Ocean and Polar Research

Korea Institute of Ocean Science & Technology (한국해양과학기술원)
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Missing Pattern Analysis of the GOCI-I Optical Satellite Image Data

  • Jeon, Ho-Kun (Marine Bigdata Center, Korea Institute of Ocean Science & Technology) ;
  • Cho, Hong Yeon (Marine Bigdata Center, Korea Institute of Ocean Science & Technology)
  • Received : 2022.01.14
  • Accepted : 2022.03.29
  • Published : 2022.06.30
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Abstract

Data missing in optical satellite images caused by natural variations have been a crucial barrier in observing the status of marine surfaces. Although there have been many attempts to fill the gaps of non-observation, there is little research to analyze the ratio of missing grids to overall sea grids and their seasonal patterns. This report introduces the method of quantifying the distribution of missing points and then shows how the missing points have spatial correlation and seasonal trends. Both temporal and spatial integration methods are compared to assess the effectiveness of reducing missing data. The temporal integration shows more outstanding performance than the spatial integration. Moran's I and K-function with statistical hypothesis testing show that missing grids are clustered and there is a non-random distribution from daily integration. The result of the seasonality test for Moran's I through a periodogram shows dependency on full-year, half-year, and quarter-year periods respectively. These analysis results can be used to deduce appropriate integration periods with permissible estimation errors.

Keywords

Acknowledgement

This study was conducted as part of the 「Research on Sustainable Use of Dokdo」 project of the Ministry of Oceans and Fisheries.

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