How can we measure how green our towns and cities are?

Neil Dymond-Green, Service Director for Impact

Neil Dymond-Green investigates an approach to mapping city trees using Google Street View data.

We’re all much more aware these days of the environment we live and work in, and recognise trees’ ability to help absorb some of the excess carbon dioxide from our atmosphere.

Areas including  Greater Manchester and Northumberland, and organisations like Trees for Cities are actively trying to increase the number of trees and people’s connection with them.

There are various approaches people have developed to work out how physically green a city or town is.

The OECD gathers international data on Depletion and Growth of Forest Resources, open access data available from the UK Data Service.

A couple of years ago, the BBC website highlighted a tool which had been devised to map four types of land use in local authorities: farmland, natural, built on and green urban.

The ONS Data Science Campus has also developed algorithms for mapping the urban forest at street level.

I was intrigued then, when I read a recent article in the Guardian: Green streets: which city has the most trees? about another approach to mapping how tree-filled cities were.

The two particularly interesting things? Firstly, that the work had been based on Google Maps Street View data and secondly that the team at the MIT Senseable City Lab made the code open source.

The researchers at MIT (in collaboration with the World Economic Forum) developed Treepedia, which currently analyses and maps the above-ground tree cover in 27 world cities (with more promised).

Treepedia map of Sydney, showing Green View Indicator percentage

Where other approaches have used satellite mapping, the MIT researchers calculated what they term the ‘Green View Index’ (GVI) using Google Street View (GSV) panoramas.

Taking this approach meant the researchers were able to represent how people perceive their environment at street level. Their GVI uses a scale from 0-100, representing the percentage of canopy coverage at any particular location.

The team go into detail about their methodology for creating the GVI in several papers, including their most recent:  Mapping the spatial distribution of shade provision of street trees in Boston using Google Street View panoramas.

One particular quirk of the team’s chosen method for calculating a Green View Index for an area is that it is (as they acknowledge) limited by where Google Street View vehicles can access.

This leads to the interesting side-effect that their Treepedia map of the Manhattan part of New York has a large dark space where Central Park is. That said, this approach does highlight the amount (or lack thereof) of trees on town and city streets, which in itself is an opener for discussion.

Treepedia map of Manhattan, New York showing the 'empty' space of Central Park

While Treepedia covers a limited number of international cities currently, the team are keen to share their code and have released an open-source Python library that can be used to compute the Green Value Index for any city or region. You will need a GIS file for the street network of your chosen area and a Google StreetView API key. The library can be downloaded from GitHub.

Have you tried mapping how green your area is? Let us know in the comments below.

About the author

Neil Dymond-Green is the UK Data Service Impact Manager.

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