austromorph

putting Austria into perspective | by @chrxf and @metropop_eu

[austromorph @austromorph]

Territory vs population:
Two geographies of the Austrian election results #bpw16

More maps: https://t.co/HSVZ8SLcK3

[Flooh Perlot @drawingdata]

Ich hätt ja noch eine andere Karte zu den Klimabonus-Klassen überlegt, da mE ein gutes Beispiel zum Thema Bevölkerung und Landkarten (von der Farbwahl nicht zu sprechen), aber ok, war die Innenpolitik halt schneller. Anyhow:

[austrianmaps @austrianmaps]

Communism in Austria – a cartogram

[austromorph @austromorph]

@bricker @GeoInfoNL Thanks for sharing! Even though you found tile maps have (even) stronger emotive properties, we still 💖 cartograms. With our @qgis plugin it’s super easy to create them: https://t.co/umpxLozvX8

[austromorph @austromorph]

@ArminWolf Und so sah die politische Landkarte der Gemeinden Österreichs 2016 gewichtet nach Bevölkerung (Anzahl der Wahlberechtigten) aus.

online map #bpw16 ➡️ https://t.co/acZsKq42vp

[tinafrank @tinafrank]

Vienna elections 2020 vs 2015.
city council and district council results – district by district

[ramon bauer @metropop_eu]

Changes in the political landscape of #Vienna: 2015 and 2020 elections – district by district.

#wien2015 vs #wien2020
winning party plus 2nd place
city council ⬅️🗳️➡️ district council

[tinafrank @tinafrank]

I made some fresh Vienna election maps with @metropop_eu

[Flooh Perlot @drawingdata]

#30DayMapChallenge Day 29: Experimental

Experimenting what different projections from the https://t.co/hbOHn9krAX package do to a simple map of Austria (without any adjustments)

[Flooh Perlot @drawingdata]

How big is the Austria city of Graz when it comes to regional elections (that happen to be today)? Find out yourself: https://t.co/wFJRuQfWcr

#30DayMapChallenge Day 23: population.

Thx @metropop_eu for the tip

[data.gv.at @datagvat]

New #nrw19 visualization "2019 Austrian General Election Results" by @austromorph - using #opendata from @BMI_OE and @STATISTIK_AT https://t.co/iFL9gD1R2A

[austromorph @austromorph]

@datagvat 1000Dank für die Bereitstellung der Daten. Die Visualisierung haben wir eingereicht.

[austromorph @austromorph]

Final results of the 2019 Austrian General Election at the scale of municipalities (and districts of Vienna) – re-sized by number of eligible voters >> https://t.co/fdr4Jh1V3i

#nrw19

[austromorph @austromorph]

Territory vs electorate:
Two geographies of the 2019 Austrian General Election results #nrw19

more #austromorph maps > https://t.co/AVf5zNWRAw

[austromorph @austromorph]

#Austria's updated political landscape #nrw19

Preliminary 2019 General Election results (w/o postal votes) – mapped by municipalities, re-sized by electorate > https://t.co/lZ4LBjnFj3

[austromorph @austromorph]

@chrxf @metropop_eu @tinafrank thx @datagvat for providing #opendata #nrw19 election results > https://t.co/wpkzNO1FdO

[austromorph @austromorph]

#Austria's updated political landscape #nrw19

Preliminary 2019 General Election results (w/o postal votes) – mapped by municipalities, re-sized by electorate > https://t.co/lZ4LBjnFj3

[austromorph @austromorph]

Great to see our #austromorph cartogram in the current issue of @archplusnet accompanying Andreas Rumpfhuber’s analysis of spatial representation and structures of the populist right in #Austria

[Topi Tjukanov @tjukanov]

Visualizing Finnish elections [thread]

1/n: Finnish population cartogram showing the most popular party in each municipality.

#vaalit2019

[ramon bauer @metropop_eu]

Global population cartogram from 1916 by LG Curtis highlighting the British and Chinese Empire.

The author emphasises that "the collapse of the British Empire (...) would convulse the whole fabric of human society." https://t.co/OMhlef338e | via @philip_thai @baskerhel

[Topi Tjukanov @tjukanov]

Persons with higher education qualifications, aged 15+, as % of total population of same age.

First on a normal coropleth map and then on a population cartogram. Neither of them is optimal to deliver the message on their own, but an animation is quite helpful.

Data: @THLorg