#30daymapchallenge — Public Fediverse posts

@joeldn this is a bit sketchy but there are a couple of examples here:

https://fosstodon.org/@wnd/115484726949074623

(There are bunch more of these at different scale which I should publish in a more structured way.

Also, if you are interested in such things here are some other things in my #Shed for the #30DayMapChallenge
https://anisotropi4.github.io/shed/30daymapchallenge.html)

@bovine3dom

#30DayMapChallenge Day 24: Places and their names. Here is another edition extended to the keld, kirk, thwaite and toft elements. #placenames #OldNorse @histodons

#30DayMapChallenge Day 24: Places and their names. Here is the same idea expanded to mostly England. I don't have the data, but I would be delighted to see a #Scandinavian or #Baltic friend extend the idea further...

Pour clôre le #30DayMapChallenge, retour aux îles Kerguelen avec une carte qui célèbre... les sciences géographiques !

📍 Trouée de la Boussole, Mont du Théodolite et de l'Alidade, Vallée de l'Octant ...et même la presqu'île de la Société de Géographie.

#30daymapchallenge – J30 #Makeover
✍️ Benjamin SAGLIO / Pierre PHILIPPE
📊 Carte IGN de 1972

For the thirtieth* #30MapsInAMonth are maps showing the electrification of the global heavy-rail network based on the track-model and electrification and electrification tags from @openstreetmap

An electric railway is the least carbon-intensive way of moving freight and passengers over long distances**. More so where the electricity generation is from renewable sources.

* and final
** words chosen more carefully

#Decarbonization #Electrification #OpenData #30dayMapChallenge #PublicTransport

For the twenty ninth #30MapsInAMonth are two visualisations based on the @WorldPopProject 2030 projected population as 100m² raster data. The first shows the population of the Islands of Northern Europe and the second population change.

1/n

#Raster #Population #Beethoven #GBR #IRE #OpenData #30dayMapChallenge

#𝟯𝟬𝗗𝗮𝘆𝗠𝗮𝗽𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 - 𝗗𝗮𝘆 𝟮𝟵: 𝗥𝗮𝘀𝘁𝗲𝗿
𝘖𝘚𝘔-𝘣𝘢𝘴𝘦𝘥 𝘓𝘜𝘓𝘊 𝘮𝘢𝘱 of 𝘒𝘢𝘳𝘭𝘴𝘳𝘶𝘩𝘦, 𝘎𝘦𝘳𝘮𝘢𝘯𝘺 2021🛰️🗺️

Satellite imagery shows how our landscapes evolve. In the LaVerDi project, HeiGIT and @BKG combine OSM data with Copernicus Sentinel-2 imagery to make land-use and land-cover monitoring across Germany more precise and responsive.

🔍 More about LaVerDi: https://heigit.org/laverdi/

#OpenStreetMap #OpenData #LULC #Karlsruhe

#30DayMapChallenge Day 28: Black

On this Black Friday, I found today’s theme in the depths of the Black Sea 🌊.

Using the OpenTopography DEM Downloader, I grabbed the Global Bathymetry SRTM15+ V2.1 dataset, calculated 100 m contours, and applied the Tanaka method with a style from the QGIS Hub plugin. 🎨

#QGIS #Cartography #OpenData #Bathymetry #BlackSea #GIS #Mapping

For the twenty eighth #30MapsInAMonth are two visualisations based on the UK National Atmospheric Emissions Inventory (NAEI) https://naei.energysecurity.gov.uk/ showing total and transport air pollution and emissions.

#AirPollution #Emissions #OpenData #30dayMapChallenge

For the twenty seventh #30MapsInAMonth is an animation showing the organisational operational boundaries boundaries of Network Rail using FOI data in a jazzy shaded colour scheme. This shows region, route, maintenance delivery unit and TME*.

* if truth be told, I don't know what a TME is...

#Infrastructure #RailOperations #30dayMapChallenge

For the twenty sixth #30MapsInAMonth is a visualisation using the Office of Rail and Road (ORR) Financial Year 2018/19 to 2023/24 passenger travel data projected onto a Network Rail shortest-path network using the centre-line track-model to create visualisation for passenger journey numbers for the active rail stations across the British rail network.

