The 2019 Bicycle Cities Index analyses the conditions for cycling in 90 cities across the globe to determine if they are good for cyclists.

City Selection

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90 cities were selected for their willingness to invest and work on initiatives to improve cycling infrastructure and safety. The study does not reflect the best and worst cities for cycling, but rather evaluates the cycling climate for these 90 cities based on factors related to bike-users.

City Size: S stands for cities with less than 500,000 inhabitants, M for cities with between 500,000 and 999,999 inhabitants and L for cities with 1 million inhabitants and above.

The study focuses on six main categories with the following factors that make a city cycling-friendly:

Weather

Percentage Bicycle Usage.

Crime & Safety: Fatalities / 100,000 Cyclists, Accidents / 100,000 Cyclists, Bicycle Theft Score.

Fatalities / 100,000 Cyclists, Accidents / 100,000 Cyclists, Bicycle Theft Score. Infrastructure: Number of Bicycle Shops / 100,000 Cyclists, Specialised Roads & Road Quality Score, Investment & Infrastructure Quality Score.

Number of Bicycle Shops / 100,000 Cyclists, Specialised Roads & Road Quality Score, Investment & Infrastructure Quality Score. Sharing: Number of Bicycle Sharing & Rental Stations / 100,000 Score, # Shared Bicycles / 100,000 Score.

Number of Bicycle Sharing & Rental Stations / 100,000 Score, # Shared Bicycles / 100,000 Score. Events: No Car Day, Critical Mass Score.

A weighted average was used for all of the factors in order to create the final scores for each category, for example the Weather Score was generated by analysing and aggregating the Hours of Sunshine, Rainfall and Extreme Weather Days of each city.

All of the information collected is based on the latest data available.

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Scoring

Scores are normalized such that 1 represents the lowest and 100 the highest value in the dataset, meaning that the higher the score, the better. However, for the factors Fatalities and Accidents / 100,00 cyclists, a lower value is better as it represents a higher safety rating for each city.

The equation for normalization is as follows: score = 10 * [x - min(X)] / [max(X) - min(X)]; or score inverted = 10 -10 * [x - min(X)] / [max(X) - min(X)] for inverted scores

The formula used for the weighted average, where n is the number of categories, and i is the i-th factor, is as follows: weighted_average: sum_(i=1)^n w_i*x_i, there w_i is the weight of column i, n - total number of columns used for the weighted average, x_i : i-th column.

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WEATHER

The Weather Score was calculated using an aggregated score, taking into account the total annual hours of sunshine, average annual precipitation in millimetres, and the number of weather days below 0 °C and over 30 °C in a city.

Sources: World Weather Online, Weather Base, Deutscher Wetter Dienst, other websites.

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BICYCLE USAGE

Percentage of people using bicycles in everyday life in each city.

Sources: Local statistical departments, Greenpeace, UN, Eco Mobility, The League of American Cyclists, and others.

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CRIME & SAFETY

Fatalities / 100,000 Cyclists

Deaths in bicycle accidents (includes deaths related to bicycle theft) per 100,000 cyclists in cities. Total number of cyclists estimated from bicycle usage rates as well as bicycle ownership rates.

Sources: OECD, local statistical departments. Bicycle ownership rate source: Oke, O., et al., Tracking global bicycle ownership patterns. Journal of Transport & Health (2015).

Accidents / 100,000 Cyclists

An estimate of bicycle-related accidents that resulted in at least light injuries, per 100,000 cyclists. Total number of cyclists estimated from bicycle usage rates as well as bicycle ownership rates.

Sources: OECD, local statistical departments. Bicycle ownership rate source: Oke, O., et al., Tracking global bicycle ownership patterns. Journal of Transport & Health (2015).

Bicycle Theft Score

A weighted average of the following subcategories collected in order to offset the low crime report rates in countries where crime is prevalent but underreported.

Stolen bicycles / 100,000 cyclists

An estimate of stolen bicycle rate per 100,000 cyclists. Total number of cyclists estimated from bicycle usage rates as well as bicycle ownership rates. Sources: local statistical departments. Bicycle ownership rate source: Oke, O., et al., Tracking global bicycle ownership patterns. Journal of Transport & Health (2015).

Homicide Rate

In order to account for low report rates of bicycle theft in some countries, the homicide rate was added as it is the most reported crime.

Source: World Bank.

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INFRASTRUCTURE

Number of bicycle shops / 100,000 cyclists

Total number of bicycle shops within the city. Total number of cyclists estimated from bicycle usage rates as well as bicycle ownership rates.

Sources: the yellow pages, Google search engine result pages, Open Street Maps Overpass API responses. Bicycle ownership rate source: Oke, O., et al., Tracking global bicycle ownership patterns. Journal of Transport & Health (2015).

Specialised Roads and Road Quality

Bicycle roads length per population.

Sources: Open Street Maps Overpass API responses: km of ways (highways) tagged for bicycle usage (allowed and specific). Road Quality score. Source: World Economic Forum.

Investment and Infrastructure Quality

An average of the scored subcategories (country-level for international; investment and infrastructure: city level for German cities):

Infrastructure Investment Score.

Sources: World Bank LPI infrastructure score, German Institute of Economy (DIW): investment in infrastructure, Bertelsmann Stiftung.

Sources: World Bank LPI infrastructure score, German Institute of Economy (DIW): investment in infrastructure, Bertelsmann Stiftung. Infrastructure Quality Score.

Sources: World Economic Forum Global Competitiveness Index Quality of Overall Infrastructure.

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SHARING

Number of bicycle sharing and rental stations / 100,000

An estimate of bicycle sharing and rental stations per 100,000 of population.

Sources: The yellow pages, google search engine result pages, Open Street Maps Overpass API responses.

Number of shared bicycles / 100,000

An estimate of shared bicycle fleet per 100,000 of population.

Sources: Local statistical departments, local bicycle sharing company websites, bicycle share map (http://bikes.oobrien.com).

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EVENTS

No Car Day

Score dependant on the existence of a car-free day, where motorists are encouraged to give up their car for one day. 1 - Has No Car Day. 0 - Does not have a No Car Day.

Critical Mass Score

Average of the subcategories: Size of Critical Mass events attendees.