Li, Y., Zhao, Q. and Wang, M. (2024) High-resolution traffic flow data from the urban traffic control system in Glasgow. [Data Collection]

Collection description

This dataset offers a long-term traffic flow data at an intra-city scale with high spatio-temporal granularity. The dataset covers the Glasgow City Council area for four consecutive years spanning the COVID-19 pandemic, from October 2019 to September 2023, providing comprehensive temporal and spatial coverage.

This dataset contains 471 files, with 470 files containing sensor’s hourly traffic flow data from October 1st, 2019, to September 30th, 2023. And a single file provides geographical information for all sensors.

The raw traffic flow data were collected through Glasgow open data portal (https://developer.glasgow.gov.uk/) and refined by a two-fold filtration process based on spatial and temporal constraints. Then the remaining sensors were examined by the numerical filtering. The cleaned traffic flow data were reconstructed and aggregated into hourly intervals.

College / School:	College of Social Sciences > School of Social and Political Sciences > Urban Studies College of Science and Engineering > School of Geographical and Earth Sciences
Date Deposited:	27 Jun 2024 10:06
URI:	https://researchdata.gla.ac.uk/id/eprint/1669
Additional details Additional details Type of data: Code, Spreadsheet Temporal coverage: From To October 2019 September 2023 Date: 25 June 2024 Date type: Publication Geographic coverage: Glasgow City, UK Data collection method: The data is collected via the Urban Traffic Control system called the Split Cycle Offset Optimisation Technique (SCOOT). Additional information: This is a metadata-only record. To access the data associated with this record, please follow the link provided to the Urban Big Data Centre. Resource language: English Status: Published Data Publisher: Urban Big Data Centre Last Modified: 27 Jun 2024 10:06

Repository Staff Only: Update this record