by Ross Donaldson, Director of Urban Systems Research, Woods Bagot
In the northern spring of 2006 the UN announced that “some day in the following months, one more child would be born in an urban hospital or a migrant would stumble into a metropolitan shantytown, and from that moment on, more than half the world’s population would be living in cities” (Happy City Montgomery 2013, p3). This meant that around 3.3 billion out of nearly 6.6 billion people were then living in cities. By 2030, it is anticipated that 70% of us will be in cities, growing to almost 5 billion people of 8.5 billion. This trend is expected to continue.
How will we house these people and how will it change our cities? What is the resilience of our existing urban system and infrastructure to cope with this? What is the inherent or latent capacity of our cities to accommodate the impact in a way that is not only environmentally sustainable, but also socially and economically viable.
This paper proposes an optimistic scenario for the outcome – and it comes from the fact that the digital revolution, associated technological advances and their disruptive forces will dramatically improve our capacity as designers, planners and architects to meet these challenges.
Steps towards a whole theory of the city
Along with the population challenge, climate change remains the second primary challenge for the 21st century and we seem to have reached a tipping point in the trajectory of that challenge. Working towards a zero carbon economy and restraining the earth’s temperature below 2 degrees Celsius continues to be the fundamental focal point. Cities comprise a major part of the problem.
In 2015 we could see for the first time a variety of market demands and economic forces aligning with the strategies we must implement to reach this target in our planning of cities.
For the first time in 2014 the amount of capacity added to the global energy supply system from renewable energy outstripped fossil fuel for the first time. The investment in fossil fuels is forecast to continue its decline as investment in clean energy grows. By 2030 it is expected that investment in clean energy will outstrip that in fossil fuels by over 4 times and low oil prices have not put a halt to the trends.
In March 2016, Saudi Arabia announced a sell off of its state owned oil assets in Aramco to create a $2tr sovereign wealth fund to diversify away from oil, a powerful and symbolic shift away from fossil fuels.
The Paris Agreement and the new accord amongst world leaders is further testament to this tipping point.
To reach a zero carbon economy this ground shift on the energy supply side must be matched by a reduction on the demand side. The key to this is cities which are responsible for more than half of the world’s energy consumption. And this will be exacerbated by the ever increasing population of cities, predicted to grow by 1 billion people migrating to cities from rural areas in developing countries in the next 15-20 years.
Demand reduction requires smarter high performing buildings, but it also requires new typologies of cities. Studies have shown that if the heat generated and lost from buildings in London for example, was captured and recycled through a combined heat and power system (CHP) the energy requirement to power London could be halved. This requires a new way of developing and regenerating cities at a district scale integrating the systems for this recovery.
To optimize this system, it is important that at the district scale, the composition must be comprised of a mix of uses, to take out the peaks and troughs of demand and consumption as well as harness the full resources within the system for potential energy sources.
Interestingly this urban composition of mixes of uses blended together in close proximity is also the basic model one sees in interesting cities with a vibrant social and cultural life. We see this in older cities and parts of cities everyone likes to visit and stay in. But one does not typically see this in modern cities and recently developed areas of cities.
Why is this? Why do we intuitively understand what a good city is and yet planners and designers consistently reproduce banal mono cultural and separately zoned cities layouts. It seems that we struggle to model and cope with the complexity.
When we visit a city like Shanghai for example, we will go to the bund and take a picture across the river to Pudong and marvel at its scale. But we will not usually visit the Pudong side. We will turn around and go into the old colonial area behind the Bund or perhaps grab a cab and go for a coffee or lunch in the French Concession. We literally vote with our feet in the judging of value in city fabric.
There is something about the perceived “livability” of these types of urban areas.
Indeed if one studies the detail make up of cities judged to be livable in the many high profile “league” tables for livability such as the Economist Intelligence Unit’s reports, you will consistently see the downtown areas of the high scoring cities, a complexity in the systems of mixed use and a distribution of what might be called social amenity throughout the urban fabric – cultural facilities, healthcare, education, worship – forming a disaggregated pattern.
