For people living in cities, population density has a defining impact on everyday life. It influences a range of factors, from how we commute, interact socially, and engage in creative projects, to how we manage environmental sustainability. It is also closely linked to transportation, the availability of amenities, and the vibrancy of city life.

But despite decades of research on this topic, there remains a distinct lack of clarity surrounding how urban density should actually be defined. Most commonly, urban density is understood as the number of people living within a given area of a city. But in reality, this definition can mask the underlying complexity. The challenge is that within any neighbourhood, density can vary dramatically.

In some areas, apartments may house hundreds of residents, while just next door, parks, streets, and railways remain uninhabited, despite being central to the functioning of cities. Ultimately, this complexity makes it difficult to quantify density, and its impacts on urban life. To gain a better understanding of how cities function, it will be crucial to account for these variances in density across different urban landscapes.

Through his research, Dr Elek Pafka introduces a new approach to mapping the multi-scale variations in urban density. He proposes two new metrics: Metropolitan Walkable Density and Urban Experiential Density. Both are calculated using uniform grids, thus overcoming the bias of previous studies. By applying these metrics across 12 western cities, his study reveals important insights into how we access and experience cities in our daily lives.

To visualize these multi-scale variations, Pafka first selected 12 large cities across North America, Australia, and Europe, using census data to map their population density. With the first metric, Metropolitan Walkable Density, or MWD for short, he aimed to bridge the gap in density measurements between two key scales within a city.

At the smaller scale, MWD considers the density of individual walkable neighbourhoods, where people typically start and end their daily journeys. These areas could include local shops, small parks, schools, and public transport stops that connect people to the rest of the city.

On the other end of the scale, MWD considers entire metropolitan areas. These often contain functions that can only be sustained by large populations, such as office complexes, universities, and stadiums. They also encompass neighbourhoods that might only be visited occasionally by residents living outside them, for purposes such as visiting friends or shopping for specialty items. Most often, this will involve trips made by car or public transport.

Across the 12 cities analysed, unsurprisingly MWD tends to increase in the urban core, then gradually decrease further from the centre. However, there are stark gaps even within city centres, often dominated by areas where people come to work or visit during the day, rather than reside.

Yet beyond these general trends, there are significant differences between cities. For example, most North American and Australian cities feature extensive areas of suburban sprawl, whereas European cities tend to have higher density throughout most of their metropolitan areas, with a narrower suburban belt.

Comparing the MWDs of individual cities also revealed some fascinating contrasts: while London has a wider suburban belt, Madrid’s is almost non-existent. In cities such as Berlin and Stockholm, higher density areas often correspond to major public transport routes, while in Milan, there is a distinct density discrepancy between the hilly north and the flat, agricultural south.

Even further, while cities like New York, Madrid, and Paris have extensive areas of very high density (over 200 people per hectare), these high-density areas are much sparser in cities such as Los Angeles, Berlin, and Milan, and are almost non-existent in Chicago, Sydney, and London.

Pafka’s maps also debunked long-standing misconceptions about urban density. For example, Los Angeles in particular is often portrayed as a most sprawled metropolis, dominated by low-density suburbs. But when considering MWD, the maps clearly showed that the city is denser than many others in North America and Australia, such as Montreal or Sydney.

Pafka suggests that this discrepancy may stem from inconsistent ways of measuring density, as well as media depictions and everyday perceptions of the city. This insight led to a second metric for measuring density, called Urban Experiential Density, or UED for short.

As previous studies have shown, human perception of a city’s density can be influenced by a variety of factors, including building height, landscaping, and the general sense of enclosure created by the surroundings. With UED, Pafka aimed to explore two key aspects of perceived density: the direct experience of a person at street level, and their experience of the central areas of the city, which are often visited by both locals and tourists alike.

Although census data for UED maps for European cities wasn’t available, the analysis revealed an intriguing contrast between North American and Australian cities. In North America, areas of higher density tend to be clustered together, whereas in Australian cities such as Sydney and Melbourne, these areas are more scattered, likely due to differences in city planning practices between the two regions.

Altogether, the analysis demonstrates that this approach to mapping and measuring urban density offers a far less distorted and more nuanced understanding of the phenomenon compared with traditional methods. While MWD showcases the patchwork of different neighbourhoods that form a larger city, bridging the gap between walkable and metropolitan scale, UED provides a clearer picture of how urban density is perceived by people who inhabit and visit cities.

For now, Pafka acknowledges that these methods are not all-encompassing: for example, urban density is also influenced by the time-varying movements of people throughout the day, week, and year. He also notes that these methods might be more difficult to apply to cities in the Global South, where detailed census data isn’t readily available. Through his future research, Pafka hopes to address these issues in more detail.

Nevertheless, his current approach already lays a solid groundwork for a deeper understanding of how cities function. By building on the concepts of Metropolitan Walkable Density and Urban Experiential Density, he ultimately hopes that urban planners and researchers could ultimately develop new strategies for making cities more energy efficient, environmentally sustainable, and better places to live.