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H3 Mobile Mobility Dataset for 55 major UK cities (2017-2024)

Li, L. and Sinclair, M. (2026) H3 Mobile Mobility Dataset for 55 major UK cities (2017-2024). [Data Collection]

Collection description

Overview:

H3 Mobile Mobility Dataset is an UBDC derivative product of Huq dataset. This dataset provides anonymised mobile location observations for 55 major UK cities from 2017 to 2024, spatially indexed to Uber’s H3 hexagonal grid. Each record represents a single location observation captured from mobile applications and assigned to an H3 grid at resolution 13, with derived temporal attributes (date, hour, minute) and linked UK administrative geographies (LSOA/Datazone, MSOA/Intermediate Zone, and Local Authority District). Temporal coverage includes full calendar years for 2017-2023 and January-June for 2024. The dataset supports high‑resolution spatiotemporal analysis of urban activity patterns and integration with other spatial data via a common grid-based framework, while preserving user anonymity through a non-reversible hashed user identifier.

Processing the Huq mobile data and indexing observations to the Uber H3 grid involved the following steps:
1. Input data preparation: ingest raw Huq location observations, including anonymised user identifiers (uid), latitude and longitude coordinates, timestamps, and device metadata.
2. Temporal attribute extraction: derive year, date, hour, and minute from the original timestamp for each observation.
3. H3 grid assignment: spatially index each point using its latitude and longitude to the Uber H3 hexagonal grid at resolution 13, generating the H3 hexagon index for the grid containing the point. At resolution 13, each H3 hexagon has an average area of 44 m².
4. Attribute enrichment: spatially join each point to LSOA/Datazone, MSOA/Intermediate Zone, and Local Authority District boundaries, and retain quality and device attributes (e.g., GPS_Accuracy and OS). The original coordinates are removed for anonymisation purposes.

Note:
1. Huq is a mobile phone app dataset capturing real-time, anonymised smartphone location events on an informed consent basis, with data limited to users aged 16+. With granular geo-data and ~0.7% population coverage, it enables analysis of mobility and footfall patterns, consumer behaviour, and the impacts of events.
2. Uber’s H3 Hexagonal Hierarchical Spatial Index is an open-source global grid system that partitions the Earth into hexagonal cells for spatial analysis and optimisation. It uses hierarchical indexing, allowing cells to be subdivided into finer resolutions and efficiently aggregated to coarser levels. Hexagons reduce quantisation error and support fast operations such as neighbourhood queries and clustering.
3. The user identifier (uid) can also be used to join this dataset with the corresponding uid field in the Home locations of mobile users dataset, enabling analysis of mobile user activities associated with home locations.

Huq dataset:
Huq is a mobile phone app dataset. The app collects real-time, anonymised location data from users' smartphones, based on the use of a range of smart phone applications. This dataset offers researchers insights into human mobility patterns and behaviour. Researchers can leverage this data to study consumer trends, urban planning, and the impact of events on people's movements, amongst other applications. Huq data offers the potential to understand changing societal dynamics and make data-driven decisions across various fields, from retail and transportation to public health and urban development. The data has geographic coverage across the UK

Access and restrictions:
H3 Mobile Mobility Dataset for 55 major UK cities (2017-2024), as well as other derived datasets based on Huq data, were available for non-commercial academic research use only.

Funding: