Compared performance and trade-offs of two space–time interpolation techniques.

Presented guidelines for filling data gaps at varying space–time coverage scenarios.

EOF outperformed space–time kriging but suffered with decreased spatial coverage.

Space–time kriging was much less sensitive to spatial gaps than temporal gaps.

Differences between the two approaches decreased with temporally aggregated data.