1/n

#Passenger #Rail #ReproducibleCode #30dayMapChallenge

For the twenty fifth #30MapsInAMonth are a series of four maps showing @WorldPopProject 1km² population data aggregated into a hierarchical set of scaled hexagons.

1/n

#Population #Hexagon #30dayMapChallenge

For the twenty third #30MapsInAMonth here is a map that shows the stations where the aggregated number of people living within the shortest walking distance to a heavy rail station is greater that 50k. The station name is scaled based on this aggregated number.

1/n

#Passenger #Rail #ShortestTravel #Station #30dayMapChallenge

#30DayMapChallenge, day 23: Process Flow directions in the French Alpes with a 5 m RGEALTI DTM (IGN France). Using #QGIS’s new native Fill Sinks (Wang & Liu), I calculated flow directions, converted them to a mesh via #Crayfish, styled with arrows, and visualised in #3D.   🎥 youtu.be/ttLxQBe0HIo

Calculate Flow Direction with ...

#30DayMapChallenge, day 23: Process Flow directions in the French Alpes with a 5 m RGEALTI DTM (IGN France). Using #QGIS’s new native Fill Sinks (Wang & Liu), I calculated flow directions, converted them to a mesh via #Crayfish, styled with arrows, and visualised in #3D.   🎥 youtu.be/ttLxQBe0HIo

Calculate Flow Direction with ...

#30DayMapChallenge, day 23: Process
Exploring flow directions in the French Alpes with a 5 m RGEALTI DTM (IGN France). Using #QGIS’s new native Fill Sinks (Wang & Liu), I calculated flow directions, converted them to a GRIB mesh via #Crayfish, styled with arrows, and finally visualised the results in #3D. 🎥 https://youtu.be/ttLxQBe0HIo

#30DayMapChallenge, day 23: Process
Exploring flow directions in the French Alpes with a 5 m RGEALTI DTM (IGN France). Using #QGIS’s new native Fill Sinks (Wang & Liu), I calculated flow directions, converted them to a GRIB mesh via #Crayfish, styled with arrows, and finally visualised the results in #3D. 🎥 https://youtu.be/ttLxQBe0HIo

#30DayMapChallenge, day 23: Process
Exploring flow directions in the French Alpes with a 5 m RGEALTI DTM (IGN France). Using #QGIS’s new native Fill Sinks (Wang & Liu), I calculated flow directions, converted them to a GRIB mesh via #Crayfish, styled with arrows, and finally visualised the results in #3D. 🎥 https://youtu.be/ttLxQBe0HIo

#30DayMapChallenge, day 23: Process
Exploring flow directions in the French Alpes with a 5 m RGEALTI DTM (IGN France). Using #QGIS’s new native Fill Sinks (Wang & Liu), I calculated flow directions, converted them to a GRIB mesh via #Crayfish, styled with arrows, and finally visualised the results in #3D. 🎥 https://youtu.be/ttLxQBe0HIo

Day 21 #30DayMapChallenge - Football icons of Birmingham Reworked a map from earlier in the challenge to help viewers understand just how iconic a football Birmingham City are... #rstats #dataviz #bcfc #kro

For the twenty fourth #30MapsInAMonth here is are two talks about the intent and give some details as to how a number of visualisations were made.

Here are #OpenData resources https://anisotropi4.github.io/shed/opendata.html used in these visualisations

The first is a Leeds Digital festival talk about a fully automated European luxury high-speed railway https://youtu.be/xFLuUO3YBBE

The second is about visualisation of Office of Rail and Road data https://youtu.be/CZm-6ahj1TU

#WhyDoIMakeMaps #30dayMapChallenge

For the twenty third #30MapsInAMonth here is are two talks about the intent and give some details as to how a number of visualisations were made.

The first is a Leeds Digital festival talk about a fully automated European luxury high-speed railway https://youtu.be/xFLuUO3YBBE

The second is about visualisation of Office of Rail and Road data https://youtu.be/CZm-6ahj1TU

Here are #OpenData resources https://anisotropi4.github.io/shed/opendata.html used in these visualisations.

