GTFS Analysis Africa

Antoine CHEVRE

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Building on the DigitalTransport4Africa initiative and the work of TransportForCairo, a personal application project to analyze African cities. It is based on GTFS data, WorldPop data, and OpenStreetMap facilities data. It enables: - urban public transit/pedestrian accessibility analysis - public transit network analysis https://huggingface.co/spaces/antoinechevre/GTFS_Analysis_Africa

This app aims to analyze African cities' transport networks and the associated urban accessibility. It's an African take on the sister app for metropolitan France.

https://huggingface.co/spaces/antoinechevre/GTFS_Analysis_Africa

The data used is:

GTFS datasets from the Digital Transport 4 Africa initiative, and those produced by TransportforCairo
WorldPop population data
Facility data recorded in OpenStreetMap

⚠

Handle data and results with caution: there is no reliable sub-municipal census for most of these cities (WorldPop population data is a modeled estimate, not a census), OpenStreetMap facility coverage varies a lot between cities and neighborhoods. An arbitrary weighting was proposed for facilities (cf. the Facilities tab under Urban accessibility). As for GTFS data, it is partial (stops and lines are reliable, but not service frequency) and often outdated / no longer maintained (GTFS validity dates are shown). Results (population grid, facilities, accessibility) are thus orders of magnitude, not reference figures. Moreover, many cities have ongoing projects and African cities are changing fast.

Results are presented in 2 sections.

📍 Urban accessibility analysis

🎯 Goals

⚙️ Features

🔗 Links & Instructions

This analysis is inspired by the book Introduction to urban accessibility (Rafael H. M. Pereira and Daniel Herszenhut, Ipea - Institute for Applied Economic Research), specifically the chapter Calculating accessibility estimates in R — adapted to Python for an African context.

Offer a processing chain to go from a raw GTFS to accessibility analysis of the network, on a 600x600m grid:
- walking/public transit mode, on a base weekday at peak hour
- weighted OpenStreetMap facilities (substitute for the BPE) within 60 min of the network
- on a WorldPop 600x600m population grid (substitute for the INSEE grid)
Offer a computation directly from the app when no travel-time matrix is cached yet
Offer a benchmark across African cities, comparing facility-accessibility indicators

🚏 GTFS Analysis

The GTFS analysis (independent from the accessibility analysis above) was developed during the Cerema TSNI 2025 Hackathon and taken over by Antoine Chèvre (and claude.ai...).

Cerema team: Patrick Gendre, Hugo De Luca and Maxence Liogier

⚙️ Features

🔗 Links & Instructions

Analysis of GTFS (General Transit Feed Specification) data to extract key public transit indicators.