A spatiotemporal comprehensive constraint interpolation method for missing values in monthly composite Suomi-NPP VIIRS Cloud Mask images

ABSTRACT

The Earth’s nighttime light imaging data collected by the Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS DNB) are severely lost in summer, hindering the further application of VIIRS DNB data. In this article, a spatiotemporal comprehensive constraint interpolation method (SCIM) that accounts for the relative stationarity of temporal nighttime light, spatial correlations and heterogeneity among pixels is designed. Meanwhile, the method considers the seasonal fluctuations in nighttime light radiation, introduces spatial autocorrelation coefficients and spatial heterogeneity coefficients, and solves the problem of missing VIIRS DNB data. First, 8 widely used temporal interpolation methods (TIM) are selected to perform temporal interpolation for missing image data. Second, the existing VIIRS monthly images are used to construct the constraint relationship between time and space, and the pixels that do not meet the constraint conditions in the TIM simulation image are removed. The inverse distance weight (IDW) method is applied to the removed null pixels to obtain the image simulated by the SCIM. Finally, the accuracy of the TIM and SCIM is evaluated. The results show that the accuracy of the SCIM-simulated image is better than that of the TIM-simulated image. The proposed approach improves the quality of the VIIRS DNB dataset.

KEYWORDS:

• VIIRS Cloud Mask
• temporal interpolation methods
• spatiotemporal comprehensive constraint interpolation
• spatial autocorrelation
• inverse distance weight

Acknowledgments

We would like to thank the National Geophysical Data Center of the United States and the Earth Observation Group. We appreciate the editors and reviewers for their constructive comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

J.F. and Q.L. conceptualized the work. J.F. and Q.L. carried out the analytical modeling and analysis. Q.L. and J.Z. performed the nighttime light data analysis. Q.L. and Y.S. performed the land use data analysis. J.Z. and Y.S. created some graphs and tables. J.F., Q.L. and K.L. designed and conducted the experiments. J.F. and Q.L. wrote the first version of the manuscript. J.F. and J.Z. planned, coordinated, and supervised the work. All authors reviewed the manuscript.

Data availability statement

The data that support the findings of this study are openly available at https://eogdata.mines.edu/products/vnl/.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 42171413]; a grant from State Key Laboratory of Resources and Environmental Information System; the Shandong Provincial Natural Science Foundation [grant number ZR2020MD015 and ZR2020MD018]; the National Key Research and Development Program of China [grant number 2017YFB0503500]; and the Young Teacher Development Support Program of Shandong University of Technology [grant number 4072-115016].