#WhyDoIMakeMaps #30dayMapChallenge

For the twenty second #30MapsInAMonth are three maps showing Natural earth data https://www.naturalearthdata.com/.

The first map show the 10m urban layer for the low countries, the second two the Islands and Northern Island and Europe with heavy rail lines.

#NaturalEarthData #Europe #Population #OpenData #30dayMapChallenge

For the twenty first #30MapsInAMonth are two maps showing concerts played by the experimental music group Einstürzende Neubauten using the band icon.

The two maps show all concerts in European and the world and is based on geolocation using data from https://www.fromthearchives.com/en/chronology1.html.

"You will find me if you want me in the garden, unless it's pouring down with rain."

#EinstürzendeNeubauten #TheGarden #Europe #WorldMap #OpenData #30dayMapChallenge

Day 20 of #30DayMapChallenge: Water 🌊
Here’s the Mediterranean Sea in stunning detail using the ETOPO1 global relief model — deep trenches, shallow shelves, and surrounding terrain all in one map.

R + terra + ggplot2 💙

#RStats #GIS #Bathymetry #Mediterranean #DataViz #Geospatial

For the twentieth #30MapsInAMonth are a set of map using @openstreetmap and @ordnancesurvey Survey to look at rivers and streams in the Islands of Northern Europe.

These three maps show difference scales and how different tags affect the maps.

#water #rivers #WorldMap #OpenData #30dayMapChallenge

⭐ Et si on représentait la Terre autrement ? En 1879, Hermann Berghaus a proposé une projection en étoile utilisant une projection azimutale équidistante pour l'hémisphère dont la projection est le centre.

#30DayMapChallenge – J19 #Projections
✍️ Pierre Philippe
📊 Natural Earth

Découvrir les cartes de nos agents : https://www.ign.fr/mag/30DayMapChallenge-30-jours-30-cartes-pour-celebrer-la-creativite-cartographique

For the nineteenth #30MapsInAMonth are a set of map using different coordinate system projections of Natural Earth railway data https://www.naturalearthdata.com/

The four maps represent points on the oblate-spheroid that is the Earth on a surface. The first uses latitude and longitude in °, the rest are in meters. The second is commonly used on the web, the third a projection for Europe and the final is the UK Ordnance Survey map projection.

#rail #WorldMap #NaturalEarth #Coordinates #30dayMapChallenge

#30DayMapChallenge Day 19: #Projections 🍊🌍 Ever tried peeling an orange and laying it flat? It cracks apart, just like the Earth when we project it onto a map. World map out of orange peel, styled in a polar stereographic projection. Made in #QGIS with #NaturalEarth data.

#30DayMapChallenge Day 19: Projections 🍊🌍

Ever tried peeling an orange and laying it flat? It cracks apart, just like the Earth when we project it onto a map.

So today I made a world map out of orange peel, styled in a polar stereographic projection. Made in #QGIS with #NaturalEarth data.

#Cartography #GIS #MapProjections #DataViz

For the eighteenth #30MapsInAMonth are a set of four animated simulations of a three body solar system. Where the mass of the two planetary bodies and the initial offset angle is varied, and correspond to the three numbers at the top of the simulation.

This was inspired by my daughter's final year degree project and, although rare, shows how you can have some things go spectacularly wrong sometimes, or not.

#Space #Modelling #Chaos #python #30dayMapChallenge

Day 17 of the #30DayMapChallenge: tried Felt.com for today’s “New Tool” theme.
Climate Change Data - Yearly AVG Temp at Weather Stations.

#30DayMapChallenge #Day17 #NewTool #FeltMap

For the seventeenth #30MapsInAMonth are four maps revising rail electrification using Vega-lite https://vega.github.io/vega-lite/, a tool I had never used before the weekend.

As before, this uses tagged @openstreetmap railway data, but this uses a topological (TopoJSON) version, which can then be quantised to give different levels of granularity.

1/n

#Rail #Electrification #PublicTransport #Vega-lite #GreatBritain #OpenData #30dayMapChallenge

For the sixteeth #30MapsInAMonth are two map showing the watershed shortest walking route to the heavy rail stations in Britian. This uses @openstreetmap highway, road and path data for routing, scaled to show the number people who might take that path.

