Have begun making tiny hexagons for my stupid mental health, as the meme goes. I'm really enjoying them so far.
Not sure what I'm making with these, but I think it'll be a new case for my power bank. My last one went a bit wonky in the wash because the wadding detached. Whoever made it really did not think that part through (it was me, I made it).
NOTE
1. The flood hazard data has invalid geometries/features. You can resolve this by fixing the geometries (takes a long time) or simply disabling the Invalid features filtering in QGIS processing settings.
2. Some areas have no flood hazard features. These are marked as NO DATA in the maps.
...
3. Generate centroids from the output of #2 (either using the Centroids algorithm or Geometry generators).
4. To speed up and automate the process, I created a model that runs steps 1-3 above.
5. Style the output of 3 using: marker = hexagon, size = depends on population, color = depends on hazard level (Var). Utilize data-defined overrides/Assistant.
PROCESS
1. Use the "Sort" algorithm to create an ordered version of the flood hazard layer such that the features with high hazard level (3) will always be the first feature that will be matched in #2 below.
2. Run a "Join attributes by Location" between the population hex grid layer and the sorted/ordered flood hazard layer (output of #1).
...
30 DAY MAP CHALLENGE 2024 | DAY 4 - HEXAGONS
Population ⬡ Flood Hazard
- larger hexagon = more people in the area
- redder color = higher hazard level
DATA
> Population density for 400m H3 Hexagons [Kontur] - https://data.humdata.org/dataset/kontur-population-philippines
> Flood hazard (100-year rain return) [UPRI/Project NOAH] - https://drive.google.com/drive/folders/10pCWTfU-gVuAbdx4gdUGaDcNrSzMz0Mm
Hungarian Oases.
Bivariate choropleth showing the density of natural (forrás = springs) and unnatural springs (kocsma = pubs) across Hungary.
Data from #OpenStreetMap, hexagons from #h3, plotted using #geopandas & #matplotlib
#30DayMapChallenge Day 4: #hexagons
@mdione I’ll see if I can explain why I personally like H3:
1. “Hexagons are the bestagons!” —CGP Grey
2. Icosahedral grid is based on Buckminster Fuller’s Dymaxion map, which I like.
3. H3 cells are more-or-less the same area across the globe which can’t be said for plain hex grids overlaid on non equal-area projections.
4. While H3’s levels of resolution are not 1:1 composable with adjacent levels, they did design it so that the cell vertices stay fixed.
#30DayMapChallenge Day 4 #Hexagons comes from @haavardaagesen showing the locations of geotagged Tweets from cross-border movers in Europe during 2021–2022. The data is used in the #BORDERSPACE project lead by Olle Jarv to study cross-border mobility.
Study of the mobility is crucial in the #EU as the #Schengen agreement allows for free mobility between member states resulting in little official data on the characteristics of cross-border mobility.
An imperfect loop of tiling #hexagons for #genuary10
#genuary #genuary2024 #GenArt #CreativeCoding #GenerativeArt #Processing
Altitude map of the Netherlands divided in hexagons of 2 km. The lowest hexagon has a mean altitude of 6,3 m below sea level, the highest has a mean altitude of 277,0 m above sea level. #30DayMapChallenge day 9 #hexagons #netherlands #maps #cartography
#30DayMapChallenge Day
: #Hexagons
Here is a stylized map of the former #Berlin #TegelAirport (#TXL), famous for its hexagonal architecture. This airport had been Berlin’s main airport until it was replaced by the new (and long overdue) Berlin Brandenburg Airport (BER). Coincidentally, TXL had its last commercial flight on 8 November 2020, almost exactly 3 years ago. The site was then repurposed as the Urban Tech Republic, a tech hub and startup incubator: https://urbantechrepublic.de
1/3
Taking a break from serious stuff to sketch out a game board in #RStats
⬡⬡
⬡⬡
⬡⬡