There are `r nrow(header %>% filter(is.na(`Location uncertainty (m)`)))`. As a first approximation, we assign the median of the respective dataset, as a negative value, to indicate this is an estimation, rather than a measure.
There are `r nrow(header %>% filter(is.na(`Location uncertainty (m)`)))`. As a first approximation, we assign the median of the respective dataset, as a negative value to indicate this is an estimation, rather than a measure.
There are still `r nrow(header %>% filter(is.na(`Location uncertainty (m)`)))` plots with no estimation of location uncertainty.
## 2 Formations
Fill out the columns `Forest:Sparse.vegetation` with 0\\NAs, where necessary. Create columns `is.forest` and `is.non.forest` using script developed for sPlot 2.1
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I am not assigning plots to Faber-Langedon formation at this stage, as this is only possible for European plots having an ESY classification.