Findings

Switzerland

In the data for whole Switzerland, a constant increase in the number of kilometres travelled per person per day can be observed between 2000 and 2015. This indicates that total mobility per capita has grown during this period. Most of this increase has taken place in the public transport sector, which means that the Modalsplit of public transport has also increased. In 2021, however, the total number of kilometres per person per day as well as the Modalsplit of public transport have decreased. This may be mainly due to the Covid-19 pandemic, which had led to a reduced mobility behaviour in the general public, but also to a reduced use of public transport for the remaining kilometres. At the same time, there is a slight increase in walking and cycling, which might also be due to the pandemic as people discovered those modes of transport as alternatives with a low infection risk.

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Cantons

As Modalsplit data on a cantonal level is only available for the year 2021 in the dataset we used, there is no timeline for the development of Modalsplit within the cantons. Nevertheless, the data allows us to compare the mobility behaviour between the different cantons. By doing so, we need to bear in mind that the 2021 data seem to be influenced by the Covid-19 pandemic and that, according to the findings in the timeline for whole Switzerland, especially public transport use seems to have been significantly lower in 2021 compared to normal years without pandemic.

For the number of kilometres travelled per person per day, we can see that the cantons with the largest distances, Uri and Fribourg/Freiburg, are both cantons with a high number of outgoing commuters to somewhat more distant urban areas such as Lausanne and Bern for Fribourg/Freiburg or Luzern and Zug for Uri. The cantons with the lowest daily travel distance are Basel Stadt and Genève, which are both densely populated urban areas that offer everything their population needs within a short distance. As both of these cantons have a rather small area, a comparably high proportion of commuters might be incoming commuters from other cantons and countries.

In terms of Modalsplit, a trend to higher public transport use in urban areas is visible since Basel Stadt, Zürich, Bern, Genève, and Basel Landschaft belong to the cantons with the highest Modalsplit of public transport. For walking and cycling, there are little visible trends in the graph, except for Basel Stadt, where walking and cycling are significantly more popular than in any other canton. This might again be due to the small area of the canton, but also to better cycling infrastructure compared to other cantons. The cantons with the lowest share of walking and cycling are Fribourg/Freiburg, Jura and Valais/Wallis, which might be due to the low population density in these cantons.

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Greater Regions

Espace Mittelland

Espace Mittelland greater region is characterised by urban, rural, and mountainous areas.

The travelled distance per person per day shows the same trend as for entire Switzerland: constant growth of kilometres travelled per person per day from 2000 to 2015, followed by a dip due to the covid-19 pandemic. Compared to entire Switzerland, however, more of this growth has taken place in the sector of motorised individual traffic, especially from 2000 to 2005. The Modalsplit of public transport, which is now roughly around the Swiss average, has even slightly decreased from 2000 to 2005.

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Nordwestschweiz

Nordwestschweiz is mainly dominated by urban areas of the city of Basel and its surroundings. In the cantons of Basel-Landschaft and Aargau, there are also some more rural areas though.

The travelled distance per person per day shows the same trend as for entire Switzerland: constant growth of kilometres travelled per person per day from 2000 to 2015, followed by a dip due to the covid-19 pandemic. As in entire Switzerland, most of the growth has taken place in the public transport sector, which is showed by the growing Modalsplit of public transport until 2015. In 2015 and 2021, the Modalsplit of public transport is slightly above the Swiss average.

images/Modalsplit Nordwestschweiz 2000-2021(absolut).png images/Modalsplit Nordwestschweiz 2000-2021(percent).png


Ostschweiz

Ostschweiz greater region is characterised by rural and mountainous regions, but also has some urban centres such as St. Gallen.

The travelled distance per person per day shows the same trend as for entire Switzerland: constant growth of kilometres travelled per person per day from 2000 to 2015, followed by a dip due to the covid-19 pandemic. As in entire Switzerland, most of the growth has taken place in the public transport sector, which is showed by the growing Modalsplit of public transport until 2015. In 2015 and 2021, the Modalsplit of public transport is roughly around the Swiss average.

images/Modalsplit Ostschweiz 2000-2021(absolut).png images/Modalsplit Ostschweiz 2000-2021(percent).png


Région Lémanique

Région Lémanique is dominated by the densely populated urban areas along the northern shore of Lake Geneva, with the major cities of Geneva and Lausanne. The regions further away from the lake and the canton of Valais are, however, more rural and mountainous regions.

In the Régon Lémanique greater region, the travelled distance per person per day does not show the typical pattern of growth until 2015. Instead, there was a dip not only in 2021, but also in 2005. The re-growth of mobility after this dip has primarily been taken by public transport, which is shown by the increasing Modalsplit of public transport. Motorised individual traffic has been slightly above Swiss average in 2015 and 2021, while public transport has been slightly below Swiss average in the same years.

images/Modalsplit RégionLémanique 2000-2021(absolut).png images/Modalsplit RégionLémanique 2000-2021(percent).png


Ticino

In the greater region of Ticino, there are urban, rural and mountainous regions.

