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How well can we reach our daily wants and needs?
Having a supermarket in your neighbourhood can shorten travel distances, reduce traffic, and make it possible to run errands on foot or by bike. This creates more modal options and ultimately improves the conditions for everyday mobility.
mobi.mapr brings the connections between activities and modes to light—for different groups of people and at various geographical scales, from the neighborhood level to the state.
These maps invite you to explore for yourself how transportation works in your area.
Things to Explore
How the analyses can be used
Gauging the quality of daily wants and needs
Accessibility to key everyday destinations such as supermarkets, schools, or medical facilities can be systematically analyzed and compared across neighborhoods. This makes it clear where daily life can be easily managed—and where travel times are particularly time-consuming.
Giving a realistic evaluation of everyday mobility options
Accessibility can be compared across different modes of transportation. This makes it possible to assess which routes are actually feasible—and where certain mobility options are limited.
Establishing a common ground for discussions on mobility
The visualization makes mobility easy to understand and allows for a direct entry into the discussion—even without prior knowledge of urban planning.
Current Analyses and Insights
From local services to leisure activities and social inclusion – mobi.mapr can be used to address a wide range of issues. Here you’ll find the latest posts.
FAQs
mobi.mapr evaluates mobility based on the accessibility of everyday activities—starting from each individual location. The analysis is based on small-scale areas (hexagons) that cover the entire territory of Germany.
For each of these hexagons, the system calculates how long it takes people to reach relevant destinations—such as shopping, work, or leisure activities—using various modes of transportation. In addition to pure travel times, the calculation incorporates realistic factors, such as extra time for parking or differences in the quality of routes.
Instead of considering just a single destination, the three closest options are included and weighted. This results in an average travel time for each hexagon.
This is then compared with similar regions. The result is an index that describes local mobility quality and shows how well mobility functions—and how it ranks in comparison.
Mobility time describes the actual time people need to reach their daily destinations. In addition to travel time alone, it also takes into account additional time spent on activities such as parking or locking up a bicycle. Furthermore, for each combination of location, activity, mode of transportation, and profile, multiple possible destinations are included and weighted against one another. This results in a realistic, everyday-life-based time estimate—not for a single route, but for the typical journey to an activity.
Mobility quality classifies this time: It uses an easy-to-understand rating system to show how well the travel time compares to structurally similar regions.
The rating is calculated exponentially—meaning that differences in short travel times carry more weight than those in longer journeys.
mobi.mapr displays only areas relevant to the analysis of everyday mobility—that is, places where people live or where typical destinations are located.
Areas with no discernible use, such as uninhabited areas, forests, or agricultural land, are therefore grayed out.
To define these areas, mobi.mapr uses population data, which is initially available at a resolution of 1 km² and is then applied to the smaller hexagons. Additionally, data from OpenStreetMap is used to determine where buildings are located. Based on this, the population is distributed within the hexagons.
mobi.mapr uses hexagons to map mobility at a small scale, independent of administrative boundaries. After all, mobility does not stop at municipal or county borders.
The hexagons have a side length of approximately 200 meters, enabling a realistic assessment of local mobility. This reveals differences within cities or regions that often remain hidden when viewed at larger scales.
Administrative boundaries are nevertheless relevant—especially for political and planning decisions. To this end, the results from the individual hexagons are aggregated into larger units such as municipalities, counties, or states and weighted by population.
Both views are available in the tool and switch automatically with the zoom level.
As you explore, you’ll see how mobility works in your area.
Comparing your findings with other regions puts them into a broader context and highlights differences and patterns.