The first shows routes based on @WorldPopProject 1km² data
The second shows routes based on data from the UK #Census2021

#Rail #Passenger #PublicTransport #GreatBritain #OpenData #30dayMapChallenge

For the fifteenth #30MapsInAMonth are two sets of map for electrical power transmission mostly on the Islands of Northern Europe.

Based on OpenStreetMap, the first set show the high-voltage transmission cables and lines, and then second of these with wind-turbines.

The second set shows #OpenData from @nationalgriduk and Scottish and Southern Electricity Networks (SSEN) data. 1/n

#electricity #transmission #generation #Ireland #GreatBritain #30dayMapChallenge

#30DayMapChallenge : #Fire

The #Volcanic Isles . A brief history of volcanism across The British Isles.

Quite pleased with how this one turned out.

Location of volcanoes taken from wikipedia (spotted a mistake and got to make an edit to wikipedia in the process); fault lines from the #BGS 625k bedrock dataset and the IE GSI 500k Bedrock Geology for Ireland. Font: League-Spartan by the League of Moveable Type.

#requests, #pandas and #geopandas for scraping and wrangling.#scipy for making the proximity surface (that's the colour scheme), #matplotlib for plotting. With all labeling done manually in #inkscape.

EDIT: I've been kindly and helpfully informed that (a) Ben Nevis' age is closer to 399 Ma; (b) some are missing; (c) others perhaps shouldn't be there; (d) it's complicated. So, maybe don't use this map to make any strategic decisions.

#volcanism #volcano #imNotExtinctImDormant #magma #geology #faultlines

#30DayMapChallenge : #Fire

The #Volcanic Isles . A brief history of volcanism across The British Isles.

Quite pleased with how this one turned out.

Location of volcanoes taken from wikipedia (spotted a mistake and got to make an edit to wikipedia in the process); fault lines from the #BGS 625k bedrock dataset and the IE GSI 500k Bedrock Geology for Ireland. Font: League-Spartan by the League of Moveable Type.

#requests, #pandas and #geopandas for scraping and wrangling.#scipy for making the proximity surface (that's the colour scheme), #matplotlib for plotting. With all labeling done manually in #inkscape.

EDIT: I've been kindly and helpfully informed that (a) Ben Nevis' age is closer to 399 Ma; (b) some are missing; (c) others perhaps shouldn't be there; (d) it's complicated. So, maybe don't use this map to make any strategic decisions.

#volcanism #volcano #imNotExtinctImDormant #magma #geology #faultlines

#30DayMapChallenge : #Fire

The #Volcanic Isles . A brief history of volcanism across The British Isles.

Quite pleased with how this one turned out.

Location of volcanoes taken from wikipedia (spotted a mistake and got to make an edit to wikipedia in the process); fault lines from the #BGS 625k bedrock dataset and the IE GSI 500k Bedrock Geology for Ireland. Font: League-Spartan by the League of Moveable Type.

#requests, #pandas and #geopandas for scraping and wrangling.#scipy for making the proximity surface (that's the colour scheme), #matplotlib for plotting. With all labeling done manually in #inkscape.

EDIT: I've been kindly and helpfully informed that (a) Ben Nevis' age is closer to 399 Ma; (b) some are missing; (c) others perhaps shouldn't be there; (d) it's complicated. So, maybe don't use this map to make any strategic decisions.

#volcanism #volcano #imNotExtinctImDormant #magma #geology #faultlines

#30DayMapChallenge : #Fire

The #Volcanic Isles . A brief history of volcanism across The British Isles.

Quite pleased with how this one turned out.

Location of volcanoes taken from wikipedia (spotted a mistake and got to make an edit to wikipedia in the process); fault lines from the #BGS 625k bedrock dataset and the IE GSI 500k Bedrock Geology for Ireland. Font: League-Spartan by the League of Moveable Type.

#requests, #pandas and #geopandas for scraping and wrangling.#scipy for making the proximity surface (that's the colour scheme), #matplotlib for plotting. With all labeling done manually in #inkscape.

