URBAN META/MORPHOLOGY | a short visual essay

place syntax tallinn

The urban form is defined by its physical presence, infrastructure, and geometry. Alongside the physical existence of the city, interactions and data flows weave a constantly evolving information environment. When we describe urban morphology, the study of the form and relations of the urban environment, we usually deal with the ensemble of volumes and open spaces.

urban meta morphology spin unit

Urban meta/morphology

What we would like to bring your attention to is urban meta- morphology: how spaces, people and the data they produce are intertwined and possess their own form and internal relations. The meta-morphology gives us access to the relations between social structure and dynamics, spatial structure, and the more conventional urban morphology. Studying this data may not be what we traditionally think of as urban planning, and it may not be glamorous, but in the near future it may be what makes a difference in actual planning and governance.

space syntax spin unit

It is a valuable effort as it relies, in many cases, on easily accessible data that can be kept up to date almost in real time – from sensors distributed around the city or social media, for instance. As the data is so easy to obtain, many different actors are now pursuing meta- morphological techniques to further our understanding of the city. While everyone is doing the same thing, what is special about our work, is the way we choose to do it and the expertise we bring to the table. For instance, qualitative data can be extracted road by road from purely quantitative data, with contributions from the researchers involved as they aggregate and curate the data.

spin unit instagram turku

This way we can understand not only the relationship between different groups and the city, but also the potential of certain locations and public spaces. We can highlight problems.

What appears as a design problem (shops in a certain neighbourhood only have one window, separated by a certain distance, do not attract passers-by and encourage them stop) may be an interaction problem (how can we re-engineer the way people interact with the environment, without necessarily affecting the urban fabric itself with architectural interventions?).

What kind of data should we be using? We want something that is easily accessible, available, and that remains valid across countries and social strata.

Harvesting data from different sources allows us to abandon traditional survey methods, and rely almost exclusively on new technology. By sifting through the wealth of data collected by sensors across the city and social media, we can perform partially automated digital surveys that provide new insight into social patterns, as well as into the way the city is lived and perceived.

gps traces turku
space syntax rome

Our goal however is never to just build a complex, multi-dimensional data set to mine for potentially meaningful relationships.

Using digital surveys allows the same penetration as ordinary interviews and surveys, without however the influence and biases introduced by the interview itself, a strong deviation from the traditional Kevin Lynch perspective. In addition, using the same processes and techniques one can evaluate the impact of the project after it has been carried out. We hope to detect a perceivable impact on the urban population, including those who don’t use or are not necessarily affected by the urban features in question.

This approach can be used extensively across the entire planning, design, implementation, and evaluation process. The take-away message from today’s talk is not about looking into existing scenarios for ways in which this new attitude to data collection and analysis can be deployed. Rather, I would like you to have a new awareness of new technologies and meta-morphological tools, and how they can be used to tackle new problems alongside existing techniques next year, or in the next decade. More than just urban design, it is a way to apply or change regulation, especially when designing or updating city plans. It is a way beyond census data and blueprints, to shake things up.

By capitalizing on the wealth and variety of raw data we can collect, we can improve quality of life and personal safety by analysing and tweaking often neglected environmental parameters. The re- appropriation of urban spaces at nighttime was the goal of one of SPIN’s earlier projects, which involved a survey of the artificial illumination across the city of Tallinn, Estonia.

“Measuring street light intensity”

We used a creative approach that involved a custom-built device and an Arduino microcontroller to map public illumination. Driving the device around the city, we gathered light intensity data in the darkest hour of the night over two weeks, which we then mapped. The degree to which an open space is available to as many different people as possible is called accessibility and can be readily computed. We noticed that the level of accessibility of urban spaces decreases with the distance from the city centre and is directly correlated with the level of public illumination.

“While this may seem obvious, we should ask ourselves what is the cause and what the consequence. Can we improve accessibility by improving the quality of public illumination?”

tallinn night map

That is why for instance we also looked at the paths commonly taken and recorded by actual cyclists, as opposed to the official bike routes. We did so by collating the GPS data from social media sources pertaining to the daily commutes of hundreds of cyclists. By highlighting the actual needs of the cycling population and how the existing infrastructure is lacking, we can provide better mobility and safety for cyclists and commuters, and we can even suggest evidence- based improvements to the existing routes. This is of particular relevance at the moment, as major cities like Munich, Paris and Copenhagen are designing and building networks of cycling superhighways for commuting into the city from the suburbs.

