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flanders - use case 2: City services planning for older people

Using Lift with Wheelchair

Description and goal

For this case we want to offer a combination of two data layers we plan to create. These layers should be easily added to existing datasets or data driven applications:

  • a first data layer shows the age distribution of citizens in a city. The datasets are bundled in statistical zones;

  • a second data layer shows the distribution of people with a physically reduced mobility;

  • the combination of both layers shows where older people with a reduced mobility are concentrated in the city.


With the use of the newly generated map layers, based on historic datasets of a city (source can be local or governmental data), it should be possible to predict how the local demographic distribution of older people with a reduced mobility will evolve in the future by using models. These models will take into account the demographic evolutions, as well as other environmental factors.


Our goal is to provide a set of data layers that help policy makers to decide where to plan new services that are of interest for older people, taking into account historic, actual and predicted data. This goal will be met by overlaying these layers on top of:

  • the location of existing points of interests for older people (primary care, informal care, supermarkets, bakers, pharmacists, shops …);

  • existing applications such as the “Zorgatlas Vlaanderen”.[1]

The Zorgatlas Vlaanderen (Care Atlas Flanders) provides an overview of Flanders' care, well-being, and health information.

Involved persona’s

For the City services planning for older people case, we mainly focus on policy- and decision makers and urban planners.


Our envisioned Urbanage solution can be used to map the service needs for vulnerable older people with a reduced physically mobility. The outcome will help them in the evidence-based decision-making process to improve the actual situation (for instance by increasing the accessibility) or the future situation (for instance by suggesting the best places to plant/build new services).

Expected outcomes

Social goal-related

  • Older people with a reduced mobility are very vulnerable for getting isolated. This group is not always taken into account when new city services are planned. The result can be that city services are not accessible for this particular group, that city services are not adapted to specific needs of people or a consultative process/design considering global population needs (including older people needs) is lacking.

  • This tool can help policymakers, decision makers and urban planners to also take into account older people needs with a reduced physical mobility when planning the integration new city services.

Policy related

  • By adding two layers, and combining them, (with historic, actual and predicted data) on top of the spatial distribution patterns of existing city services, the best solution of the implant of new older people related services can be determined.

  • This target group provides an extra point of view, enhancing the evidence-based decision making. The weight factor of the contribution of the target group will depend on the specificity of the service itself.


Communication/co-creation/co-design related (storytelling, gamification)

  • The outcome of this case can be a starting point for co-creation as well. The best scenarios can be prepared and may be subject of online/offline communication campaigns and are a perfect source for co-creation and co-design. By presenting cases and scenarios, target groups can give feedback, they can vote or they can set priorities making the decision making even more proven.

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