EDIT: I've been kindly and helpfully informed that (a) Ben Nevis' age is closer to 399 Ma; (b) some are missing; (c) others perhaps shouldn't be there; (d) it's complicated. So, maybe don't use this map to make any strategic decisions.

#volcanism #volcano #imNotExtinctImDormant #magma #geology #faultlines

#30DayMapChallenge : #Fire

The #Volcanic Isles . A brief history of volcanism across The British Isles.

Quite pleased with how this one turned out.

Location of volcanoes taken from wikipedia (spotted a mistake and got to make an edit to wikipedia in the process); fault lines from the #BGS 625k bedrock dataset and the IE GSI 500k Bedrock Geology for Ireland. Font: League-Spartan by the League of Moveable Type.

#requests, #pandas and #geopandas for scraping and wrangling.#scipy for making the proximity surface (that's the colour scheme), #matplotlib for plotting. With all labeling done manually in #inkscape.

#volcanism #volcano #imNotExtinctImDormant #magma #geology #faultlines

#30DayMapChallenge Day 15: Fire 🔥 Mapped the density of fire stations in the Netherlands using #QGIS. #OpenData from #OpenStreetMap via QuickOSM plugin. Styled with #heatmap renderer. Fire service zones from @[email protected] via #PDOK Services plugin.

#30DayMapChallenge Day 15: Fire 🔥 Mapped the density of fire stations in the Netherlands using #QGIS. #OpenData from #OpenStreetMap via QuickOSM. Styled with #heatmap renderer. Fire service zones from @CBSstatistiek via #PDOK Services plugin.

#30DayMapChallenge – Day 13: 10 minute map Map of the #Mara River Basin made in #QGIS with #HydroSHEDS #opendata and @maptiler.bsky.social #vectortiles. 🎥 Try it for your own catchment: youtu.be/hUgEYKz87gw

#30DayMapChallenge – Day 13: 10 minute map

Map of the #Mara River Basin made in #QGIS with #HydroSHEDS #opendata and @maptiler.bsky.social #vectortiles.

🎥 Try it for your own catchment: https://youtu.be/hUgEYKz87gw

For the thirteenth #30MapsInAMonth are two short form maps based on Tom Forth's https://www.tomforth.co.uk/circlepopulations/ tool that shows the population within a 100km radius circle of two points in the UK: a point in the North is 20 141 911 and West London is 22 625 112. This is based on @opendatabund Street Map data and @CopernicusEU EU Global Human Settlement (GHS) layer centre data.

#Population #UK #OpenData #30dayMapChallenge #NorthSouth

For the twelfth #30MapsInAMonth is a theoretical future public transport network for a hundred years hence. This is based on population density aggregating @WorldPopProject population data onto 43km edge-length hexagons, creating a network flow and overlaying with @CopernicusEU urban centre data. The different population centre colours related to different levels of urbanisation.

#OpenData #30dayMapChallenge #population #PublicTransport #passenger #future

For the eleventh #30MapsInAMonth is an animated map of the British rail network showing track occupancy count for passenger train services in hour slices for the week of 18 August 2025.

This is based on the Network Rail centre-line track- or network-model and Common Interface File (CIF) format timetable file published on the Rail Data Marketplace combined with ORR and @openstreetmap location data for timetable points.

#OpenData #30dayMapChallenge #timetable #rail #passenger

#Day07 of #30DayMapChallenge on Accessibility This map shows the time needed to cycle from Bains des Paquis (a popular fondue and sauna place in Geneva) 🆕 1st time use of the `osmr` package to define #isochrones. Gallery: guillaume-noblet.com/30DayMapChal... #dataviz #rstats #ggplot2 #gis #map

#30DayMapChallenge Day 10: Air 🌪️ Animated mesh layers of #hurricane tracks resembling Vincent van Gogh’s Starry Night. #HurricaneMelissa #Jamaica. Made with #QGIS. Data from #Copernicus #ECMWF

🌬️ Day 10 – Air
For #30DayMapChallenge I explored average monthly wind speed using WorldClim data.
Each frame shows mean wind speed (m/s) around the world — from calm zones to powerful currents.

🗺️ Animated in #RStats with terra, ggplot2, and gganimate.

#DataViz #ClimateData