]. In this paper we describe, in details, the quality assessment or quality assurance (QA) plan for AOD products derived using the SRAP algorithm. The pixel-based QA plan is to give a QA flag to every step of the process in the AOD retrieval. The quality assessment procedures include three common aspects: 1) input data resource flags, 2) retrieval processing flags, 3) product quality flags [3]. Besides, all AOD products are assigned a QA `confidence\´ flag (QAC) that represents the aggregation of all the individual QA flags. This QAC value ranges from 3 to 0, with QA = 3 indicating the retrievals of highest confidence and QA = 2/QA = 1 progressively lower confidence [4], and 0 means `bad\´ quality. These QA (QAC) flags indicate how the particular retrieval process should be considered. It is also used as a filter for expected quantitative value of the retrieval, or to provide weighting for aggregating/averaging computations [5]. All of the QA flags are stored as a "bit flag" scientific dataset array in which QA flags of each step are stored in particular bit positions.
Keywords :
aerosols; atmospheric optics; AQUA satellites; China; MODIS data; QA confidence flag; QA flag; QA flags; SRAP algorithm; TERRA satellites; aerosol datasets; aerosol retrieval problem; atmospheric aerosol optical depth; atmospheric research; bright land surface; input data resource flags; particular retrieval process; pixel-based QA plan; product quality flags; quality assessment; quality assurance plan; retrieval processing flags; synergetic retrieval-of-aerosol properties algorithm; Aerosols; Asia; Clouds; Convergence; MODIS; Optical filters; Quality assessment; Aerosol retrieval; MODIS; QA flag; Quality assessment; Scientific dataset;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
Type :
conf
DOI :
10.1109/IGARSS.2014.6947404
Filename :
6947404
Link To Document :
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