“Using GPS enabled devices to map cycling paths”

cycling map tallinn cyclists spin unit

Social media

Social media has become a common feature of our everyday life. For researchers, social media provides large amounts of readily accessible, on-time and qualitatively rich data that can be used to study urban activities and interactions. Social networks such as Twitter and Instagram have become pervasive in our society. The data made available by these social networks can therefore be collected and analysed by third-parties, providing a granular and detailed description of social processes through space and time. 

In our research, we were particularly interested in the analytic use of Location-Based Social Network data, combined with other data sources used in urban and traffic planning, in this case remote mapping and configurational analysis. We were interested in exploring which spaces in Turku’s city centre are more likely to attract people today and how the situation might change if a new tram line is constructed. The study was commissioned by the City of Turku, Finland, and funded by the Turku Urban Research Programme.

A sense of place, a case study in Turku – Finland.

space syntax turku finlad

The data-based approach can offer interesting insight into the daily and weekly rhythms of use of space as well as the meanings people attach to particular urban spaces. In such analysis, location-based data sets work as an invisible treasure of data and meta-data produced directly by the urban population, including visitors.

In this explorative study on Turku we presented just a few possible uses of this data. Activity patterns are studied by mapping a variety of human activities at ground level, correlated with the way people use the urban space. In addition, the study describes the interaction between different uses during specific periods of time. With location-based data, we gain deeper first-person insight into the local area, without being too intrusive or developing an ad-hoc data- harvesting programme. This way, we can apply our methods and knowledge to the unique context of, in this case, the city centre of Turku.

The opening of new shopping malls at the outskirts of the city may be convenient for some. At the same time, these new urban areas lack the complexity and variety that the centre can offer.

The new malls have attracted large part of commercial activities and significantly reduced the commercial real estate value in the city centre. What we found in our study, however, is that the city centre is still the main hub for social life, and has therefore the highest potential for intervention, and for social and commercial development.

We simply need to find new intervention strategies to revitalise the city centre, and make it more attractive and liveable, especially in the colder winter months. All data points towards an urban design problem, and a lack of connective tissue between the centre and the new suburban hubs. We also noticed that very few bus stations are located in socially active areas, and conversely, a large number of bus stations are severely underused. Social media data can be used for transportation planning, for instance allowing us to learn where and at what time certain areas are more active.

As our preliminary study also focused on the development of a new tram line, we combined spatio-temporal patterns, activity patterns and accessibility data to design optimal public transport routes. We concluded that a new tram line would indeed revitalise the city centre and provide reliable transportation for the suburban areas. The reach of the new tram line, and possibly the extended public transit system, would also offer opportunities for new housing in the suburbs and a larger-scale planning effort. The new line provides a planning tool in itself, thus empowering both the city centre and the wider Turku region within a daily commute.

tram line project turku

Naturally these methods have a variety of obvious and not-so-obvious downfalls. There is a strong selection bias intrinsic in the way the information is collected, as only smartphone users or social-media users, for instance, will leave a visible trace for us to follow and study. At the same time, however, the analysis has the advantage of being essentially free from different planning dogmas and essentially context- agnostic.

To conclude, we want to find a good balance between projects that are high-concept and context-specific, which allows us to acknowledge differences and similarities within a global framework. With virtual eyes on the street, we can observe the action of actual people and use that information in urban planning to design new activities that can be hosted in a pre-existing, underused location.


It is a wide-ranging approach that can be adopted by government organizations and local institutions, as well as academic researchers, and it has high local interest, as it is quick, easy, commercially viable. It allows us to study the pace of the city and its activities, observed indirectly by sampling the key locations of collective activity, through for example social media. It provides a multi-dimensional abstract map, by slicing up our data sets, instead of traditional geographical maps. This allows the creation of new centralities and strengthens existing connections that have not yet been recognised and integrated into the urban fabric.