Students of the Data Visualization subject at UCA are participating in the #30daymapchallenge. Each day, a map created by a different student will be published.
Day 1: Points
Author: Altagracia Villegas
Touristic places of Guatemala & Mountains of El Salvador
Data 📁: MapCruzin/GADM
Tool ⚙️: #QGIS :qgis:
I’ll attempt the #30DayMapChallenge this year! I plan to use it for the personal challenge of trying something—even if it’s a tiny something—I’ve rarely or never done before, be it a map style, a GIS function, or whatever else. Perhaps I’ll document those things at the end, but meanwhile…
For Day 1 of #30DayMapChallenge, I mapped 9 of the schools for Black children in northern Delaware when Delaware--there were more than 80 throughout the state when the state enforced racial segregation in schools. #rstats
#30DayMapChallenge Day 14: Europe. What powers Europe? A small multiples map of Europe showing the location of power plants by primary fuel. I rather like how this turned out. Tried showing all of them on one map but it got messy.
#30DayMapChallenge, Day 3: Polygons. River Basins of the Iberian Peninsula. No neon this time; feels good to be back in daylight. Faster rendering times too.
Edit: I made a mistake with the data source, it's HydroSHEDS, not OSM.
Decided to do something “simple” for today. Here is a map of all ferry routes ⛴️ in the #Philippines 🇵🇭 that have been mapped in #OpenStreetMap. Data has been extracted via #OverpassTurbo (data licensed under ODbL 1.0) and rendered via #Leaflet.
Since the Philippines is an archipelago, ferries and boats are important means of transportation especially since the thousands of small islands are too small to host airstrips.
#30DayMapChallenge Day 5: Analog map. In keeping with what has apparently become my annual craft day, here's the world as an octahedron. Last year, it was a cube, and the year before that, it was an icosahedron.
OK, made a bit more progress with the dataset I was originally interested in using for day 8️⃣ #30DayMapChallenge : all the shops mapped on #OpenStreetMap in Africa (using the Geofabrik polygon).
At around 310k shops Africa has about 22% more mapped than the UK with a population over 20x greater. Plus likely many more smaller shops & street vendors.
I've therefore used shops as a proxy for retail centres (villages/towns/cities NOT malls!). Also included a marimekko plot I made 8 yrs ago.
Antarctica for day 2️⃣ 5️⃣ of #30DayMapChallenge : a fanciful conjecture based on NISDC bedrock data. Subsidiary title should read "nor isostatic rebound nor sea level rise".
Data extracted via #OverpassTurbo and plotted using geojson.io to add some styling.
(The map is so bad that I got the “This page is slowing down Firefox. To speed up your browser, stop this page.” message. This is why you use marker clustering, or a GIS tool more suited to the job such as #QGIS or something like @felt.)
For today’s theme, here are the locations with photos of all known and extant #HistoricalMarkers (aka commemorative plaques) found in Europe that were created by the National Historical Commission of the #Philippines (#NHCP). It turns out that these are all related to our national hero José Rizal since he traveled extensively in Europe.
(I was fortunate enough to visit the 2 markers in Germany and would love to visit the rest!)
I think someone else struggled with reefs, atolls were also a real hodgepodge, so this map for day 1️⃣ 6️⃣ of #30DayMapChallenge is more useful as a guide for cleaning data up in #Oceania than anything else.
I'd love to do a legend with overlapping circles to show the size (see @seav's map today), but have no idea how to do that in #QGIS (or even what the technique is called)
Day 2 of the 2023 #30DayMapChallenge is “lines" and I got it into my head to draw paths to the closest Ookla Speedtest servers from where you were viewing the vis from.
However, the restrictive CORS setting on that API endpoint meant I had to seriously overcomplicate my solution by, um, building the vis into a self-contained #Golang binary that fires up a local web server to make what I wanted done possible.
Made with one of my most favourite #python libraries: ridge-map. Super easy to use. You can create stunning visuals with just a few lines of code. Checkout the documenation: https://pypi.org/project/ridge-map/
My first ever map for the #30DayMapChallenge: location data of 141k road traffic fatalities in Great Britain, 1979-2022. Spot the coordinate reference issues! Belated day 1: points. #geocompx
#30DayMapChallenge Day 23: 3D. Technically everything I've done so far is 3D—illuminated tubes, tiny illuminated spheres, big illuminated spheres, path traced shaded relief, 3D polygons. For unofficial #rayshader day, I decided to render the building heights of New York, New York.
“An accessibility surface visualizes travel times to a given location for each cell within a raster grid. To compute this, I use layered isochrones from Mapbox along with the fasterize package in #rstats to convert the isochrones to a smooth surface.” - Kyle Walker
The image below shows drive-times in normal traffic to Nike headquarters in Beaverton, Oregon, visualized interactively with R and Leaflet.
Kyle's R code: https://github.com/walkerke/map-challenge-2023/blob/main/scripts/day-21-raster.R #RSpatial#GIS@rstats#30DayMapChallenge