Seasonal decomposition
Well, it looks like the number of flights fluctuates a lot on weekdays, which is indeed a dominant characteristic of human-related activities. Let's verify that by identifying and removing the weekly seasonality by decomposing this time-series into the seasonal, trend, and random components with moving averages.
Although this can be done manually by utilizing the diff and lag functions, there's a much more straightforward way to do so with the decompose function from the stats package:
> plot(decompose(ts(daily$N, frequency = 7)))
Removing the spikes in the means of weekly seasonality reveals the overall trend of the number ...
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