{"id":16547,"date":"2016-01-10T08:05:51","date_gmt":"2016-01-10T13:05:51","guid":{"rendered":"http:\/\/www.howderfamily.com\/blog\/?p=16547"},"modified":"2022-04-26T06:11:26","modified_gmt":"2022-04-26T11:11:26","slug":"geo-matryoshka-state","status":"publish","type":"post","link":"https:\/\/www.howderfamily.com\/blog\/geo-matryoshka-state\/","title":{"rendered":"Geographic Matryoshka with US States"},"content":{"rendered":"\n

A challenge resulted from the recent Outside of California<\/a> article, in a comment by loyal reader Rhodent. However, I have to say that I spent way more time than I’d care to admit seeking an optimal solution. Readers who relish a good mental challenge will probably enjoy trying to improve upon my results. Others will hopefully at least appreciate the obsessive-compulsive effort I endured.<\/p>\n\n\n\n

\"Matryoshkas.<\/a>
Matryoshka — Russian Nesting Dolls<\/figcaption><\/figure>\n\n\n\n

I’ll go ahead and let Rhodent explain the challenge. One can also view the full comment<\/a> in its original context if this snippet doesn’t provide enough information. Per Rhodent;<\/p>\n\n\n\n

“I made some GeoGuessr<\/a> puzzles where the theme was places with this sort of name. I would string them together into what I called ‘Geographic Matryoshkas’, although I didn\u2019t stick to the idea that the city name had to be the name of another state… Maryland (neighborhood), London; London, Ontario; Ontario, New York; New York, Texas; Texas, Queensland… I\u2019d be curious to know what would the longest string one could come up with if one did restrict it to using cities whose names were that of American states.”<\/p><\/blockquote>\n\n\n\n

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OK, Challenge Accepted<\/h2>\n\n\n\n

So I undertook a brute force method. I searched for every state name found in another state in the U.S. Geological Survey’s Geographic Names Information System<\/a> that fell within feature classes “Civil” and “Populated Place”. This partitioned options to places where people likely lived, i.e., “A political division formed for administrative purposes (borough, county, incorporated place, municipio, parish, town, township)<\/em>” or a “Place or area with clustered or scattered buildings and a permanent human population (city, settlement, town, village)<\/em>.”<\/p>\n\n\n\n

Thus I eliminated topographic features like rivers, mountains, forests and such. Some of the resulting locations may have been tiny or insignificant, and that was fine, I simply wanted to make sure they all came from an authoritative source. If it was good enough for the USGS then it was good enough for me. I called the resulting places “towns” even though some were counties, villages, etc., just to keep things as simple as possible.<\/p>\n\n\n\n

Additionally I eliminated all partial matches. As an example, the result had to be New York exactly and not simply York. And yes, six different states actually had towns named New York, which certainly surprised me.<\/p>\n\n\n\n

Then I eliminated over-matches so the town named Kansas in Alabama was acceptable while Kansas City in Missouri and its half million residents fell to the cutting room floor. I know! How arbitrary! I wanted to keep the game as pure as possible. That still left 299 state-named towns even after strictly applying the rules, leaving a manageable number of options in my opinion.<\/p>\n\n\n\n

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Everything went into a Google Docs spreadsheet<\/h2>\n\n\n\n