Public Transport Accessibility Analysis

Objective:

This project was designed to enhance the accessibility of public transportation in the neighborhoods of Toumpa and Ano Poli in Thessaloniki. The focus was on using geospatial data analysis to understand how easily people can walk to their nearest bus stops.

Methodology:

Analysis

1. Data Collection: The data was collected from OpenStreetMap using the OSMnx Python library, which included information about buildings, streets, and bus stop locations.
2. Data Processing: The data was cleaned and organized to ensure it was accurate and usable for analysis. Python scripts were employed to align all data to a common format for detailed examination.
3. Network Analysis: Calculated the shortest walking routes to bus stops by connecting buildings to the closest points on the walking network, determining the most efficient paths for pedestrians.
4. QGIS Application: QGIS was used to produce static maps that visually represent the data and analysis results, providing clear geographic visualizations of walking routes and accessibility.

Results:

• The analysis provided a comparison of how accessible public transportation is in both neighborhoods. It showed differences in walking distances and times to bus stops, identifying areas where access could be improved.

Accessibility Maps: