TY - GEN
T1 - Quality assurance plan for China collection 2.0 aerosol datasets
AU - She, Lu
AU - Xue, Yong
AU - Guang, Jie
AU - He, Xingwei
AU - Li, Chi
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/4
Y1 - 2014/11/4
N2 - 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.
AB - 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.
KW - Aerosol retrieval
KW - MODIS
KW - QA flag
KW - Quality assessment
KW - Scientific dataset
UR - http://www.scopus.com/inward/record.url?scp=84911406934&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2014.6947404
DO - 10.1109/IGARSS.2014.6947404
M3 - Conference contribution
AN - SCOPUS:84911406934
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 4161
EP - 4164
BT - International Geoscience and Remote Sensing Symposium (IGARSS)
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - Joint 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014 and the 35th Canadian Symposium on Remote Sensing, CSRS 2014
Y2 - 13 July 2014 through 18 July 2014
ER -