Accessibility — the ease with which individuals can reach needed or desired activities — is a relative measure that varies according to a person's age, health, wealth and preferences.

I developed a tool to evaluate accessibility in urban areas by modeling street networks as graphs, computing metrics like shortest path distances to key amenities (e.g., schools, hospitals, parks) and considering a user's preference of amenities and maximum walking distance. I used OpenStreetMap (OSM), Ordnance Survey (OS) and Office for National Statistics (ONS) data to fetch networks, amenities and urban area boundaries. I implemented a data processing pipeline in Python to find the shortest distance from each 100m² in the urban area to its nearest amenity. I created an interactive dashboard with Typescript and React for users to input their own amenity preferences and maximum walking distance and calculate the personalised scores, presenting the accessibility score data as a heatmap. I analysed Swansea, Cardiff and Bristol and discussed the tool's implications for equitable urban planning. This project integrates geographic information with network science for sustainable urban development.