Visualizing Pedestrian Activity in the City of Melbourne

 

Pedestrian activity is a direct reflection of the city’s livability and vibrancy. The variety of factors inclining our travelling preferences in favour of walking, range from access to transit and population density to perceived pedestrian safety and street design. Currently, there isn’t a standard approach to measuring walkability. Nevertheless, it is a common belief that a compact and well-connected urban environment, offering a diverse mixture of uses is fundamental to get people to walk.

According to Jeff Speck‘s “General Theory of Walkability“, the first thing you need to do is offer citizens a reason to walk and then make the walk safe, comfortable and interesting. Julie Campoli, an other urban designer with a passion for walkable cities, believes that there are six key elements to the perfect pedestrian environment: Design; Diversity; Density; Distance to Transit; Destination Accessibility and Parking.

As the world’s most liveable city, Melbourne is already exhibiting good results when considering these indicators, yet walkability patterns vary from one location to another. In the last couple of months we explored data from the city’s pedestrian counting system to visualize movement patterns and network interdependencies. Here is a sneak peak of the project’s current state.

Above: Total number of pedestrians counted by year, including busiest day and busiest location. Image by Morphocode.

Melbourne’s Pedestrian Counting System

Melbourne is considered to be the most liveable city in the world according to The 2015 Economist Intelligence Unit ranking. The city is also exemplary for its mindful use of data in urban analytics and for its Open Data Policy allowing simple access to Council-owned information.

In the last six years, local authorities has installed 44 sensors to measure pedestrian activity at strategic locations throughout the city. Each sensor is installed on a street pole or under an awning to cover a pedestrian counting zone on the footpath below. The counts are updated regularly and are published in .csv file format on Melbourne’s Open Data Portal. The raw data is a tabular representation of hourly numbers of pedestrians at each measurement point. We used this open dataset and a visualization technique called “Horizon Graph” to reveal movement patterns in a seamless urban electrocardiogram.

Above: Location of pedestrian counting sensors in the City of Melbourne. Image by Morphocode.

 

For more than 30 years the City of Melbourne has been transforming the municipality’s walking environment. Melbourne’s iconic Bourke Street Mall opened officially in 1983. Guided by the Places for People studies in 1994 and 2005, the City of Melbourne has widened footpaths, laid high quality pavements, encouraged outdoor dining and reduced traffic signal cycle times to support improvements to public transport to make Melbourne a more attractive place to be.
City of Melbourne Walking Plan (2014-2017)

 

The average block size in the Central Business District of Melbourne is 200 by 100 meters. This iconic layout was named after Robert Hoddle, who conceived it in 1837: initially a square grid, the plan was subsequently subdivided in smaller rectangular blocks and still preserves the strong hierarchy of the street system. The Hoddle Grid covers the area from Flinders Street to Queen Victoria Market, and from Spencer Street to Spring Street. Melbourne’s numerous Arcades and Lanes are an important feature of the city’s cultural heritage and provide through-block pedestrian shortcuts that increase connectivity. The majority of the pedestrian counting sensors, installed by the municipality of Melbourne are located in the Central Business District and provide a better understanding of how people navigate through the area.

 

Above: Visualization of pedestrian activity in March 2015 shows significant spikes accross the city during a 3-day Moomba Festival. Image by Morphocode.

Visualizing Pedestrian Activity with Horizon Graphs

To build the visualization we’ve used Cubism.js – a d3 plugin for visualizing time series. The library was developed by Mike Bostock and is built around a visualization technique called Horizon Graph. Horizon graphs are similar to traditional area charts, but allow to fit the same data into less space while preserving resolution. They are often used in data dashboards to monitor real-time activity such as CPU usage and stock exchange data.

Cubism.js comes with built-in support for real-time sources such as Cube and Graphite. It is not well-suited for static data sources such as Melbourne’s Pedestrian Counts dataset. We had to implement a custom Metric to load the pedestrian data from past periods and then plot them on the canvas using a custom Context.

Above: Increasing data density while preserving resolution – how to read a Horizon Graph of pedestrian activity. Image by Morphocode.

 

Above: The 5-minute walk. Access to a wide variety of amenities and services within a short distance can increase pedestrian flows and encourage people to walk. Image by Morphocode.

The 5-minute walk

During the research we also explored access to different types of amenities within the Central Business District of Melbourne, where the majority of the pedestrian counting sensors are located. The map above shows access to basic amenities around the sensor at Alfred Place – a pedestrian shortcut, cutting through the width of a block. Plotted dots visualize the density of 5 types of elements:
 Landmarks and places of interest
Public Transport stops
Outdoor furniture
 Public memorials and sculptures
 Drinking fountains

The walking distance standard has slight variations across the globe but it is considered that a person would cover 80 meters within a minute of walking. This is the reason why a 5-minute walk is usually represented as a circle of 400-meter radius.

Above: Sensor profiles show variations in pedestrian activity accross different types of locations. Image by Morphocode.

