*THIS ARTICLE IS AUTOMATICALLY TRANSLATED, AND MIGHT INCLUDE TRANSLATION MISTAKES.
The activity-tracking app Strava was used by approximately 700,000 cyclists in the Netherlands in 2023, making it the largest tracker for cyclists. Although road cycling, mountain biking, and running are the primary activities for most users, many commuting trips are also recorded. Since 2021, Strava has provided free access to anonymized and aggregated route data from cycling and running users. Governments can gain access to data within their district under strict privacy conditions (more information: Track Landscapes privacy policy and Strava privacy policy).
Strava data was recognized by the Province of Utrecht as a potentially valuable source of cycling data for regional cycling policy. In 2022, we (Track-Landscapes + Arcadis) explored this potential by combining Strava analyses for the province of Utrecht, examining both recreational and utilitarian cycling use. In 2023, we continued this research with three goals/parts:
Gaining insight into the representativeness of utilitarian cycling data;
Reflecting on the regional cycling network and the ambitions of the implementation program;
An overview of the effects of cycling investments between 2019 and 2023 on Strava usage.
In this article, we describe five ways in which, according to our findings, Strava data can be useful for regional cycling policy:
Understanding travel patterns;
Reflecting on various route networks;
Integrating the interests of diverse users of the cycling networks;
Gaining insight into missing links;
Input for traffic safety.
1. Putting Yourself in the Movement: A Means for Discussion, Reflection, and Justification of Upgrading Cycling Routes.
In 2022 and 2023, work sessions were organized with cycling experts from various organizations, where Strava maps of both utilitarian and recreational cycling flows were central. These maps strongly appeal to professionals in the fields of mobility, spatial planning, and recreation because they provide a clear overall picture of actual cycling trips undertaken.
They provide insight into how people experience routes, with aspects such as continuity, logic, and attractiveness, which are often difficult to fully capture in traffic models.
Although Strava data is not a replacement for traffic models or local counts, it adds an important human element that traditional data often lacks. While models are more anonymous, Strava data allows for lively discussions about the logic and intensity of existing cycling routes and the desirability of new or improved routes. Strava provides valuable insights into long-distance cycling and recreational cyclists, but it should not be seen as representative of all utilitarian or recreational cycling traffic.
However, these maps can be very useful for substantiating cycling investments. Based on the displayed cycling flows, arguments can be made about the cycling experience, network logic, and the potential value of certain interventions. This can relate to both improving existing routes and advocating for new connections.
In the 2023 work session, the focus was on two specific areas: Utrecht-Zeist-Bilthoven and Amersfoort-Leusden-Woudenberg. Local experts were present, who used their knowledge of the area and cycling routes to more specifically interpret the Strava data. In this way, Strava usage patterns were compared with the perceived quality of cycling routes (width, surface, safety) and usage from personal experience or other counts.
In addition, local cycling officials often have cycling measures on their wish lists that have not yet been implemented. The Strava data helps them to better substantiate these plans with factual insights into cycling and walking flows. Visual overview maps of those flows not only clarify the arguments but also work convincingly for decision-making.
2. Reflecting on Different Types of Route Networks: Confirmation, Surprise, and Attention Through Broad Overview.
The strength of Strava Metro is that it can display cycling flows of two different cycling types on a large scale and separately, for example, at the provincial level. The map below shows the utilitarian cycling flows on all paths and roads in the province of Utrecht, based on routes included in OpenStreetMap. The main concentration of usage is around Utrecht and Amersfoort.
Since this article is public, the data is presented in percentages rather than absolute numbers. The legend shows the percentage of the most trafficked path in the province (Biltsestraatweg), with ‘several tens of thousands’ of passages annually. Routes with ‘thousands’ of passages per year can be found in all work and residential areas. The exact figures are available in the working documents and GIS maps for the province.
An overall view like this map can reveal forgotten or overlooked routes. The maps then act as a 'wake-up call'. In work sessions, several routes were identified as being surprisingly highly used or underused. In both cases, the Strava cycling maps can lead to a refinement of the importance of different routes.
However, the overall usage view (350,000 lines) can also be overwhelming and therefore difficult to interpret. It is thus useful to filter or mask the cycling flow maps, for example, based on specific networks. This makes it visually easier to show only the roads that achieve at least 5% of the utilitarian Strava passages per year.
Such a view is, for example, easier to compare with the preliminary choices for cycling routes in the Province; are the current or planned cycling routes heavily used?
We can also turn it around: are certain routes perhaps more important than we previously thought? We have overlaid the planned cycling routes as a white layer over the Strava cycling flows. The colored lines that remain visible are not planned cycling routes but are still heavily used.
There are many routes that we have classified into three types:
Direct core connection routes: For example, the Koningsweg and Koeweg near Bunnik (1a), the Hilversumsestraatweg between Baarn and Hilversum (1b), or the route between Amersfoort and Soest via the Maleburg (1c).
Green alternatives: Routes with an attractive green character that are often also the shortest way to residential areas, but the green character may play a role in their use. Examples include the routes along the Vecht between Breukelen and Maarssen/Utrecht (2a), the Groenedijk and Lindenlaan between Utrecht and Hilversum (2b), or the routes through the Korte and Lange Duinen as a green alternative to the Birkstraat or Soesterbergsestraat between Soest and Amersfoort (2c).
