Colin Ferster’s research while affiliated with University of British Columbia and other places

Walking is a healthy, sustainable, and economical form of transportation or recreation. Yet in North America walking is not always accessible, safe, or comfortable. A challenge to creating quality pedestrian environments is lack of data on what barriers exist and how barriers vary across communities. Our goal is to characterize pedestrian barriers and concerns at the microscale level. We analyzed 2,588 reports of hazards, missing amenities, or incidents from WalkRollMap.org , a crowdsourced webmap of barriers to walking or rolling. We assigned themes related to actionable infrastructure interventions and summarized data by location, walkability, street type, and characteristics of who reported it (age, gender, and self‐reported disability). Most reports were related to crossings (45%), sidewalk quality (29%), and the volume and speed of cars (13%). Reports were more common in more walkable places (likely related to exposure) and on major roads. People living with a disability reported sidewalk concerns at a higher rate than others, while people over 75 years of age were more likely to identify issues related to the volume and speed of cars. Cities should prioritize risk reduction interventions for pedestrian road crossings and sidewalk improvements, especially on major roads in amenity dense walkable places.

Walking is a simple way to improve health through physical activity. Yet many people experience barriers to walking from a variety of physical, social, and psychological factors that impact their mobility. A challenge for managing and studying pedestrian environments is that barriers often occur at local scales (e.g., sidewalk features), yet such fine scale data on pedestrian facilities and experiences are often lacking or out of date. In response, our team developed WalkRollMap.org an online mapping tool that empowers communities by providing them with tools for crowdsourcing their own open data source. In this manuscript we highlight key functions of the tool, discuss initial approaches to community outreach, and share trends in reporting from the first nine months of operation. As of July 27, 2022, there have been 897 reports, of which 53% served to identify hazards, 34% missing amenities, and 14% incidents. The most frequently reported issues were related to sidewalks (15%), driver behavior (19%), and marked crosswalks (7%). The most common suggested amenities were sidewalks, marked crosswalks, connections (i.e., pathways between streets), and curb cuts. The most common types of incidents all included conflicts with vehicles. Data compiled through WalkRollMap.org offer unique potential for local and timely information on microscale barriers to mobility and are available for use by anyone as data are open and downloadable.

High-quality and consistent cycling infrastructure data are needed to advance research into equity and safety and for planning active transportation. With recent growth in cycling and investments in cycling infrastructure, there are concerns that these investments have not been equitable across communities. There is no consistent and complete national dataset for cycling infrastructure in Canada. Our goal is to develop a national cycling infrastructure dataset by (1) classifying OpenStreetMap (OSM) using the Canadian Bikeway Comfort and Safety Classification System (Can-BICS) as consistent criteria and categorisation for comfort class and infrastructure type; (2) performing a site-specific accuracy assessment by comparing the classification with more than 2000 reference points from a stratified random sample in 15 cities; and (3) presenting summary results from the national dataset. Based on reference data collected in 15 test cities, the classification had an estimated accuracy of 76 ± 3% for presence or absence of infrastructure, 71 ± 4% for comfort class and 69 ± 4% (by length) for infrastructure type. High comfort infrastructure was slightly underestimated (since bike paths were sometimes confused with multi-use paths) and low comfort infrastructure was slightly overestimated. Nationally, we identified 22,992 km of cycling infrastructure meeting Can-BICS standards and 48,953 km of non-conforming infrastructure. Multi-use paths are the most common infrastructure type by length (16.6%), followed by painted bike lanes (11.0%), and then high comfort infrastructure (cycle tracks, local street bikeways and bike paths) (4.3%). There was a wider range in access to cycling infrastructure in small cities than in medium and large cities. To reduce repeated effort assembling data and increase reproducible active transportation research, we encourage contribution to OSM.

