29.03.23 - Data driven urban planning - What is the impact of creating "slow zones" in the city?
Data driven urban planning - what is the impact of creating "slow zones" in the city? (areas designed to be more pedestrian-friendly)
MIT Senseable City Lab has just published a study to answer this question by performing a spatial analysis integrating geo-referenced data obtained by a social network. More than 11 million tweets from over 30k users were used in the city of Paris.
Why Paris? Over the past 10 years, Paris has implemented slow zone in more than half of its streets to return space from cars to people. Besides limiting vehicle speed, Paris implemented physical changes to improve walking conditions, adapt the city infrastructure for bikes, and offer livelier, more pleasant streets.
What is the impact? First, street sensor analysis showed that car volume decreased by 41% in slow zones relative to other areas of the city.
But what about human activities in these zones? Comparing street segments immediately within the slow zone boundary to street segments immediately outside the slow zone shows that human activity measured using Twitter is 44% higher in slow zones. This effect is driven by an increase in both the number of users and in the number of tweets per user.
In addition, slow zones draw visitors from a wider geographic range of neighborhoods, contributing to social mixing.
This is the future of urban planning:
We use maps for navigation to get around the city more efficiently. By combining these maps with sensor data and geo-referenced feeds from social networks, we can now adapt the infrastructure of our cities and demonstrate the benefits of these changes to achieve greater acceptance.
This project shows also the importance of having access to Open data : Paris Open Data Portal was used to provide slow zone boundaries and street sensor data.
One challenge is to get relevant data from social network: in this case, only data until 2015 was used as Twitter stopped providing street level positioning accuracy on the data after that year and only area or city level positioning.
#urbanplanning #multidatasources #cities #qualityoflife