[R-sig-Geo] How to objectively subset cities by population

[Thiago V. dos Santos]

Dear all,

I have temperature records of nearly 1200 locations in southern Brazil.

I am writing a shiny app that will show an interactive map with the locations plotted as circles, where the user can click a location to see its temperature time series.

However, if I show all the locations in the map, it will look really bad, too cramped.

Therefore, in an attempt to make the map look a bit cleaner, I am trying to think of an objective way to subset the locations. My initial approach would be to show only the "largest" locations, i.e. the ones with a population above a certain threshold.

The problem is: the distribution of the population is so positively skewed that I am having a hard time determining the optimal cutoff point.

Does anybody here know any tool or method, possibly spatial, that can assist me with this analysis?

These are the locations I am working with:

#-------------------------------
# Download and summarize
locs <- read.csv("https://www.dropbox.com/s/ykdd8x1mlc76klt/locations.csv?raw=1")
hist(locs$Population)
summary(locs$Population)

# Convert to spatial points and plot
require(sp)
coordinates(locs) <- cbind(locs$Lon , locs$Lat)
plot(locs)
bubble(locs,"Population")
#-------------------------------

Thanks in advance,
 -- Thiago V. dos Santos

PhD student
Land and Atmospheric Science
University of Minnesota
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