Based on data from GovTrack, this map displays the ideological leanings of current (at the time) members of the U.S. House of Representatives by their district. “The data is based of numbers from 0-1. If the congressman is a 0 he is the most liberal in the House. If a congressman is at 1 then he is the most conservative. If the congressman is a 0.5 they are centrist. […] The most conservative congressman is Jeff Duncan, a Republican from South Carolina’s 3rd District. The most liberal congressman is Barbara Lee, a Democrat from California’s 13th District.”
President Trump’s proposed budget would end funding for Amtrak’s long-distance passenger routes, leaving only the Northeast Corridor and state-funded lines. Maps of the lines that would be closed share the problems of Amtrak network maps in general. Take USA Today’s map from its 12 April article on the subject:
Like electoral maps that make large, less-populated areas look more important than densely populated areas, this map is somewhat deceptive: it distorts the extent of the cutbacks because it shows lines rather than trains. There are, for example, a lot more trains in the Northeast Corridor than run between Chicago and the Pacific Northwest (the daily Empire Builder). State-run services tend to have lots of lines and trains over short distances that are too small to see clearly on this map. Adding connecting services (which are usually bus routes) adds even more detail, and clutter, to a small map.
Cameron Booth, for his part, visualizes the proposed cuts by starting with his Amtrak Subway Map and greying out the lines that would be cut. This doesn’t solve the number-of-trains problem, but it does provide a clearer sense of what’s happening to the network.
Proposed budget could eliminate 15 long-distance Amtrak trains, which would leave the notionally "national" rail network looking like this: pic.twitter.com/OkBTsz8hCg
— Transit Maps (@transitmap) April 15, 2017
Previously: Cameron Booth’s Amtrak Subway Map.
President Trump’s budget proposes eliminating the EPA’s Great Lakes Restoration Initiative. That fact is no doubt what’s behind two publications posting maps earlier this month, only a couple of days apart, showing the environmental stresses on the Great Lakes basin.
Canadian Geographic reposted a map from their July/August 2013 issue:
And the Washington Post included the following map in an article on the proposed elimination of two EPA programs (including the aforementioned Great Lakes Restoration Initiative):
On a recent episode of the PBS version of the Antiques Roadshow, Chris Lane appraised a copy of the 1833 Churchman Eagle Map of the United States at $25,000. On the Antiques Print Blog Lane explains how he arrived at that number, which some have thought was a bit on the high side. [WMS]
ProPublica is tracking—and mapping—bomb threats against Jewish organizations and community centers in the United States. As of this moment, there have been 133 threats against 99 locations since January 1st.
In response to measures like North Carolina’s House Bill 2, which restricts access to public washrooms by transgender people, crowdsourced online maps of safe washrooms—places with unisex or gender-neutral washrooms, or that let transgender people use the washroom that matches their gender identity—have been created: Refuge Restrooms has both a list and a map view; Safe Bathrooms uses Google My Maps. These maps seem like the modern-day equivalent of The Negro Motorist Green Book for trans people. [WMS]
The Washington Post maps the parts of the United States most dependent on trade—and thus most at risk if the Trump administration starts a trade war with the U.S.’s trading partners.
50 Fantasy States is Chris Engelsma’s ongoing project to create fantasy-style maps of all 50 U.S. states. Six have been completed so far, including the above fantasy map of Alaska.
Last month the New York Times mapped the U.S. cultural divide by looking at television viewing preferences. More precisely, the geographic distribution of viewership for the 50 most-liked TV shows. The correlation between Duck Dynasty fandom and voting for Trump was higher than for any other show. More surprisingly, the show most correlated with voting for Clinton? Family Guy.
Writing for the Portland Press-Herald, Colin Woodard compares the 2016 presidential election results to the eleven regional cultures he sets out in his 2011 book, American Nations. “The bottom line: the 2016 presidential election results exhibited the same regional patterning we’ve seen in virtually all competitive contests in our history, including those in 2008 and 2012. But by running on an unconventional platform, Donald Trump was able to erode his rival’s margins in certain nations.” He did better enough in rural Yankeedom and the Midlands to deny Clinton the victory in states she could not afford to lose. With plenty of maps to show the swing from the 2008 and 2012 votes. [Cartophilia]
Previously: Electoral Map What-Ifs.
Neil Freeman’s Random States of America creates election maps from an alternate reality. They apply real-world election results to randomly generated state boundaries, which can yield radically different results than what actually happened.
Taking things one step further, Josh Wallaert of Places asked Freeman “to calculate who would win the 2016 election if the states were redrawn under plausible scenarios.” The result is a collection of electoral might-have-beens based on familiar scenarios: Pearcy’s 38 states, Freeman’s 50 states with equal population, even the megaregions based on commuter data we saw earlier this month. Each map demonstrates that, under the U.S. system, who wins depends on where you draw the borders.
Like The United Swears of America, The Great American Word Mapper explores regional variation in English language use in the United States based on geocoded Twitter data, this time through a search interface that allows side-by-side comparisons. As before, forensic linguist Jack Grieve is involved, along with fellow linguist Andrea Nini. [Kottke]
While the map shows the historical probability that a snow depth of at least one inch will be observed on December 25, the actual conditions in any year may vary widely from these because the weather patterns present will determine the snow on the ground or snowfall on Christmas day. These probabilities are useful as a guide only to show where snow on the ground is more likely.
While the subject may seem whimsical, it’s based on 1981-2010 Climate Normals data; this paper details into the methodology involved. (It also answers a question that climatologists and meterologists get a lot.)
In a paper published in PLOS One, Garrett Dash Nelson and Alasdair Rae explore whether megaregions—i.e., a region centred on a major metropolitan area—can be determined algorithmically, using commuter flow data. In the end they conclude that “any division of space into unit areas will have to take into account a ‘common sense’ interpretation of the validity and cohesion of the regions resulting from an algorithmic approach. For this reason, the visual heuristic method coupled with the algorithmic method offers a good combination of human interpretation and statistical precision.” In the process, they’ve generated a series of maps that are fascinating on several levels, including a final map of megaregions that combines algorithmic results with visual heuristics (i.e., human judgment). [Atlas Obscura]