Data and planning experts from Transport for London outline how user-friendly geospatial data and business processes underpin the delivery of the Mayor’s ambitious Transport Strategy.
Earlier this year, London Mayor Sadiq Khan released his Transport Strategy for the city, with a key focus on ‘healthy streets’. His target is that 80 per cent of journeys in London will be via walking, cycling and taking public transport by 2041, up from 63 per cent now.
Last week, London’s first ever walking and cycling commissioner, Will Norman, set out plans to make the UK capital ‘the world’s most walkable city’.
The overarching aim is to cut congestion, boost active lifestyles and improve air quality, and the Mayor is investing a record £2.2 billion in healthy streets.
There’s a way to go to get there, though. Of the 27 million daily trips that take place in London, around 10 million are still by “unsustainable modes”, such as cars, taxis, etc. For London to achieve its 2041 target, it needs a 0.7% shift every year.
At the recent Esri UK Annual Conference, Joe Stordy, Data and Spatial Analysis Manager, and Henry Cresser, Principal Strategy Planner, Transport for London (TfL), shared how they’re using data to turn these high-level targets into a detailed plan they can use to make a change.
Work on the ground
While TfL may be best known for its management of the underground network, a lot of its work also takes place above ground on London’s streets.
Ongoing projects includes improving cycle ’superhighways’, the pedestrianisation of Oxford Street and “transformation” of areas such as the Vauxhall Cross gyratory.
“I use the word transformation because these are really substantial radical changes to London’s road network,” Stordy said.
“Like any other business, we have a business plan for the next five years,” he added.
Data is key to creating this plan and making it happen – this includes both TfL data and national data. TfL has aggregated more than 200 datasets, based on 6 million different pieces of data.
While TfL has access to an “incredible” amount of data, the key challenge is: “Making that data relevant to what’s happening on the ground – to when we’re putting spades into the ground and digging holes. How data informed, how intelligent is that process?
“And that’s really what we’re trying to achieve,” Stordy said.
This means extracting the best value from data as well as driving a cultural shift in the business.
Cresser said: “The scale and complexity of both the challenge and the data is vast. So for us, simplification is key.”
TfL adopted a hex-based analytical grid. Each hex, or “walkable neighbourhood” is 350 metres across and all the relevant transport planning data is aggregated onto the grid.
The crucial question then was how to make it useable and accessible to the business.
TfL created a City Planner Tool, using ESRI’s ArcGIS mapping and analytics platform, providing a user-friendly front end for business stakeholders.
Cresser explained: “The tool is about access to data first and foremost and then, secondly, we built in this analytical functionality, with the custom widgets, that allows transport planners at TfL to undertake the prioritisation and case-making work that really we’re trying to drive through the business.”
The City Planner Tool allows users to understand the movement through neighbourhoods by mode or combination of different modes, and by time of day. They can also view the original input data that’s been aggregated into the tool. Further, they can generate reports that map against the Mayor’s Transport Strategy.
The next task was to drive business processes.
“TfL is a big organisation and a lot of this work can get lost unless you embed it into business process,” Cresser said.
The challenge here was “combining the business language of delivery with our new spatial language.”
TfL developed a scoring framework for each of the Transport Strategy outcomes using its aggregated data.
“By combining different datasets for these outcomes, you can understand the extent to which you should be seeking to address that outcome in a [particular] place,” Cresser commented.
In the example above, safety is scoring very highly, showing that there’s a significant level of traffic collisions and high levels of crime in this area. Therefore, planners should be seeking to address those outcomes.
Through the City Planner dashboard, TfL can provide a “fingerprint”, informed by data, to steer project development.
Cresser said: “As the project moves through the lifecycle, we can see how the deliverables of that project are changing over time.”
The outcomes can also be viewed spatially – visualising where the city should be looking to intervene to address a particular outcome, e.g. safety.
The image below shows safety hotspots in Westminster, for example.
Cresser explained: “If we had schemes in some of those areas we might seek to bring them forward in the portfolio. Or if we’re not planning to invest any money in those areas to address safety, we could obviously seek to create a new scheme, adopting the business process.”
In action: Broad Sanctuary
The analysis of Broad Sanctuary above shows, for example, that there’s a big opportunity around active outcomes, such as cycling and walking. The green outcome score is quite high, which typically means that air quality is very poor. The public transfer outcome is also high, which means that bus performance has been quite poor. The unlocking outcome highlights that population and/or employment growth is expected in the area.
These snapshots offer a “fingerprint” and show “how we can take that forward to develop an intervention in this area or trade it off against another intervention to get value for money from what we’re doing,” Cresser said.
TfL has been using data in this way to inform portfolio balancing and scheme development for around six months now. It has been applied to over 100 schemes.