A project by Team MAPM for the "Map your world!" mapathon by HERE Maps.
We won 3rd place! Our final elevator pitch can be viewed here.
Follow this link to view our map: https://maawoo.github.io/Project_MAPM/
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Imagine you move to a new city and you have no idea about the different districts and what they have to offer in terms of culture, nightlife, accessibility to public transport and so on. With this map we want to give people the tool to Find the Right Place for their new home! (...at least if they want to move to Jena, Germany 😉)
Several public datasets containing factors for the attractiveness of urban spaces were combined to generate one simple to use map indicating the neighborhood of highest comfort for each individual.
In the Layers tab, single layers can be viewed. The features of each layer are selected using reasonable filters in order to portray only those features affected by the selected parameter. Generally, the darker the display color, the stronger this feature is influenced by the specified parameter. Either negatively (e.g. in case of noise pollution) or positively (e.g. in case of proximity to nature).
In the Use Cases tab, different scenarios have been precalculated based on different parameters. In a later update, we want to give the user more freedom to explore the data and visualize his/her own preferences on the map.
Julia is a young university student, who is going to move to Jena with her dog. She loves nature and additionally her dog needs to be close to green spaces to feel comfortable. Since Julia regularly travels, she would also like to be close to public transport without having to suffer from any noise pollution. Parameters used:
- distance to Nature (+)
- distance to Public Transport (+)
- Noise Pollution (-)
Peter loves to party and enjoys going out with friends. He studies at the local university but strongly dislikes getting up early. Noise doesn't bother him too much though. Parameters used:
- density of Restaurants (+)
- density of Nightlife (+)
- distance to University (+)
Anna and Klaus are a middle-aged couple and both work full-time. They like arts and theater and often spend the evening with a good meal in a restaurant and a stage play or concert afterwards. But because Anna works for an international company, she needs to be close to public transport as well. Parameters used:
- density of Culture (+)
- density of Restaurants (+)
- distance to Public Transport (+)
The Schiller family consists of Mum and Dad with their two teenage daughters. The daughters love shopping in their free time but their parents rather enjoy some peaceful quietness. Also, the mum has a strong pollen allergy and wants to live far from any trees. Parameters used:
- density of Shops (+)
- Noise Pollution (-)
- distance to Nature (-)
By clicking on a building in the map, a Pop-Up will show up which contains exact information about all attributes for the selected building.
The main source of our data is OpenStreetMaps. Using R scripts, we extracted building polygons for the city of Jena and did calculations for each of these polygons. On the one hand, distances to some features were calculated (e.g. distance to nature) and on the other hand we counted features (e.g. restaurants) in a certain perimeter surrounding the polygon.
We also included publicly available noise data from the Thuringia state government and the German Railway. The noise dataset was calculated after EU regulations at a height of 4 m above ground.