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 straightaway 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 inwards the images, associated amongst the image's textures, colors as well as shapes. They as well as then used machine learning to associate icon features amongst scores of perceived safety. MIT tin forcefulness out as well as then role the resulting algorithm to predict the perceived security of a novel image. They tin forcefulness out so laissez passer on whatever Street View icon a 'StreetScore' based on the results of the Place Pulse survey.

StreetScore has straightaway released a set out of maps showing areas of perceived security inwards 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 stand upwards for the areas which StreetScore has assigned equally having a high perceived security rating as well as the reddish dots are the locations amongst a depression perceived rating score.


BikeDistrict is a actually cracking trial of providing wheel directions on an interactive map. The application allows you lot to search for as well as acquire cycling directions inwards Milan, Italy.

The application returns 3 suggested routes for whatever directions query: 'cycle', 'direct' as well as 'safe'. The 'cycle' pick 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 provide a route which tries to avoid these cycle unfriendly roads. The 'direct' pick returns the most straight route as well as the 'safe' pick 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 inwards 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 inwards the suggested directions you lot tin forcefulness out select it on the map as well as BikeDistrict volition automatically route but about it.

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


In the Great Britain all the unmarried people alive inwards London, all the cyclists alive inwards Cambridge & Oxford as well as all the quondam 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 last quite happy exploring all day. I've seen a lot of maps of census information over the years as well as I must nation that this novel map from DataShine ranks correct upwards in that place amid the best.

DataShine Census maps information from the 2011 Great Britain census. What I actually similar most DataShine is the total of information from the census that has been mapped. You tin forcefulness out explore the information downward to census tract score inwards a set out of unlike demographic categories, including population, housing, education, work as well as beliefs. Each of these categories include a set out of sub-categories, so in that place actually is a lot of information to explore on the map as well as a lot that tin forcefulness out last learned most the Great Britain as well as its people.

Footnote:

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