In Ticino, the travelled distance per person per day has remained stable from 2000 to 2005, before shooting up to a higher level in 2010 and the typical dip due to the covid-19 pandemic in 2021. Ticino is the only greater region that shows a significant decrease of the public transport modal split not only in 2021, but also from 2000 to 2005. It has only recovered to 2000 level in 2015, before dipping in 2021. We don’t know the reasons for this decreased use of public transport after 2000. A possible reason for this anomaly might have been the poor reliability of trains in Ticino due to delayed international trains on the Gotthard railway line. In 2015 and 2021, Modalsplit of public transport is still below the Swiss average. However, since the level of public transport service in the whole region has been significantly improved by the opening of the Ceneri base tunnel in 2020, this might change in the future.

images/Modalsplit Ticino 2000-2021(absolut).png images/Modalsplit Ticino 2000-2021(percent).png

Zentralschweiz

Zentralschweiz greater region is mainly characterised by rural and mountainous areas, but also has some medium sized urban areas around the cities of Lucerne and Zug.

The travelled distance per person per day shows the same trend as for entire Switzerland: constant growth of kilometres travelled per person per day from 2000 to 2015, followed by a dip due to the covid-19 pandemic. As in entire Switzerland, most of the growth has taken place in the public transport sector, which is showed by the growing Modalsplit of public transport until 2015. In 2015 and 2021, the Modalsplit of public transport is slightly below the Swiss average.

images/Modalsplit Zentralschweiz 2000-2021(absolut).png images/Modalsplit Zentralschweiz 2000-2021(percent).png


Zürich

Zurich greater region is dominated by urban areas of Zurich city and its surroundings. Even the rural areas of this greater region are more urbanized compared to the rest of Switzerland.

The travelled distance per person per day has also increased in the Zürich greater region from 2000 to 2010. In 2015, however, a slight decrease occurred, followed by the typical decrease caused by the pandemic in 2021. The 2015 decrease in total travel distance is mainly due to a decrease in motorised traffic, but also to a slight decrease in public transport use. The Modalsplit of public transport, however, is significantly above the Swiss average in 2015 as well as 2021.

images/Modalsplit Zürich 2000-2021(absolut).png images/Modalsplit Zürich 2000-2021(percent).png



Conclusions

There are 3 major trends in terms of mobility and Modalsplit shown by the data for entire Switzerland and for most greater regions:

  1. The demand of mobility per capita has risen between 2000 and 2015. This trend has been temporarily halted by the covid-19 pandemic in 2021 but could continue in the future.
  2. Modalsplit of public transport and walking and cycling tend to increase slightly, while motorised traffic is decreasing slightly. This trend has also been temporarily halted by the covid-19 pandemic but might continue in future. Motorised traffic, however, still remains the most used mode of transport in all regions and cantons.
  3. There is also a slight trend showing that public transport and walking and cycling are more popular in urban than in rural areas. This finding, however, should be treated with caution, as there is no data for urban, rural or mountainous regions only, but all greater regions consist of different areas with different characteristics.

In data of the next micro census survey, which is scheduled for 2025, it will be interesting to see whether the trends from before 2021 will continue or whether the pandemic has led to lasting changes in mobility behaviour.




Discussion

Considerations & limitations

We designed our map with user-friendliness and inclusivity in mind. One big focus was therefore on colour blindness. This was tested with digital tools as well as users. Another focus was the access to a broad audience. We wanted our map to be useful and interesting for many different users. Therefore, some information is easily accessible and the map is fun to explore on a basic level. Still, complex statistics can be done by users who spend some time to understand the complex features of the map. Some of those features may be slightly hidden but not for users who are familiar with similar tools. Simultaneously, these features are not distracting or a visual overload. Our map should be simple, show the necessary and be visually pleasing.

A limitation of the map is that it is best used on a computer and not a mobile phone. Some of the features, like hovering over graphs, can be done easiest with a mouse pad. Last but not least, our map as well as our website is created for a certain screen size. Consequently, we paid attention for it to show as a whole with all bottoms accessible as well as the map and graphs being readable on these specific screens.

Possible improvements

After the creation of the map, we ran some tests with a diverse user sample. We let them go through the map while we observed their behaviour. Simultaneously, they were allowed to ask questions and give suggestions.

One of the suggestions we were not able to implement due to technical limitations within ArcGIS Experience Builder was a more interactive map surface. Some users did not naturally understand the interactivity of the map. Therefore, some reaction like lightening up while you hover over the map would have been desirable. The implementation of this function would not have been possible within our given timeframe.

Additionally, we would have loved the map to load faster so that comparisons between the years became easier. To do so we already simplified the map and deleted unnecessary features, but it is still slow.

Finally, we would have loved to fix the selection of specific regions as you switch between years (also showing the graphs). This is possible but afterwards you cannot select another pie chart anymore in other years. Meaning you have to go back to the original year, where the feature was selected, to clear the selection. Adding to that we would have liked to keep all the pie chart on the map when selecting one. The source of this problem was that we needed a filter function for the bar charts to adapt. The selection and the filter functions worked against each other, and we did not yet find a solution for that.

From a data perspective, it would be interesting to see if pre-Covid trends hold true when incorporating the next microcensus dataset. Additionally, we would have loved to have access to more years on a cantonal level.