I got an old vector dataset with polygons covering a continent. The data was first published on paper at scale 1:5 000 000 and was later digitalized. I don't have the original data and no information about the vectorization or any metadata. I guess that the distance between the vertices rather than the accuracy limits the resolution.
Vertices are saved with high resolution (e.g. "nnn.nnnnnnnnn","-nn.nnnnnnnnn"). The dataset has few points that can be georeferenced nor any nodes that are defined as coordinates (e.g. at even degrees or UTM coordinates). When I compare some coastline sections, the error is up to +/- 20km.
I'd like to find a formula to estimate the maximum error based on the distribution of the vertices. I have access to any GIS application but would prefer a robust statistical reference.
How can I calculate the maximum error of the dataset, assuming that all vertices are correct? Or phrased differently: What method can I use to find the largest resolution of the dataset?
I tried to rasterize the dataset at different cell sizes and then oversample it to a small cell size to detect the smallest possible rasterizing without loss of resolution, but that is rather time-consuming and not very mathematical approach.