DOI: 10.1016/j.atmosenv.2015.05.023
Scopus记录号: 2-s2.0-84929464641
论文题名: A consistent aerosol optical depth (AOD) dataset over mainland China by integration of several AOD products
作者: Xu H ; , Guang J ; , Xue Y ; , de Leeuw G ; , Che Y ; H ; , Guo J ; , He X ; W ; , Wang T ; K
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2015
卷: 114 起始页码: 48
结束页码: 56
语种: 英语
英文关键词: Aerosol optical depth
; Albedo
; Merging
; MISR
; MODIS
; SeaWiFS
Scopus关键词: Aerosols
; Algorithms
; Atmospheric aerosols
; Band structure
; Data flow analysis
; Image reconstruction
; Imaging techniques
; Maximum likelihood
; Maximum likelihood estimation
; Mean square error
; Merging
; Optical properties
; Remote sensing
; Satellite imagery
; Solar radiation
; Spectrometers
; Aerosol optical depths
; Albedo
; MISR
; MODIS
; SeaWiFs
; Radiometers
; AERONET
; aerosol composition
; albedo
; data set
; ground-based measurement
; marine atmosphere
; MISR
; MODIS
; optical depth
; SeaWiFS
; spatiotemporal analysis
; accuracy
; aerosol
; albedo
; algorithm
; Article
; Asia
; China
; error
; latitude
; longitude
; maximum likelihood method
; optical depth
; priority journal
; remote sensing
; surface property
; temporal analysis
; time series analysis
; weight
; China
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: The Moderate Resolution Imaging Spectroradiometer (MODIS), the Multiangle Imaging Spectroradiometer (MISR) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) provide validated aerosol optical depth (AOD) products over both land and ocean. However, the values of the AOD provided by each of these satellites may show spatial and temporal differences due to the instrument characteristics and aerosol retrieval algorithms used for each instrument. In this article we present a method to produce an AOD data set over Asia for the year 2007 based on fusion of the data provided by different instruments and/or algorithms. First, the bias of each satellite-derived AOD product was calculated by comparison with ground-based AOD data derived from the AErosol RObotic NETwork (AERONET) and the China Aerosol Remote Sensing NETwork (CARSNET) for different values of the surface albedo and the AOD. Then, these multiple AOD products were combined using the maximum likelihood estimate (MLE) method using weights derived from the root mean square error (RMSE) associated with the accuracies of the original AOD products. The original and merged AOD dataset has been validated by comparison with AOD data from the CARSNET. Results show that the mean bias error (MBE) and mean absolute error (MAE) of the merged AOD dataset are not larger than that of any of the original AOD products. In addition, for the merged AOD dataset the fraction of pixels with no data is significantly smaller than that of any of the original products, thus increasing the spatial coverage. The fraction of retrievable area is about 50% for the merged AOD dataset and between 5% and 20% for the MISR, SeaWiFS, MODIS-DT and MODIS-DB algorithms. © 2015 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81653
Appears in Collections: 气候变化事实与影响
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作者单位: Key Laboratory of Digital Earth Sciences, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing, China; Faculty of Life Sciences and Computing, London Metropolitan University, 166-220 Holloway Road, London, United Kingdom; Department of Physics, University of Helsinki, Helsinki, Finland; Finnish Meteorological Institute, Climate Research Unit, Helsinki, Finland; Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing, China; University of Chinese Academy of Sciences, Beijing, China
Recommended Citation:
Xu H,, Guang J,, Xue Y,et al. A consistent aerosol optical depth (AOD) dataset over mainland China by integration of several AOD products[J]. Atmospheric Environment,2015-01-01,114