#Data-driven #DataVisualization #Mapping #Emotion #Ambience


Street Life Map

; Adding an emotion layer on the urban area

Harvard Graduate School of Design | 2019
Advisor: David Malan (CS50)
Team:
CY Chang, Shikun Zhu
Duration:
1 month
Role:
Ideation, research, data collection, implementation
Tools:
Mapbox API(JavaScript), Urban Network Analysis(Rhino)
︎ Interactive Prototype










> How might we improve the urban experience for the people who barely know the area? 


















| Problem | 
Visitors, travelers, or newcomers often have a hard time understanding the neighborhood’s ambience just as looking at the maps.

| Goal |
Encouraging people to explore the city and improve their urban experience 







>> A new way of visualizing urban street ambience by measuring the intensity of social activities that may happen on the streets










How it works





| Accessibility to Scores |

The scores are calculated based on certain types of geospatial point (POI) data
e.g., catering, leisure, shop, and tree cover ratio











| Scores to Line Weight |

Each street’s scores are normalized and converted to line weights to represent the intensity.











Prototype














︎ Interactive Prototype

















copyright. Eunsu Kim | 2020