Since 2005, LSE Cities (London School of Economics) has been collecting comparative data on how global cities perform in terms of key spatial, socioeconomic, and environmental indicators.
This is their latest data matrix:
To be clear, it is not a ranking of cities. It is intended to help us better understand how different cities around the world are performing.
Depending on how you're consuming this post, the text may be difficult to read. So here's what each column represents, moving from left to right:
Current population in the administrative city (millions)
Current population in the urban agglomeration (millions)
Average hourly population growth of urban agglomeration 2015 to 2030 (people per hour)
Administrative city area (km2)
Average density of built-up administrative area (people/km2)
GDP per capita in urban area ($, PPP)
Percentage of country's GDP produced by the metro region
Population under 20 (%)
Murder rate (homicides per 100,000 inhabitants)
Percentage of daily trips made by public transport
Percentage of daily trips made by walking & cycling
Car ownership rate (per 1,000 inhabitants)
CO2 emissions (tonnes per capita)
If you'd prefer to download a full PDF of the chart, click here.
The below graphs are taken from a recent (June 2019) report by Knight Frank on "prime" residential pricing across the world. They define "prime" as generally being the top 5% of each market by value. What these graphs show are the spread between the average price of a prime property and the top price achieved in that market.
The latest project out of MIT's Senseable City Lab examines the "sensing power of taxis" in various cities around the world. Looking at traffic data, they determined how many circulating taxis you would need to equip with sensors if you wanted to capture comprehensive street data across a particular city. This might be useful if you wanted to measure things like air quality, weather, traffic patterns, road quality, and so on.
What they found is that the sensing power of taxis starts out unexpectedly high. It would only take 10 taxis to cover 1/3 of Manhattan's streets in a single day. However, because taxis tend to have convergent routes, they also discovered rapid diminishing returns. It would take 30 taxis (or 0.3% of all taxi trips) to cover half of Manhattan in a day, and over 1,000 taxis to cover 85% of it. A similar phenomenon was observed in the other cities that they studied: Singapore, Chicago, San Francisco, Vienna, and Shanghai.
However, if you look at the percentage of trips needed to scan half of the streets in a city, Manhattan has the lowest rate at 0.3%. Vienna is the highest at 9%. But I'm not sure if this is a function of the utilization rate of their taxis or if it has something to do with urban form. Singapore has a similarly low rate (0.44%), but its street grid looks nothing like that of New York's.
Here's a short video explaining the project:
https://youtu.be/Vs3q3jQaM9Q
Since 2005, LSE Cities (London School of Economics) has been collecting comparative data on how global cities perform in terms of key spatial, socioeconomic, and environmental indicators.
This is their latest data matrix:
To be clear, it is not a ranking of cities. It is intended to help us better understand how different cities around the world are performing.
Depending on how you're consuming this post, the text may be difficult to read. So here's what each column represents, moving from left to right:
Current population in the administrative city (millions)
Current population in the urban agglomeration (millions)
Average hourly population growth of urban agglomeration 2015 to 2030 (people per hour)
Administrative city area (km2)
Average density of built-up administrative area (people/km2)
GDP per capita in urban area ($, PPP)
Percentage of country's GDP produced by the metro region
Population under 20 (%)
Murder rate (homicides per 100,000 inhabitants)
Percentage of daily trips made by public transport
Percentage of daily trips made by walking & cycling
Car ownership rate (per 1,000 inhabitants)
CO2 emissions (tonnes per capita)
If you'd prefer to download a full PDF of the chart, click here.
The below graphs are taken from a recent (June 2019) report by Knight Frank on "prime" residential pricing across the world. They define "prime" as generally being the top 5% of each market by value. What these graphs show are the spread between the average price of a prime property and the top price achieved in that market.
The latest project out of MIT's Senseable City Lab examines the "sensing power of taxis" in various cities around the world. Looking at traffic data, they determined how many circulating taxis you would need to equip with sensors if you wanted to capture comprehensive street data across a particular city. This might be useful if you wanted to measure things like air quality, weather, traffic patterns, road quality, and so on.
What they found is that the sensing power of taxis starts out unexpectedly high. It would only take 10 taxis to cover 1/3 of Manhattan's streets in a single day. However, because taxis tend to have convergent routes, they also discovered rapid diminishing returns. It would take 30 taxis (or 0.3% of all taxi trips) to cover half of Manhattan in a day, and over 1,000 taxis to cover 85% of it. A similar phenomenon was observed in the other cities that they studied: Singapore, Chicago, San Francisco, Vienna, and Shanghai.
However, if you look at the percentage of trips needed to scan half of the streets in a city, Manhattan has the lowest rate at 0.3%. Vienna is the highest at 9%. But I'm not sure if this is a function of the utilization rate of their taxis or if it has something to do with urban form. Singapore has a similarly low rate (0.44%), but its street grid looks nothing like that of New York's.
Here's a short video explaining the project:
https://youtu.be/Vs3q3jQaM9Q
The most expensive market is Hong Kong. The average price of a prime property in 2018 was USD 4,251 per square foot (or USD 45,760 per square meter) and the top price achieved was in 2016 at USD 28,154 per square foot (or USD 303,051 per square meter).
Using the 2018 average, a 350 square foot studio apartment would run nearly USD 1.5 million (or almost CAD 2 million), assuming there are "prime" studios available in the market. Remember, we are talking about the top end of the market.
If you'd like to download a copy of the full report, you can do that over here.
The most expensive market is Hong Kong. The average price of a prime property in 2018 was USD 4,251 per square foot (or USD 45,760 per square meter) and the top price achieved was in 2016 at USD 28,154 per square foot (or USD 303,051 per square meter).
Using the 2018 average, a 350 square foot studio apartment would run nearly USD 1.5 million (or almost CAD 2 million), assuming there are "prime" studios available in the market. Remember, we are talking about the top end of the market.
If you'd like to download a copy of the full report, you can do that over here.
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