Jorge M. Pacheco, one of the scientists involved in the study explains “what this means is that now we finally could have a unified characterisation of urban areas worldwide that pave the way for city planners all over the world to collaborate, whether comparing urban policies or forecasting typical future scenarios and procedures to deal with them.”

“And the software that does all this “says Pacheco “ is not only effective, but also easy to use, can assess any region in the world and be run in any computer. All we need is people’s interest; the technology is free and is here. ”

The logic behind the development of our cities is, to anyone that ever lived in one, a mysterious affair. Like living organisms, buildings grow fuelled by the desires and views of the individuals that live and rule in the cities. An objective approach to urban development has been needed for a long time but is now more urgent than ever with the rapid growth of cities in countries with fast economical growth like India and China, where too often cement jungles are destroying people’s lives.

In the work now published, Sara Encarnação, Jorge M. Pacheco and colleagues from the ATP-Group at the Institute for Interdisciplinary Research and the Centre for Geographical Studies and Regional Planning, at the NOVA University, both in Lisbon, use as case study the Metropolitan Area of Lisbon (MAL) or “Big Lisbon” - which includes the city, as well as its growing suburbs and a ring of rural regions.

Then from information on the urban development of MAL in three different years - 1960, 1990 and 2004 – they develop a mathematical model that classifies cities based not only on the amount of built up, but – and here is the interesting part - also on how built-up is distributed (so where are the buildings) and how dense or fragmented is the spatial patterning of the city, as well as how these vary with time.

And what they found is 5 very distinct Types of development, each with specific characteristics and, even more interesting, predictable behaviours. These go from Type 1, where built-up areas are scarce and isolated, and land is used mostly for agriculture and forest, to Type 5, where building is close to saturation and the space for new constructions is rare.

To city planners, however, Type 3 and 4 are the ones of real interest. These are regions with plenty of free land where to built, but also a space distribution that allows many different ways to arrange what is built. And here is where their problem lays - the combination of space to build and possibilities to arrange the built-up, puts these regions at the highest risk of uncontrolled (chaotic) growth.

Additionally, Type 3 regions typically grow by forming new dispersed built-up areas, which are linked to urban sprawl (the rapid expansion of urban areas known to bring planning, social and even health issues). Type 4 areas, on the other hand, develop by consolidating existing constructions into large connected urban block making them, despite still problematic, much less than Type 3 regions.

But the question with all theoretical models is how well they describe (and predict) real events. To test this

the researchers went back to MAL and after calculating the Type of each Km2 of territory and giving each of the 5 Types a distinct colour, plot the results in the maps. By “typing” each Km2 they will obtain a highly detailed image of what is happening. Figure 1 shows the results:

What they discover is a remarkable agreement between what the model predicts and what planners known about MAL development throughout the years. For example, several spots of Type 3 (yellow) and 4 (orange) areas detected in 1990 (that by 2004 show huge growth) are regions known to have gone through uncontrolled housing due to lack of effective regulation, and that now have huge urbanisation and social problems

Even more important, the model provides warnings; in 2004 it is already possible to spot, next to a new road in the northern periphery of Lisbon, several Type 3 areas, which, if left without regulation, will no doubt be at risk of yet more chaotic development.

Throughout history, cities tend to move from Type 1 to Type 5 (as D increases), but it is how they get from one to the other that determines their inhabitants quality of life. Encarnação and Pacheco’s work reveals that metropolitan areas behave like living evolving organisms that need effective, but also flexible planning and regulation.

By developing a way to classify what is happening as it is happening, uncovering in real time those areas requiring more attention Encarnação and Pacheco’s model brings this flexibility.

Pacheco adds “Now imagine a Google map with a version of the world in which every patch of land will be cartographically identified according to the model, and you can see how much easier and quicker would be to make the right planning decisions”