Ring routes: The current cycling routes are mostly radial, focused on the major centers, but many cycling flows follow a tangential ring movement. People avoid the central city and choose alternatives through less urban, greener environments. Examples include the route along Fort Vechten above Houten towards Nieuwegein (3a) and the route around Amersfoort, along the 'de Wieken' business park, to Leusden and the Treekerweg (3b).
These ring movements emphasize the importance of a continuous cycling network in various directions, not just radial. Tangential routes often encounter barriers and missing connections, as large infrastructures and waterways have developed mainly radially around cities.
Comparisons have been made in various other ways between Strava utilitarian cycling flows and certain types of networks:
Strava utilitarian cycling vs. the regional cycling network; which routes are not yet part of the RFN but are heavily used?
Strava utilitarian cycling vs. separated cycling paths; on which cycling paths is the congestion the greatest? How wide/narrow are these paths?
Strava utilitarian cycling vs. the recreational node network; aren’t the ‘recreational’ routes also heavily used for utilitarian purposes?
3. Integrating the interests of various ‘other’ users on the cycling networks: sportive cyclists, walkers, and runners.
The utilitarian cyclist is often seen as the main user of the cycling network, but Strava data shows that many other types of trips take place. This usage by different groups often overlaps more than expected. The sporty Strava cycling data offers the opportunity to also take into account the interests and needs of recreational cyclists. Where can we consider recreational cyclists in the design of cycling routes? And can recreational use be an additional argument for improving routes?
However, the biggest 'eye-opener' of the 2023 work session was the Strava walking data (recreational walking and running). This was seen as a very valuable addition. While we already have some insight into cycling flows through counts and models, this is still completely lacking for walking flows (see this article for more information).
Strava data shows that there is a lot of recreational walking on certain cycling paths and roads. Where does this lead to conflicts? Is a separate walking facility desirable? Or can the importance of walkers be used to prioritize missing links or route improvements? This would benefit both groups of users.
The maps below show the walking and cycling flows in the Amersfoort-Woudenberg region, the focus area of the work session, with various discussed observations of heavily or lightly used routes. For example, the Valleikanaal (1), routes around the Groene Zoom (2 & 3), and city-to-country connections at the edge of Amersfoort (4).
4. Clear Visual Insight into Missing Links.
By looking at the total cycling and walking flows, missing connections become immediately apparent. In the image above, several potential or discussed desired connections are indicated with dotted lines.
Based on the existing flows, it is easy to reason where a new connection would be a valuable addition. This is often visible when the intensity of use does not flow directly between locations, but there is a lot of "detour" cycling. We aim to make the lines where usage converges as continuous as possible. The slide below highlights one of the many missing links with great potential for both cyclists (recreational and utilitarian) and recreational walkers (between Soest and Baarn):
The diversity of users, as highlighted by Strava data, is an important factor here. A new bridge, tunnel, or connection through a rural area is most valuable when it serves different types of users. This increases the likelihood of getting the connection on the implementation agenda.
5. Input for traffic safety challenges
With colleagues from the province, an initial exploration was conducted on the question: what value can Strava Metro data have for traffic safety in cycling and walking? In order of potential:
Road cyclists: cycling flows and speedStrava Metro provides insight into the route usage of road cyclists, who are often involved in accidents (falls, collisions with other cyclists, or motorized traffic). Both the volume and speed can help identify roads where the safety of road cyclists requires extra attention.
Utilitarian cycling flows, also in the cityOn busy cycling routes, safety is crucial. Outside the city, Strava cycling flows can provide insight into total congestion, while within the city, routes with a lot of regional traffic, which often travels faster, can be identified. This may indicate routes with significant speed differences between cyclists.
(Running) on shared roadsStrava walking flows show where a lot of walking occurs on bike paths or roads. Here, extra attention to safe space for walkers and runners is important.
Utilitarian cycling speedsStrava utilitarian cyclists are usually fast cyclists. The data can show where high speeds occur. For example, on the Woudenbergseweg, cycling is exceptionally fast. This route leaves much to be desired in terms of traffic safety. It seems to be a result of both the slight slope and the presence of relatively many fast-moving Strava users.
Additional and Refining
In our view, Strava data does not provide a definitive answer as to which route is best chosen for a cycling investment or upgrade (e.g., to a fast cycling route). Firstly, because usage potential, rather than current usage, is often the most important criterion for such decisions. Secondly, because Strava does not represent all types of cyclists or walkers.
However, for those aware of this, Strava data offers excellent possibilities for thinking about route potentials, conducting discussions, and justifying choices based on the interests of different user groups in the city and the countryside. In the province of Utrecht, Strava data is used in this way: as a supplementary and refining analysis alongside other forms of cycling data, inventories, and criteria for cycling investments.
And although this is already a lot, we continue to see new applications emerging based on this usage data. We remain fully engaged with this. One of these is discussed in article 3: monitoring and evaluating cycling measures.
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