Published January 20, 2026 | Version v1.0.0
Dataset Open

London Underground Stations: Geospatial, Passenger Usage and Accessibility Data

  • 1. ROR icon Royal Holloway University of London

Description

This dataset provides a structured geospatial and operational record of London Underground (Tube) stations.

Each entry represents a London Underground station or station component, capturing spatial location, served lines, historical opening information, passenger usage, and step-free accessibility status. Some station names appear more than once to represent distinct operational or historical station components (e.g. different line groupings or opening years). These are intentional modelling units rather than duplicate records, and are suitable as separate nodes in graph-based or optimisation models.

The dataset is designed to support transport network analysis, accessibility studies, route planning, optimisation and graph-based modelling, and teaching in GIS, Operations Research, and urban transport systems.

Each record includes:

  • WGS 84 latitude and longitude,

  • UTM Zone 30N projected eastings and northings (EPSG:32630),

  • served Underground lines and fare zone,

  • local authority information,

  • station opening year,

  • passenger usage estimates for 2024, including usage ranks and bands,

  • step-free accessibility status as of December 2025, and

  • a brief free-form descriptive note providing contextual or locational information.

Passenger usage figures follow Transport for London reporting conventions; in particular, Bank and Monument share a combined usage value for 2024. Step-free access is defined as step-free from street to platform level, consistent with TfL’s official classification.

Coordinates are provided in EPSG:32630 (WGS 84 / UTM Zone 30N) to enable replicable planar distance calculations, optimisation modelling, and spatial analysis. The dataset covers London Underground stations only and excludes the Elizabeth line, London Overground, Docklands Light Railway (DLR), Tram, and National Rail services.

The dataset and accompanying documentation are provided as CSV and Markdown files.

Files

README.md

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