LAUSR

To solve the problem of low coverage of MODIS aerosol optical depth (AOD) products, this letter proposes a 3-D spatiotemporal interpolation method to predict missing values for time series AOD products. In this study, ordinary Kriging interpolation and 3-D spatiotemporal interpolation are applied to analyze the dynamics of AOD in Beijing–Tianjin–Hebei urban agglomeration (BTHUA), China, and the performances of the two methods are compared. The results show that the 3-D spatiotemporal interpolation has a better performance in predicting missing data of AOD products. The proposed interpolation method provides a feasible solution for the establishment of long-term MODIS aerosol products with temporal and spatial consistency, and also provides effective data support for the study of urban environmental changes.