Background: The lack of consistent measures of the cycling environment across communities hampers cycling research and policy action. Our goal was to develop the first national dataset in Canada for metrics of the cycling environment at the dissemination area (DA) level - the Canadian Bikeway Comfort and Safety (Can-BICS) metrics. Data and methods: The Can-BICS metrics are area-level metrics based on the quantity of cycling infrastructure within a 1 km buffer of the population-weighted centroid of DAs. The base data are a national cycling network dataset derived from OpenStreetMap (OSM) (extracted January 25, 2022) and classified by high-, medium- and low-comfort facilities. A Can-BICS continuous metric (sum of cycling infrastructure per square kilometre weighted by comfort class) and Can-BICS categorical metric were derived and mapped for all 56,589 DAs in Canada. The Can-BICS metrics were correlated with other national datasets (2016 Canadian Active Living Environments [Can-ALE] and 2016 Census journey-to-work data) to test for associations between Can-BICS and related measures. Additionally, city staff were engaged to provide feedback on metrics during the development phase. Results: One-third (34%) of neighbourhoods in Canada have no cycling infrastructure. According to the categorical measure, 5% of all DAs were assigned as the highest category of Can-BICS (corresponding to 6% of the population) and were nearly all within metro areas. The Can-BICS continuous metric had low correlation with bike-to-work rates (R = 0.29) and was more strongly correlated with sustainable-transportation-to-work rates (R = 0.56) and the Can-ALE metrics (R=0.62). These correlations were variable across cities. Interpretation: The Can-BICS metrics provide national research- and practice-ready measures of cycling infrastructure. The metrics complement existing measures of walking and transit environments (Can-ALE), collectively providing a cohesive set of active living measures. The datasets and code are publicly available, facilitating updates as new infrastructure is built.

Cities are making infrastructure investments to make travel by bicycle safer and more attractive. A challenge for promoting bicycling is effectively using data to support decision making and ensuring that data represent all communities. However, ecologists have been addressing a similar type of question for decades and have developed an approach to stratifying landscapes based on eco-zones or areas with homogenous ecology. Our goal is to classify street and path segments and map streetscape categories by applying ecological classification methods to diverse spatial data on the built environment, communities, and bicycling. Piloted in Ottawa, Canada, we use GIS data on the built environment, socioeconomics and demographics of neighborhoods, and bicycling infrastructure, behavior, and safety, and apply a k-means clustering algorithm. Each street or path, an intuitive spatial unit that reflects lived experience in cities, is assigned a streetscape category: bicycling destination; wealthy neighborhoods; urbanized; lower income neighborhoods; and central residential streets. We demonstrate how streetscape categories can be used to prioritize monitoring (counts), safety, and infrastructure interventions. With growing availability of continuous spatial data on urban settings, it is an opportune time to consider how street and path classification approaches can help guide our data collection, analysis, and monitoring. While there is no one right answer to clustering, care must be taken when selecting appropriate input variables, the number of categories, and the correct spatial unit for output. The approach used here is designed for bicycling application, yet the methods are applicable to other forms of active transportation and micromobility. ARTICLE HISTORY

We conducted a case study to assess the validity of community science (Yelp, OpenStreetMaps) and commercial (DMTI) food outlet datasets. We compared counts of food outlets from 13 street segments in Vancouver and Montreal to Google Street View. We found that OpenStreetMaps correctly identified the most outlets in both cities and DMTI consistency overcounted outlets. In Vancouver, we assessed validity by outlet type, again OpenStreetMap performed the best overall but largely missed grocery stores, and Yelp did not include convenience stores. Results provide insights into using different commercial and open-source datasets to measure food environments.

Safety concerns are a barrier to increasing bicycling. BikeMaps.org, a tool for crowdsourcing bicycling collisions, near misses, and falls, offers rich data on local bicycling safety concerns. Our goal is to characterize dominant bicycling safety issues reported in nine Canadian cities. We analyzed 2,513 BikeMaps.org reports (522 collisions, 151 falls, 1840 near misses), and summarized the types of incidents reported, ratios of near misses to collisions by incident type and by city, and injuries resulting from various types of crashes. Incidents categorized as a ‘dangerous pass, overtake at midblock’, were most commonly reported and had the highest ratio of near misses to collision reports (9:1). Cities with a high commute mode share for bicycling had lower near miss to collision reporting ratios. Overall, 40.3% of reported collisions or falls required medical treatment. Incident types with the most severe outcomes were ‘left cross at an intersection’ (58.4% reported needing medical treatment); ‘vehicles failing to stop at intersection or yield to bike’ (54.0%); and ‘multi-use paths, vehicle conflicts at intersection’ (48.5%). Mitigating conditions leading to real or perceived concerns over dangerous passes by vehicles should improve bicycling comfort. Bicycling injuries will be reduced by safety improvements at intersections including those with multi-use paths.