Measuring Bicycling Infrastructure Across Canada:

Active transportation, such as walking and bicycling to get places, is an important way for Canadians to move through their communities. Active transportation can reduce road congestion and greenhouse gas emissions, and it is also an important way to help Canadians increase their daily physical activity. Physical activity has many physical and mental health benefits, including helping to reduce the risk of chronic disease and improve positive mental health and wellbeing^{Footnote 1}.

The Physical Activity, Sedentary Behaviour and Sleep (PASS) Indicators, is a Public Health Agency of Canada (PHAC) product that consists of a list of key indicators and measures related to these movement behaviours^{Footnote 2}, including active transportation. For example, the PASS Indicators indicate that Canadian adults reported using an active form of transportation for an average of 1.8 hours per week^{Footnote 2}.

Evidence shows that the safer an individual feels on their cycling route, the more likely they are to cycle^{Footnote 3}. This can be particularly true for those who are less confident cycling, and could reduce a barrier for individuals to begin cycling^{Footnote 4}. It is important that bicycling infrastructure is built to keep riders safe. However, not all types of infrastructure provide equal levels of safety^{Footnote 5}. In this update, PHAC applies the Canadian Bikeway Comfort and Safety (Can-BICS) classification system to municipal cycling GIS data in order to capture this distinction in infrastructure and provide a baseline for future measures and indicators.

Bicycling infrastructure in City Name using nomenclature classification system.

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Background

The Canadian Bikeway Comfort and Safety (Can-BICS) Classification System

The Can-BICS describes five categories of cycling infrastructure across three comfort and safety levels. High comfort categories include “cycle tracks”, “bike-only paths”, and “local street bikeways”. Medium comfort includes “multi-use paths”. Low comfort includes “painted bike lanes”. The data blog also presents “non-conforming” infrastructure which is cycling infrastructure that the city has identified, but which is not classified as sufficiently comfortable to be included in Can-BICS, as well as “not classified” infrastructure which is infrastructure that could not be definitively classified. The categories are further described by Winters, et. al^{Footnote 6}. For each of the 30 cities listed above, the cycling infrastructure classified by each city, based on their own reported infrastructure, is included as well as the corresponding Can-BICS category. The city total infrastructure equals the Can-BICS infrastructure “plus” the non-conforming and the not classified categories. In some cases, the cities identify more infrastructure than can be classified as safe and comfortable under Can-BICS.

Open-Data

Open-data refers to data that is free to access, use, modify, and share^{Footnote 7}. A growing number of Canadian municipalities have created accessible open-data portals that include the location and types of bicycling infrastructure. These open-data datasets are rich sources of information that can be leveraged for many uses, including public health. The first edition of this data blog demonstrated the potential of open-data to report bicycling infrastructure using the many classifications created by 26 cities. However, it was difficult to compare across cities because the labels used to classify infrastructure types were not consistent.

This second edition applies the Canadian Bikeway Comfort and Safety (Can-BICS) classification system^{Footnote 6}. The Can-BICS classification is a Canadian standard naming convention for cycling infrastructure that reflects user comfort and safety and allows measuring cities’ cycling infrastructure in a way that is comparable across different types of infrastructure and comfort levels.

This comparable data is key to establish a method of measuring cycling infrastructure in sentinel cities that can be monitored over time. In this update, data from four additional cities was added to the datablog. The datablog now includes data from every province, and includes cities that account for 44% of the Canadian population. Work is progressing to add territorial cities in the future.

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Takeaways

• There is a wide diversity of cycling infrastructure, and a wide variety of naming conventions that differ from city to city.
• For high comfort infrastructure, the most common type of infrastructure is cycle tracks (high comfort); however, multi-use pathways (medium comfort) and painted bike lanes (low comfort) predominate in most cities.

Limitations

• The publication date of each dataset varied by municipality, the earliest being from June 2013 and the latest from August 2018 with the exception of Halifax, St. John’s, Charlottetown, and Saskatoon which range from 2016 to 2022. The age of some of the data means that new infrastructure may not be reflected.
• Applying the Can-BICS classification to publicly available cycling infrastructure data is currently carried out using visual inspection of segments of city defined infrastructure to assign a Can-BICS category. Therefore, reviews done independently may lead to some difference in classifications on account of reviewer variability and choice of different infrastructure segments to inspect and classify.
• This current data blog is intended to establish baseline data. Future changes in kilometers of reported infrastructure may result from:
  1. newly constructed infrastructure.
  2. more consistent application of infrastructure standards by cities
  3. greater standardization of coding methodologies for Can-BICS coders.
  Over time, variability due to ii) and iii) should diminish as classifying infrastructure becomes more established.
• Caution should be exercised in comparing cities and their infrastructure given differences in both population and population density. More populous cities have more resources to build infrastructure, and more densely populated cities have more efficient use of infrastructure. The more important comparison will be to examine changes within the same city over time. By establishing this baseline data, cities can even now use the data to highlight upgrades to their networks since our provided dataset dates.

Conclusion

Although there is a long history of building cycling infrastructure, classifying this infrastructure with a consistent and comparable nomenclature is a recent innovation. PHAC is still in the early stages of applying classification methods of this sort to administrative data provided by Canadian communities. Development of Can-BICS and the use of open data as presented in this tool will help support consistent monitoring of active transportation infrastructure across Canada and provide a new tool to understand this important determinant of daily physical activity. Work continues to update Can-BICS data with new data forthcoming from Statistics Canada and Housing, Infrastructure and Communities Canada and ongoing work at the Cities, Health & Active Transportation Research Lab.

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