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Maps distort how we see the world

unchartedterritories.tomaspueyo.com

341–350 of 351 posts

Re: Maps distort how we see the world

#341

Earlier quoted context omitted.

This is one of those 'common misconceptions' where I hear about its refutation more often than I encounter people who believe the supposed misconception. Much like anything talking about map projections, in fact.

You may need to read more crappy fantasy books. To cite a completely representative example, consider 'High Valyrian' from Game of Thrones https://gameofthrones.fandom.com/wiki/High_Valyrian , a liturgical language that of course is contrasted with Low (or Bastard) Valyrian, a degenerate family of dialects.

I don’t doubt they exist, but the only two examples I ever hear are the GoT one you mentioned and High/Low Gothic in WH40k. But I see that factoid about High/Low German repeated multiple times a year. It was a common entry on ‘fantasy cliche’ lists even in the dial-up era of the Internet.

Re: Maps distort how we see the world

#342
post #259

Earlier quoted context omitted.

it’s a huge stretch to claim there was no bias involved. the biais is in putting europe front and center and at the top. Have you seen maps that place the americas in the center? How about maps with north and south swapped?

Actually, in China I saw a map where the cut was in the Atlantic Ocean. I am not sure how wide spread that is but I would say it makes sense for any world map used in Eastern Asia.

That is the default map in Japan, just search google images for 世界地図

Re: Maps distort how we see the world

#343
May I suggest a term for this sort of article: "mapsplaining".

I have known about the distortions of the Mercator projection since LBJ was president, and about ever ten or fifteen years someone feels compelled to announce it as news.

Re: Maps distort how we see the world

#345

Earlier quoted context omitted.

> Every flat map projection distorts something, so every projection has to optimize some parameter and trade off other utility. I'm constantly amazed at how hung up people are on apparent size of countries. If size is your thing, use some other projection! That's the point of the post. The trade-offs between different projections are rarely discussed, considered or even mentioned outside very small cohorts because th…

The faux outrage is hard to take. I grew up with the chopped up non Mercator maps and nobody cared looking at one or another. It was called out multiple times in my geography glasses in the 80s that the flat contiguous map was wrong and we spent lots of time looking at globes and North or South Pole centered maps. Nobody is being oppressed or underrepresented by this projection. This isn’t an episode of the west wing…

The idea that we're all in the dark about the real relative sizes of the countries is silly. It's not like we look at a globe and get shocked by the sizes of the countries.

Re: Maps distort how we see the world

#346
post #208

Earlier quoted context omitted.

As an adult I was shocked to find out how the projection I grew up with altered my perception of my poverty-stricken country. I had no idea for my entire life that it was so much larger than other countries on the map I thought were larger. I doubt I am rare here at all. And I have no idea what "The West Wing" is. And I doubt I am rare here at all also.

It is a TV show from 1999 that centered on the literal office of the same name that the US President holds court in.

The West Wing is not the President's office, but rather the section that contains The Oval Office, which is President's office, along with other executive offices and rooms, such as the Press Briefing room, the Situation Room, etc.

Re: Maps distort how we see the world

#347
post #3

> Countries closer to the equator—which happen to be poorer1—seem smaller than they are. Depends on the projection you use and its parameters. The "Web Mercator is racist" meme is just lazy. One way around the issue is rendering a globe on a screen. Google maps does this when you zoom out far enough. By the same token, if you're using a screen, it's possible to dynamically reproject a map based on whatever is centere…

> One way around the issue is rendering a globe on a screen. Google maps does this when you zoom out far enough. This isn't a way around the issue because the screen is two-dimensional so you are still showing a projection of the globe. I think Google uses the perspective projection when you zoom out enough.

Using a perspective projection works because our brains automatically understand the distortions caused by that sort of projection and account for them.

Reprojecting on-the-fly is a way around it. Yes, you're still projecting to two dimensions but it drives home the point that the area of a landmass is relative depending on what the user is looking at. Something like: https://observablehq.com/d/539403a9237e737d

Re: Maps distort how we see the world

#350

Earlier quoted context omitted.

The linear plot in that Wolfram link is messed up. It doesn't show all the data (caps out at 800 billion GDP). Here's a corrected linear plot, from the script that I linked (commenting out the log-log scaling): https://ibb.co/9bBgwH8 There is clearly a correlation, even on linear. It's a little messy, but it's undeniably there. The starting point for this discussion was about the relationship between a country's size…

> The result is 0.82, which indicates a strong positive correlation. datamash gave me 0.52 for Pearson. Which is "eh, maybe".

That's weird, are you looking only at the top 10 countries?

I've reproduced dwaltrib's results using World Bank data on 251 countries, and I get a Pearson's r of 0.82 and a p value of 5.6e-61 (!). I.e. a strong correlation, with high confidence. It makes sense too -- larger countries generally have more people, and more people generally generate more economic activity.

Code if you want to try yourself:

import pandas as pd

gdp = pd.read_csv("~/Downloads/API_NY.GDP.MKTP.CD_DS2_en_csv_v2_5551501.csv").set_index("Country Name")

land_area = pd.read_csv("~/Downloads/API_AG.LND.TOTL.K2_DS2_en_csv_v2_5552158.csv").set_index("Country Name")

gdp["GDP"] = gdp["2020"]

gdp["Land"] = land_area["2020"]

gdp = gdp.dropna(subset=["GDP", "Land"])

from scipy import stats

print(stats.pearsonr(gdp.Land, gdp.GDP))

#+RESULTS: : PearsonRResult(statistic=0.8151313879150333, pvalue=5.621180589722219e-61)

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