u/chillchamp

Construction was finished 3 days ago.

I posted an ice age map recently and people pointed out a few weaknesses in the data I used. I tried to fix that. I also added biome data (so fascinating), glaciers on top of the Alps and tried to find better data sources for the ice sheets. If you see any inacuracies please let me know. Details in the comments.

Check out the interactive map: chillchamp1.github.io/lab/eiszeit-europa

Europe from 24,100 BC to today. The crust sags under the ice and rebounds after it, and the sea drops 130 m as the water is locked up 

Lambert azimuthal equal-area, 4,500 × 5,250 km. Modern terrain plus the modelled crustal difference — so these are today's mountains at their ice-age elevation, not the landforms of the time. Ice thickness in ICE-6G_C carries ±20–30% uncertainty, and the build-up before 25 ka is far more weakly dated than the retreat.

Interactive version, with the dated ice margins and their uncertaintyband: https://chillchamp1.github.io/lab/eiszeit-europa/

Sources: Ice and crust ICE-6G_C (Peltier et al. 2015) margins DATED-1 (Hughes et al. 2016) terrain ETOPO 2022

This animation is half real map, half cartogram: Cities get drawn wider than they really are.  Every district is one flat block of data, so the round hills are just smoothing. 

Height is people per area, so a mountain's volume is the actual number of people in it.

Blue is below half the national average of 2024. The population data is interpolated between censuses - More a portrait than a measurement.

https://chillchamp1.github.io/lab/bevoelkerung-kreise/

The United Nations General Assembly voted to endorse the Equal Earth projection as the recommended map layout for educational materials, public communications, and data reporting where accurate relative land sizes matter.

In this animation I compare the Mercator projection with the Equal Earth projection. I also added a globe for comparison.

Check out the webapp it's interactive.

https://chillchamp1.github.io/lab/weltkarte-projektionen/

Election maps flatter empty land. This animation reweights Germany's 2025 federal election so every person gets the same area. Colour shows the party with the most votes in each area. 

Data: election-night dataset compiled by Zeit Online (GitHub: ZeitOnline/bundestagswahl-2025-gemeindeverbands-daten, 25 Feb 2025

Note that on this map time of day and date move on different clocks.

If you want to explore this map further: https://chillchamp1.github.io/Animal-movement/rings.html

22 of them died on the way 😟 I added little crosses so you can see where.

https://chillchamp1.github.io/Animal-movement/

Data: Flack et al. 2016, Movebank Data Repository doi:10.5441/001/1.78152p3q (CC0). Basemap: Terrain Tiles on AWS Open Data + ESA WorldCover 2021.

I also made an open source web app where you can explore all of it (and some more) on your own: https://chillchamp1.github.io/github.io/#eu

Interactive version and more info on my Github: https://chillchamp1.github.io/github.io/

Source of the train departures: DELFI e.V.

I made an extremely experimental visualization of the HDI-development betwen 1990 and 2023 in the US and Cannada. I made something similar for Europe yesterday and tried to improve based on the criticism. I left out Mexico because its HDI is much lower so there would be less visual distinction between the US and Cannadian regions. Let me know If you are interested in other regions or comparisons it should be relatively little effort now that I have everything up and running.

Data source: Global Data Lab – Subnational Human Development Index, values export from globaldatalab.org (as of 2023). Region boundaries: GDL Shapefiles v6.4 (PRIO). 

This map shows changes in HDI compared to the European average. This is an experimental type of visualization let me know what you think.

Data source: Global Data Lab – Subnational Human Development Index, values export from globaldatalab.org (as of 2023, methodology per Smits & Permanyer 2019). Region boundaries: GDL Shapefiles v6.4 (PRIO).

I recently made a prototype for a Sashiko pattern library. It shows animations instead of stitching diagrams and people seemed to really like it. So I put in some more work, polished it and added a few features (ie. colors) that are hopefully useful to the community.

This library will be free and open source forever.

Everyone can participate by creating new patterns in the sandbox. These I will add to the main gallery over time. I recommend the remix feature in the existing patterns to get a hang of how the editor works.

If you wish for new features or find bugs, please let me know here. I appreciate people helping me to add patterns, this way the library will grow quicker. Let me know what you think :-)

https://sashikolib.org/

I made this raised bed for my mom. I totally underestimated how much mortar these joints would take (over 100kg/200 lbs).

There are probably 30-40 wheelbarrows of grass clippings and leafs inside of this monstrosity but it was fun to make :)

You may have to download the map to see it in high res.

Climate change will heavyly damage our cities because of extreme weather events. I created a map shows areas at risk in the German capital of Berlin which used to be a swamp mostly.

Water Bodies (Blue): Rivers, Lakes and canals sourced from the Berlin Water Map (Gewaesserkarte).

Heavy Rain Depressions (Purple): These indicate topographical sinks at risk during extreme weather events (Starkregenhinweiskarte).