At least in the winter . As the days get longer , the risk tapers off tardily , or gets pushed back an minute or two , as you could see in this chart of pedestrian risk over clock time . But , it ’s not just a chart — it ’s also a map .
It ’s the employment of John Nelson , who has previously done visualizations that take a look attraffic fatalitiesand a series of “ tornado change of location mapping . ” In this infographic chart , he plots out the jeopardy of pedestrian accidents , as it change over time of year and time .
https://gizmodo.com/visualizing-5-years-of-traffic-fatalities-what-is-the-5970486
https://gizmodo.com/when-tornados-strike-which-way-do-they-travel-513093207
While it ’s not surprising to see that pedestrian accidents increase as it gets glowering , and decrease when the light is better , what is interesting is the way it form what Nelson calls a “ non - geographic map . ” OnNelson ’s blog , he explain why and how this sort of unwitting mathematical function is produce by the data , not just from them :
Amazingly , or not so amazingly to the tougher nuts out there , is that the very roundness of Earth is echoed in the shape of the curve you see in this chart . It ’s like what I would expect to see from a rough radio scope sign of some remote planet , only it ’s our planet . And the sign we see is an emerging reflectivity of our movements on its curving surface . These traffic events happened in the United States . But the bender would be the same for other northerly Hemisphere places , and it would bend the other way for places in the Southern Hemisphere . Because we hold out on something that is dynamic , data of our lives often discover the signal of that dynamic process -a roundabout meta figure of Earth . That ’s a map .
Datadatavisualizationmaps
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