New The Maps Of The Week

One of the most interesting uses of Street View imagery since its introduction on Google Maps has been past times MIT. MIT's Place Pulse projection is a crowd-sourced experiment examining people's perceptions of unlike urban environments using their reactions to unlike Street View images.

MIT has similar a shot taken the the crowd-sourced security rankings for 3,000 street images from New York as well as Boston as well as created an algorithm to automatically practise a perceived security rating for Street View images. Using the Place Pulse scores MIT assigned attributes to features acquaint inward the images, associated amongst the image's textures, colors as well as shapes. They as well as then used machine learning to associate picture features amongst scores of perceived safety. MIT tin mail away as well as then role the resulting algorithm to predict the perceived security of a novel image. They tin mail away thus laissez passer whatsoever Street View picture a 'StreetScore' based on the results of the Place Pulse survey.

StreetScore has similar a shot released a position out of maps showing areas of perceived security inward New York, Boston, Chicago as well as Detroit. Using Street View images of the urban center StreetScore assesses the perceived security of locations throughout the city. Green dots on the map correspond the areas which StreetScore has assigned equally having a high perceived security rating as well as the ruddy dots are the locations amongst a depression perceived rating score.


BikeDistrict is a actually bully illustration of providing cycle directions on an interactive map. The application allows you lot to search for as well as acquire cycling directions inward Milan, Italy.

The application returns 3 suggested routes for whatsoever directions query: 'cycle', 'direct' as well as 'safe'. The 'cycle' selection returns a route which preferences cycle paths as well as avoids the roughest roads. Milan has a lot of cobbled streets as well as selecting the 'cycle' route volition supply a route which tries to avoid these cycle unfriendly roads. The 'direct' selection returns the most straight route as well as the 'safe' selection volition avoid the busiest streets as well as preference cycle paths.

The staged directions for each route are color coded on the map as well as inward the step-by-step instructions to highlight the route weather for every phase of the journey. If you lot don't similar a item route inward the suggested directions you lot tin mail away select it on the map as well as BikeDistrict volition automatically route approximately it.

As good equally providing cycle directions BikeDistrict tin mail away exhibit the place of all cycle stations (with real-time information on the position out of bikes as well as docks available), cycle parking locations, drinking fountains, cycle repair shops as well as biking related events.


In the U.K. all the unmarried people alive inward London, all the cyclists alive inward Cambridge & Oxford as well as all the erstwhile people alive on the coast.¹

I gleaned these nuggets of information from DataShine Census, a novel census information explorer for the UK. Influenza A virus subtype H5N1 census map which I would hold upwards quite happy exploring all day. I've seen a lot of maps of census information over the years as well as I must tell that this novel map from DataShine ranks correct upwards at that spot amid the best.

DataShine Census maps information from the 2011 U.K. census. What I actually similar almost DataShine is the sum of information from the census that has been mapped. You tin mail away explore the information downwards to census tract degree inward a position out of unlike demographic categories, including population, housing, education, occupation as well as beliefs. Each of these categories include a position out of sub-categories, so at that spot actually is a lot of information to explore on the map as well as a lot that tin mail away hold upwards learned almost the U.K. as well as its people.

Footnote:

¹ All the misreadings of the information hither are the mistake of the writer as well as non the mistake of DataShine Census.

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