On Wed, Oct 20, 2010 at 11:20 AM, Peter Budny <pet...@gatech.edu> wrote:
> "Andrew S. J. Sawyer" <assaw...@gmail.com> writes: > > > My thoughts are mixed in below. > > > > On Wed, Oct 20, 2010 at 11:17, Peter Budny <pet...@gatech.edu> wrote: > > > > Antony Pegg <anttheli...@gmail.com> writes: > > > > > tagging admin area / populated centers / labels in USA seems to > > > come down to two main tags: > > > > > > admin_level and place > > > > Before you over-simplify, let me point out a couple things: > > > > 1. Not all of the US is incorporated. In the Northeast, every tiny > part > > of land is incorporated into a town or township or borough. But in > the > > Southeast (and I presume elsewhere as well), there's lots of > > unincorporated land, even in the vicinity of large cities. Look at > > Atlanta, which still has lots of unincorporated area. > > > > That's a big variation, and the map needs to be equally competent at > > handling both regions. > > > > Slight correction, not all land in the Northeast is incorporated. In New > > Hampshire there are a handful of communities which are not > > incorporated. > > I was exaggerating to illustrate the differences, but point taken. > > > > 2. Defining how "important" a city is (and thus, how big its label on > > the map should be) is a tricky thing to do. Population is certainly > a > > large factor, but how do you define this? The City of Atlanta is the > > #33 most populous city in the US, with 540,000 people, but the > Atlanta > > metropolitan area is #9 with 5,475,000 people and is the largest > metro > > area in 800 miles. > > > > There's also a recognition factor... the whole world knows where New > > York is and would expect it to be fairly prominent on a map. Capitol > > cities are considered to be "important" even when they're not very > > prominent or populous. Etc. > > > > It seems to me that admin_level handles the first point, except that > 4 > > levels to cover all of the US doesn't give much granularity. Maybe > we > > need to think about using the in-between levels to show more detail? > > > > place= seems to be handling the second point, but not very well. > Should > > label sizes really be determined purely by population? By > "importance"? > > What criteria should there be? I don't think the current scheme of > > city/town/whatever is very good, because it's another instance of > > hacking a British scheme onto a country with a very different history > > and organization. > > > > I agree that there isn't a one-size-fits-all approach that will work > > with displaying/tagging named communities on the map. I think that a > > combination of the size of the given area, the "admin_level" of the > > given area (country, state, county, etc), population and > > recognizability (capital cities, etc). The latter being the most > > difficult to quantify in a manner in which many people would agree on > > (less capital cities). > > I forgot to mention control cities ( > http://en.wikipedia.org/wiki/Control_city). > These are cities that are designated for use on highway signs to > indicate which direction you're heading. These should definitely appear > on the map, even if they're relatively small cities (e.g. Valdosta, > Georgia). > > > However, I agree that a ratio of area, "admin_level" and population > > could take care of most cases. > > This gets me wondering if maybe there's some way to do it more > automatically. For instance, it should be easy to find data sources > for population, area, and lists of "global cities" > (http://en.wikipedia.org/wiki/Global_city) and control cities. Maybe > there should be a process just before the renderer that takes in that > information and decides how to label cities automatically. That keeps > the OSM database down to the basics. > -- > Peter Budny \ > Georgia Tech \ > CS PhD student \ > > > If you haven't seen it, the 41Latitude blog had an earlier post about getting a good density of US city names at different zoom levels--it was in reference to Bing maps, but the same ideas apply: http://www.41latitude.com/post/931787074/improving-bing-maps-3 In his analysis, using the Census' Urban Clusters and Micropolitan Statistical Areas looked useful. Worth a read, if you're still following this thread. :)
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