Filling the missing data gaps of daily MODIS AOD using spatiotemporal interpolation
Yang, Jing1,2; Hu, Maogui1,3
Corresponding AuthorHu, Maogui(humg@lreis.ac.cn)
AbstractAerosol is an important component of the atmosphere that affects the environment, climate, and human health. Remote sensing is an efficient observation method for monitoring global aerosol distribution and changes over time. The daily Moderate Resolution Imaging Spectroradiometer (MODIS) level-2 aerosol optical depth (AOD) (Collection 6) product (10 km resolution) is often used to study climate change and air pollution. However, the product is prone to yielding large amounts of data gaps due to the unfeasibility of retrieving reliable estimates under cloudy conditions, and these data gaps inevitably affect the results and analysis of the product's application. In this study, a geostatistical data interpolation framework based on the spatiotemporal kriging method was implemented to interpolate satellite AOD products in Beijing, China. Compared to the ordinary kriging method for filling data gaps, the spatiotemporal interpolation not only utilizes spatial autocorrelation but also considers the temporal and spatiotemporal autocorrelations between different locations. In the study region, the completeness of the spatiotemporal-interpolated AOD product reaches 67.73%, which is significantly superior to the completeness of the original MODIS product (14.27%) and that of the spatial kriging-interpolated AOD product (33.3%). The cross-validation results show that the mean absolute error of the spatiotemporal kriging results (0.07) is lower than that of the ordinary kriging (0.09). (C) 2018 Elsevier B.V. All rights reserved.
KeywordMODIS aerosol product Spatiotemporal correlation Missing AOD data Interpolation
Indexed BySCI
Funding ProjectNational Natural Science Foundation of China[41771434] ; National Natural Science Foundation of China[41531179] ; State Key Laboratory of Resource and Environment Information System[O88RA200YA]
Funding OrganizationNational Natural Science Foundation of China ; State Key Laboratory of Resource and Environment Information System
WOS Research AreaEnvironmental Sciences & Ecology
WOS SubjectEnvironmental Sciences
WOS IDWOS:000432475300066
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Cited Times:10[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Corresponding AuthorHu, Maogui
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China
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GB/T 7714
Yang, Jing,Hu, Maogui. Filling the missing data gaps of daily MODIS AOD using spatiotemporal interpolation[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2018,633:677-683.
APA Yang, Jing,&Hu, Maogui.(2018).Filling the missing data gaps of daily MODIS AOD using spatiotemporal interpolation.SCIENCE OF THE TOTAL ENVIRONMENT,633,677-683.
MLA Yang, Jing,et al."Filling the missing data gaps of daily MODIS AOD using spatiotemporal interpolation".SCIENCE OF THE TOTAL ENVIRONMENT 633(2018):677-683.
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