I then compared rural stations in the Mid-West (a low-population-density region of the U.S.) with all rural stations. There wasn't a major difference between these two sets of stations either. Commenter steven was not convinced, however. He posted some satellite pictures of rural stations that are located in what appear to be sub-urban areas.
How could we measure the impact of human populations on station temperature with the data available to us? It's clearly not enough to express doubt and speculate about what might be going on.
Here's what I came up with. There's a vegetation property in the station metadata. If you look at stations in regions that are forested (FO), marshes (MA) or deserts (DE), they appear to be actually rural. I looked at a subset of such stations in Google Maps, and they are not close to human settlements, with few exceptions. The GHCN Processor command I used to obtain a temperature series is the following.
ghcnp -dt mean -include "population_type=='R' && (vegetation=='FO' || vegetation=='MA' || vegetation=='DE')" -o /tmp/global-rural-plus.csv
575 stations fit these characteristics. For comparison, I got temperature series for big cities (population > 0.5 million), and small towns and cities (population <= 0.5 million.) I calculated 12-year moving averages in each case, which is what you see in the figure below.
There might be some differences, but they are always small, and we've compared several different stations sets now, globally and at the U.S. level.
An argument could also be made that small human settlements increase the albedo of an area, so they might have a cooling effect.
Here's an actual UHI finding of interest. I compared cities of population over 2 million with towns whose population is between 10,000 and 15,000. The difference is more pronounced in this case.
The overall effect is still negligible, nevertheless. The number of cities decreases exponentially with population size.