Places for People: Melbourne’s long-term commitment to walkability

The Places for People study began in 1993 when the city invited Professor Jan Gehl for the first time to assess the quality of public space and public life in Melbourne. The study was reassessed in 2005 and again, another decade later, in 2015. This lengthy data collection period has provided rigorous insight into how the city performs at a local, everyday level for people and continues to inform urban strategies in their long-term commitment to increasing the levels of pedestrian accessibility.

 

“Places for People focuses on walking as the primary mode of transport in the city.”
 City Strategy and Place, 2015

 

Through the years, a variety of measures have been undertaken to make the urban environment more appealing for walking – the amount of footpath space has been expanded by nearly 15 per cent since 2007; a speed limit of 40 km/h has been set in the central city; numerous public spaces have been renovated and through-block laneways have been enhanced and converted to active uses.

Currently, walking accounts for 66 per cent of all trips within the municipality of Melbourne.

 

 

What’s next?

We are currently developing an interactive version of the data visualization that will allow you to explore pedestrian activity by location and time. The project will be published soon on our website. You can subscribe to our newsletter for more updates.

Hello Munich!

 

As we already mentioned on twitter and facebook, we will spend the next couple of months in Munich, working as guest artists in PLATFORM. The concept that we are currently developing is called Data Urbanism and will be presented in an exhibition on the 21st of October.

 

Platform
Above: W;HERE by Duncan Swann, exhibition opening. Image courtesy: Vivi D’Angelo for PLATFORM


PLATFORM
is a cultural service agency for the creative sector, which develops and implements cultural concepts for the city, public institutions and companies. In particular, it anchors the creative processes of design, art, architecture and theories in urban development processes and a lively dialogue between business, culture and the public are close at heart. This is a pilot project of the city of Munich and is situated in a 2000 square meter floor of a building in a former industrial area.

 

Meanwhile we are residing at Streitfeld where the afternoons could not be more delightful!

We will try to post updates on our work as often as possible and occasionally send newsletters with more details on our upcoming exhibition!

Cover image courtesy of PLATFORM.

 

 

 

Data Urbanism

 

Context

In 2007, the global urban population reached the 50% threshold and for the first time in history exceeded the global rural population. The same year, the first iPhone was released and set the tone for a smartphone revolution that changed the way we experience, navigate and interact with our immediate urban environment. We are now living in increasingly data-rich environments where open data platforms allow us to access, collect and analyse information about the city. As urban sensors become more and more ubiquitous and spatial information even more abundant, data vizualisation allows a critical evaluation of active policies and city services by transforming otherwise hidden patterns into visual arguments.

The amount of data generated by our daily activities and interactions will increase persistently, as digital devices continue to permeate our lives. And while we use those devices as a central access point to information, the data we generate on a daily basis — either directly or as a by-product of our social activities — is often associated with contextual meta-information about location, usage and people. In other words, data gives a valuable insight into both our social interactions and the environment that staged those interactions. Furthermore there is a strong tendency to open data repositories that were once locked within government agencies. Open access to information, as well as the emergence of low-cost or free analysis web tools, allows citizens to look for patterns in government activity or to use data analysis to advocate for change.

We refer to the process of making urban data visible, accessible and actionable as Data Urbanism.
Data Urbanism suggests an iterative approach to urban planning that starts with harnessing the potential of open spatial data by enabling hands-on interaction with it and transfoming the invisible bits into a coherent exploratory mechanism.

 

 

Cities: The Global Urban Transition

The trends of urbanization differ across the globe. In 2014, Latin America and the Caribbean and Northern America had the highest levels of urbanization, at or above 80%. Europe remains in third place with 73% of its population currently living in urban areas and is expected to reach 80% urban by 2050. Between now and 2050, 90% of the expected increase in the world’s urban population will take place in the urban areas of Africa and Asia [1]. In other words, the projected urban growth will be concentrated in cities in the developing world where the correlation of the rate of urbanization with economic growth has been weaker. Expansion of urban areas is also on average twice as fast as urban population with significant consequences for greenhouse gas emissions and climate change [2].

 

Global-Urban-Expansion

Above: Global urban population growth. Data Source: United Nations, World Urbanization Prospects: The 2014 Revision. Image by Morphocode.

Cities were once defined by Jane Jacobs as “problems in organized complexity”. Today, they are seen as engines of innovation and growth on a global scale which explains the general shift in urban planning thought from problems of equity to problems of efficiency [3]. But the problems of cities go beyond mere benchmarking of sustainability indicators. Social and economic issues in cities are what planners call “wicked problems”. Due to their complexity, they remain computationally intractable and cannot be solved in a top-down fashion by a central planner regardless the amount of data available [4].

Cities-smaller-2
Above: Global urban population growth is propelled by the growth of cities of all sizes. Data Source: United Nations, World Urbanization Prospects: The 2014 Revision. Image by Morphocode.

As rapid urbanization and advances in ICT are shaping the course of contemporary culture and society, the “Smart City” agenda is also gaining momentum. Focused mainly on issues of efficiency and optimal performance, this vision of the city suggests that every human action is quantifiable and therefore predictable. A technocratic take on urban governance that often fails to acknowledge the wider social effects of culture and politics shaping the complexities of urban life. Aside from transforming our cities into optimal systems and turning data into a huge commodity market, the smart tech sector has fewer things to say about the importance of civic engagement.

 

Making Data Visible, Accessible and Actionable

Data science can be understood in terms of seven stages: acquire, parse, filter, mine, represent, refine, and interact [5]. The first step, acquire, is associated with an open data release. This is a critical stage allowing civic hackers and data journalists to harness the revelatory power of data repositories. The other six steps, however, remain an impossible leap for the average citizen.  These steps are strongly associated with the practice of citizen-centered design.[6]

In the best case scenario open data is first released in machine readable format, say a .csv file or a .json file. Even then it is rarely usable by the majority of citizens as making sense of it requires a certain amount of technical skills. Few people, even within the city administration, are capable of transforming data repositories into visual elements of spatio-temporal order. This is where the open data movement is still in its infacy. And as we fail to reveal the full potential of open data, more people fail to recognize it as an integral part of their rights as citizens. In order to bridge the gap between open data and civic society data should be made visible, accessible and actionable for a variety of audiences.

Sofia-Building-Permits-2
Above: Mapping building permits in Sofia. Image by Morphocode

Public data is often locked behind proprietary web interfaces. This prevents the re-use of data and stops citizens from exploring, interacting with and making sense of available datasets. This is the case of the Building Permits in Sofia – a public register that keeps track of all recent building permits issued by the municipality of Sofia. While the data is publicly accessible, it is impossible to download or export it in a machine readable format. The raw data is essentially locked behind a single access point – the clunky interface of the web application. This prevents the re-use of data to create maps and visualizations; to ask questionts and search for answers in the data. As we mapped and visualized this single dataset a variety of questions, concerning the built environment emerged: How is the urban landscape changing and what trends are expected in the years to come?;  What are the dynamics of local businessesHow often does public space renovation happen around the city? How is public money spent? etc. (More updates on this project soon).

 

Data Visualization: Revealing Urban Insights

When Scottish engineer and economist William Playfair invented graphical statistics in the end of the 18th century, no one assumed the impact they would have on modern information design. His early attempts to analyse data from England’s import-export statistics at that time are exemplary for their visual literacy and simplicity. The foundations of graphic representation: line graphs; bar charts of economic data; pie charts and circle graphs – all originated at that time and still remain some of the basic elements of data visualization. More recently the rise of data journalism has brought a new light to the importance of information graphics in contemporary culture, where reading habits are shaped by the ubiquity of digital devices. Collecting data is important, but what’s even more important is connecting them to a specific context and revealing networks of interdependencies. And the best way to convey this type of information is through means of visual communication.

 

Pollution

Above: Visualizing pollution patterns. The data is collected from various sensors deployed in 7 cities around the globe and is part of the Data Canvas initiative. Visit project

Visualizing urban data is a critical task as cities continue to dominate global concerns about climate change, economic prosperity and social equity. Interactive visualizations reveal how cities perform and how people interact with the urban environment by exposing the underlying logic of demographic processes, mobility patterns and digitalized daily transactions. In that sense they are the key to maximizing data efficiency and upgrading urban governance to a more open and agile model. As we strive for more compact, connected and coordinated urban growth, visualizing the dynamics of urban processes becomes both an integral part of city governance and an instrument for civic engagement. Urban data has been explored widely across the globe and the resulting outcomes differ in scale and type: from large scale projects for real-time observation such as the IBM Intelligent Operation Center in Rio de Janeiro, to interactive urban dashboards, mobile applications and hackathons.

In all cases the main challenges for generating dialogue through urban data visualizations consist of choosing the right type of visual strategy and achieving high standarts for data accuracy.

 

 

 


 

References:

1. United Nations, Department of Economic and Social Affairs, Population Division (2014). World Urbanization Prospects: The 2014 Revision, Highlights (ST/ESA/SER.A/352).
2. IPCC, 2014: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T.Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
3. Batty, M. (2012). Lecture: Smart Cities & Big Data How We Can Make Cities More Resilient[PDF]. University University College College Dublin
4. Bettencourt, L.M.A. (2013) The Kind of Problem a City is. Santa Fe institute Working Paper. Paper #: 2013-03-008.
5. Fry, B. (2004). Computational Information Design. PhD Thesis, Massachusetts Institute of Technology.
6. Harrel, C.(2013). The Beginning of a Beautiful Friendship: Data and Design in Innovative Citizen Experiences. In Goldstein, B. and Dyson, L.(Eds.). Beyond Transparency: Open Data and the Future of Civic Innovation. San Francisco, CA. Code for America Press.