This is the antithesis of precincts and zones for health, education and arts as we see in many more recently planned modern cities.
So it seems that the design of cities for energy optimisation aligns with designing for livabiliy. And this typology is also the focus in markets in many established large cities experiencing a demand driven priority for lifestyle livability where the intensification of urban cores rather than growth in the suburbs is a growing trend.
Quite apart from “doing the right thing” in the context of demand reduction for energy and creating cities with a high level of social vitality, there are powerful market forces now aligning with this.
In simple terms, twentieth century planning was based on central place theory and and zoning of uses into discrete parts of the city. The vast dispersal of residential suburbs, ever sprawling across the landscape around the city commercial cores, along with the phenomenon of big box retail centres and so forth has generated massively expensive transport systems connecting these cells, contributing to significantly to the energy demand of cities and waste in resources of an unprecedented scale – these are more expensive to build and operate than any urban form ever constructed. These have been “divided” cities.
But the market is speaking.
In America in 2011, for the first time the inner urban areas of major cities experienced more growth than the suburbs.
An one of the most powerful forces in this are the millennials who want a life in a vibrant human scaled city. And amongst the millennials, college graduates are the strongest in this – what has been called the “white flight” to the suburbs in the 50s and 60s of the last century is now the “bright flight” back to the city in this century.
And in this context, one of the most economically potent impacts is coming from the Tech sector.
In order to engage in the discourse around these forces Woods Bagot has been sponsoring a series of conferences in major cities around the world. We call these “cities of opportunity” (borrowed from the PwC reports of the same name).
We call the series “Indivisible Cities” a deliberate and provocative attack on the conventions of 20th century urban planning. We have held three in the series, in London, New York and Melbourne. The final two in this series will be in Shanghai and Sydney, with Djakarta to follow. The target audience has been developers and policy makers who together “build” the city.
Computational modeling of the city
To help fuel the debate we have undertaken a programme of research, focusing on London and New York, to understand in real depth the impact of the Tech sector market force and how it is manifest spatially.
To overcome the inherent weakness in traditional planning analysis we have brought bear the full potential of the ever increasing data resource available to planners. Ubiquitous big data by itself is no solution. Understanding how to use it is the key. We have built a new architecture of computational modelling, digitally integrating multi layers of data to produce algorithmic models, for the first time accurately representing the complexity that has evaded planners.
We have focused on the Tech sector because it is such a powerful force in real estate markets in great cities and all progressive cities are now focused on competing for the Tech market. But the research shows that this is just one of any number of market “communities” which could be modelled in this way to understand what has been the incomprehensible complexity of interesting vibrant cities, incomprehensible that is, apart from at the intuitive level!
What we have discovered is that there are very distinctive traits in the Tech Sectors behaviour when its players are seeking places to locate their businesses in cities.
They occupy mixed use areas, including a significant residential element, with local convenience shopping close by (typically for instance within 50-80m of a café or pub in the Shoreditch Silicon Roundabout area), within 150-200 meters of a subway station (in New York), with nearby public space and park amenity and so forth.
They will occupy parts of the city with a fine urban grain in terms of heights of buildings, density of street and aspect ratios to these streets. There are discernible mathematical patterns to this disaggregated structure and it can be modelled.
We are steadily building a new model for the city based on real data and dimension to the point where we can predict behaviour.
We are modeling here not only what Tech is thinking when it is making a rental choice, we are how they are making this choice. We are modelling how they are thinking!
These graphs model the criteria by which Tech chose is location and identify which parts of the city meet these criteria both in terms of relational proximities and the dimension of these.
And the map below shows where they are actually located. It’s a small step from this to be predictive and to step into these algorithms as design tools for optimum performing cities for all types of communities.
This will be transformative in how we can now plan cities and areas of regeneration in cities and how we explore the “latent capacity” of cities to meet the demand for growth in this century – in a socially, economically and environmentally viable way.
The practice of urban design is about to change fundamentally and we will have the opportunity to put behind us the flawed planning of the 20th century. And as we do so we will be able to plan for cities to play their part in meeting the climate change challenge.