exde601e:

Human data shows how we move in cities.

Human helps people move almost twice as much in six weeks. Every day, people track millions of activities with our app. We visualized 7.5 Million miles of activity in major cities all across the globe to get an insight into Human activity. Walking, running, cycling, and motorized transportation data tell us different stories.

(Source: cities.human.co)

Amazing! Visualizing what is the fastest mode of transport in different cities? by @youarehereMIT

Amazing! Visualizing what is the fastest mode of transport in different cities? by @youarehereMIT

nevver:

Breathing City

nevver:

Breathing City

(via zuloark)

BIG TIME BCN
The whole of Barcelona’s heritage in a map
Data from more than 70,000 plots and 3,000 monuments is available in a new, interactive map which visualises information on Barcelona’s heritage.
BIG TIME BCN is a project by 300.000 Km/s (Pablo Martinez and Mar Santamaria) with Oriol Hostench.

BIG TIME BCN

The whole of Barcelona’s heritage in a map

Data from more than 70,000 plots and 3,000 monuments is available in a new, interactive map which visualises information on Barcelona’s heritage.

BIG TIME BCN is a project by 300.000 Km/s (Pablo Martinez and Mar Santamaria) with Oriol Hostench.

Visualizing London’s Evolution From Roman Times to Today

A new animation from University College London’s Bartlett Centre for Advanced Spatial Analysis illustrates how London has changed from Roman times to the present day.

vizual-statistix:

Unlike like Emperor Kuzco, I was actually born with an innate sense of direction.  If you’re like me, and you use the Sun to navigate, you probably appreciate cities with gridded street plans that are oriented in the cardinal directions. If you know that your destination is due west, even if you hit a dead end or two, you’ll be able to get there. However, not all urban planners settled on such a simple layout for road networks. For some developers, topography or water may have gotten in the way. Others may not have appreciated the efficiency of the grid. This visualization assesses those road networks by comparing the relative degree to which they are gridded.
To generate the graphic, I first calculated the azimuth of every road in ten counties (plus one parish and D.C.). I tried to choose consolidated city-counties to keep the focus on urban centers, but for larger counties, I opted not to clip the shapefile to the city boundary. All calculations were made in a sinusoidal map projection using the central longitude of the area of interest. I then graphed the angles on rose diagrams (wind roses) using bins of 5° to show relative distributions for each area. The plots were scaled such that the maximum bar height was the same on each rose. To ensure rotational symmetry in the plots, each azimuth was counted twice: once using the original value and once using the opposite direction (e.g., 35° and 215°). As such, all streets, regardless of one-way or two-way traffic, were considered to be pointing in both directions.
The plots reveal some stark trends. Most of the counties considered do conform to a grid pattern. This is particularly pronounced with Chicago, even though much of Cook County is suburban. Denver, Jacksonville, Houston, and Washington, D.C., also have dominant grid patterns that are oriented in the cardinal directions. While Philadelphia and New York are primarily gridded, their orientations are slightly skewed from the traditional N-E-S-W bearings. Manhattan is particularly interesting because it has a notable imbalance between the number of streets running the width of the land (WNW to ESE) and the length of the land (NNE to SSW). New Orleans and San Francisco express some grid-like forms, but have a nontrivial proportion of roads that are rotated in other directions. Downtown Boston has some gridded streets, but the suburban grids are differently aligned, dampening the expression of a single grid on the rose diagram. Finally, the minimal geographic extents of the grids in Charlotte and Honolulu are completely overwhelmed by the winding roads of the suburbs, resulting in plots that show only slight favoritism for certain street orientations.
If you want to see more detail, a full-resolution version of this graphic can be downloaded here:
https://www.dropbox.com/s/my7y24hrzvhagce/Road_Orientation.png
Data source: http://www.census.gov/cgi-bin/geo/shapefiles2013/main
Script for azimuth calculation: http://www.ian-ko.com/free/free_arcgis.htm

vizual-statistix:

Unlike like Emperor Kuzco, I was actually born with an innate sense of direction.  If you’re like me, and you use the Sun to navigate, you probably appreciate cities with gridded street plans that are oriented in the cardinal directions. If you know that your destination is due west, even if you hit a dead end or two, you’ll be able to get there. However, not all urban planners settled on such a simple layout for road networks. For some developers, topography or water may have gotten in the way. Others may not have appreciated the efficiency of the grid. This visualization assesses those road networks by comparing the relative degree to which they are gridded.

To generate the graphic, I first calculated the azimuth of every road in ten counties (plus one parish and D.C.). I tried to choose consolidated city-counties to keep the focus on urban centers, but for larger counties, I opted not to clip the shapefile to the city boundary. All calculations were made in a sinusoidal map projection using the central longitude of the area of interest. I then graphed the angles on rose diagrams (wind roses) using bins of 5° to show relative distributions for each area. The plots were scaled such that the maximum bar height was the same on each rose. To ensure rotational symmetry in the plots, each azimuth was counted twice: once using the original value and once using the opposite direction (e.g., 35° and 215°). As such, all streets, regardless of one-way or two-way traffic, were considered to be pointing in both directions.

The plots reveal some stark trends. Most of the counties considered do conform to a grid pattern. This is particularly pronounced with Chicago, even though much of Cook County is suburban. Denver, Jacksonville, Houston, and Washington, D.C., also have dominant grid patterns that are oriented in the cardinal directions. While Philadelphia and New York are primarily gridded, their orientations are slightly skewed from the traditional N-E-S-W bearings. Manhattan is particularly interesting because it has a notable imbalance between the number of streets running the width of the land (WNW to ESE) and the length of the land (NNE to SSW). New Orleans and San Francisco express some grid-like forms, but have a nontrivial proportion of roads that are rotated in other directions. Downtown Boston has some gridded streets, but the suburban grids are differently aligned, dampening the expression of a single grid on the rose diagram. Finally, the minimal geographic extents of the grids in Charlotte and Honolulu are completely overwhelmed by the winding roads of the suburbs, resulting in plots that show only slight favoritism for certain street orientations.

If you want to see more detail, a full-resolution version of this graphic can be downloaded here:

https://www.dropbox.com/s/my7y24hrzvhagce/Road_Orientation.png

Data source: http://www.census.gov/cgi-bin/geo/shapefiles2013/main

Script for azimuth calculation: http://www.ian-ko.com/free/free_arcgis.htm

theatlanticcities:

"What does a full day of flight paths over Europe look like? Sort of like an immense rave on the cloud tops, according to this trippy visualization that might have you reaching for glow sticks and PLURRing in no time.”

(Source: thisiscitylab)

Mapping London’s housing 
Neal Hudson, a residential property analyst at Savills, has produced a fascinating map illustrating the distribution of different housing tenure types in central and inner London. Green means social housing, blue means private rented, orange signifies home owners with mortgages and red shows wholly-owned.

Mapping London’s housing

Neal Hudson, a residential property analyst at Savills, has produced a fascinating map illustrating the distribution of different housing tenure types in central and inner London. Green means social housing, blue means private rented, orange signifies home owners with mortgages and red shows wholly-owned.

Mobile & Sensible Moscow

Interactive data visualization of research ‘Transport Network and Social Network: Motion and Emotion’ Moscow Urban Forum 2013 Research is the collaboration between Thomson Reuters, Mathrioshka and MegaFon Сommissioned by the coordinator of complex research ‘Archaeology of the periphery’ consortium bureau Meganom and Institute Strelka

More info 

shareablecity:

Smart London - Imagining the Future City: London 2062 (by UCLTV)

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