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#viridis

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Eugene Alvin Villar 🇵🇭

I guess one reason why I haven’t done heat maps before is because I don’t think they are as useful compared to other cartographic #dataviz techniques such as binning and choropleths. But maybe I’m missing something?

Anyway, for the heat map, I used the Leaflet.heat #LeafletJS plugin by Volodymyr Agafonkin, creator of Leaflet: github.com/Leaflet/Leaflet.hea

The hexbin map uses the #H3 hex grid system with the #Viridis Inferno sequential palette.

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GitHubGitHub - Leaflet/Leaflet.heat: A tiny, simple and fast heatmap plugin for Leaflet.A tiny, simple and fast heatmap plugin for Leaflet. - Leaflet/Leaflet.heat
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Eugene Alvin Villar 🇵🇭

#30DayMapChallenge 🗺️ Day 8️⃣: #HumanitarianDataExchange (#HDX)

I have questions. 🙋

I was browsing the HDX data on #ClimateChange and found this wind speed hazard data from #ETHZürich Weather and Climate Risks group generated using their Climada tool. What’s interesting was they provided wind speeds in a ~4×4–km grid but as a CSV file! I had no idea what the data looked like and so I rendered it as a map with the speed colored using the #Viridis Mako palette (originally from seaborne).

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Raster map of the Philippines where the land is divided into a grid of approximately 4×4–km cells and where each cell is colored based on the historical tropical cyclone wind speed that affected that area. The speeds range from 0 m/s to 84 m/s and the northern part of the Philippines typically sees higher wind speeds while the extreme southern part sees little to no wind.
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Eugene Alvin Villar 🇵🇭

#30DayMapChallenge 🗺️ Day 4️⃣: Hexagons

Because the prompt says to use a hex grid, I couldn’t do what I did last year: en.osm.town/@seav/111380068524

So I took this opportunity to play around with Uber’s H3 grid system: h3geo.org/

Anyway, here are three maps showing the #Wikidata items with P625 (coordinates) where P17=Q928 (country = #Philippines 🇵🇭) aggregated (binned) into H3 hexagonal cells in three different resolutions (4 to 6) and colored with the #Viridis Inferno palette.

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Map of the Philippines as a grid of hexagonal cells with a radius of around 25 km and where the cell’s color indicate number of items, ranging from black (0) to bright yellow (high value). The brightest cell is located around Manila.
Map of the Philippines as a grid of hexagonal cells with a radius of around 10 km and where the cell’s color indicate number of items, ranging from black (0) to bright yellow (high value). The brightest cells are located around Manila.
Map of the Philippines as a grid of hexagonal cells with a radius of around 4 km and where the cell’s color indicate number of items, ranging from black (0) to bright yellow (high value). The brightest cells are located around Manila.
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