There are lots of interesting things going on using data in cities at the moment. Many articles and blog posts talk about how data, and open data in particular, has the potential to deliver public services better, start to address long-term outcomes (such as health problems), and create a basis for decision-making. In times when public sector funding is under pressure delivering these outcomes is even more important than normal.
Collecting data in cities is helpful as it provides something to measure progress against. It means measuring specific outcomes, which also means being very precise about what outcomes are important.
It can also be a link between deciding a wider objective (improve air quality) and a specific implementable actions (make public transport free). However, to do this requires both domain and data expertise:
- to understand the difference between data on the outcomes of a system, and the variables in that system
- to measure and analyse the urban systems that form the variables
- to know how data is recorded on urban systems and what it actually represents Read More
A couple of weeks back the Design Council Newsletter re-published some work from 2014, looking at how Hackney had become one of the most liveable boroughs in London. This is evidenced by an increase in people cycling to work and a decline in those driving – both around or over 10%.
One of the reasons set out for this change in behaviour is the success of policies implemented over the last 10 years, which include re-designing residential streets. In particular the use of “filtered permeability” – using bollards to make some streets only accessible to pedestrians and cyclists – is described as part of this achievement.
Increasing active travel share and decreasing private car use is very positive, however, closing streets immediately raises questions around the wider impacts.
In a very quick summary there are three major issues with filtered permeability:
- Fragmented networks increase congestion and lengthen car trips
- Increased likelihood of air pollution in higher density, mixed use areas
- Reduced levels of natural surveillance impact personal safety
These points are expanded in the post below: Read More
These are some observations from a trip to Lima in August, around the way that cities grow. These are only based on personal experience of the city, conversations with the Lima-nites I was with at the time and stories from the main stream media.
These are some notes from a talk I gave at Space Syntax’s last Urban Imperative: Improve, Extend, Create series of events in July. It looks at how to think about designing a city from scratch. The focus of this post is to look at exactly which components of a masterplan to design and why.
This shows some work that is slightly experimental. At the moment it’s about testing ideas through a process, and at the moment it’s only a process. It started as a real project to look at ideas about how to develop a city from scratch but then some further research work was done.
This is the combination of a couple of talks I’ve given in the last few months to the ULI Urban Tech Committee and the Academy of Urbanism Digital Urbanism groups.
Urban Tech is something that has developed a lot in the last 10 years and which now seems to have a lot of interest and attention. There are a lot of terms – Future Cities, Smart Cities, Prop Tech, Urban Tech, etc – which are all slightly related but not quite connected in the way they could be.
One way of trying to understand how they fit together is by tracing what has changed in this time and what this means for the way we interact with cities.
While its interesting to see how things have changed, what is possibly more important, as professionals who work with, and in the context of cities, is to ask the more difficult “so what” questions of why things should change?
Here’s an outline of the reasons Why that will be explained in more detail below:
- Better outcomes for cities and people
- Creating benefits between public and private sectors in the short and long terms
- More transparent and inclusive decision-making
- Crossing siloes between planning and service delivery for more effective and efficient spending
Earlier posts looked at why (master) planning hasn’t worked as intended, reaching one conclusion that the design outcomes weren’t flexible enough. The response was to aim to design the fewest fixed components and allow the city to grow more organically on a plot by plot basis within this framework. Changes in the economic or social context would be reflected by variations in density, land use, massing and speed of growth.
An early outline of fixed components includes solids (blocks, plots) and voids (street, infrastructure, and utility networks). Of course there are a secondary set of requirements that must be provided, but which there is some flexibility in terms of location or exact configuration – these include social infrastructure etc.
This post starts to set out how to develop this spatial framework. Building on Bill Hillier’s idea of the Movement Economy (1) – the configuration of space affects the distribution of people who affects the distributions of land uses and values – the starting point is the spatial network. Space is very difficult to change, with far-reaching impacts, while buildings can be replaced, and land can be bought and sold.
In turn this post becomes an examination into the geometry of spatial networks and urban blocks.
As always these are developing thoughts.
These are some developing thoughts about how to plan and grow cities.
Growing, as opposed to planning or building, is important as the cities we think of as successful today weren’t designed in one attempt, or built in a few phases, but grew over many years.
There’s a lot of criticism of the way cities currently respond in a physical way to their wider economic and social context. It is arguable that planning in its current form has not and does not achieve the objectives it sets out to. Many cities are fragmented by infrastructure, set out in low density single use zones, suffer poor health, are difficult to grow, irresponsive to market conditions, irresponsive to their residents, or uncoordinated in outcome.
Collage: Ed Parham 2016, combining: Hong Kong photos, Wolf; Exodus ii Dubai, Lyon; sprawl, unknown.
The last 100 years is littered with example of ambitious city projects that have not worked as intended. Why do so few new cities work the way they were meant to? How can we learn from these and avoid falling in to similar traps? What do we know now that could make any difference?
This post works through two examples to make a case for measuring density in terms of population per length of street rather than population per unit area.
It uses two different building typologies to distribute people. While these are typologies rather than measures of density, they are important because they are often how higher level, block-based densities get interpreted and applied at the scale of the urban block.
In both cases a consistent block size and population have been used. The variation comes from the way this population is distributed at the block level (through individual buildings on individual plots, or through a single building on a single plot.
These two approaches have then been distributed across a grid of streets, and compared in terms of the number of people who live on each street. While this is a very simple measure – it does not consider the people who may be passing through the street as part of a larger scale journey – it does give an impression of the latent activity that could occur.