Awan, F. M. (2025) Birmingham city Averaged OD Matrices 2019-2023. [Data Collection]

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Collection description

Overview:
Averaged Origin-Destination (OD) Matrices provides information about the percentage of average number of trips between different origins and destinations in the city across 5 years (2019 – 2023). Before generating the final OD matrices, the detected and weighted trips were averaged across 5 years to mitigate any event or season-based biases. Location data from mobile phone apps aggregated by Huq Industries was used to derive OD Matrices and these are an UBDC derivative product of Huq dataset.
Calculating OD Matrices from the mobile phone app data involved the following steps:
• Filtering out inaccurate and imprecise GPS points.
• Estimating stay locations using time and distance thresholds. A stay location is detected if a user spent at least 5 minutes in a 500m radius area.
• Extraction of trips between stay locations.
• Associating each detected stay location with an MSOA/Intermediate Zone (IZ) in the city.
• Applying weights based on the user’s home location MSOA/Intermediate Zone and their activity status in the dataset.
• Aggregating the number of trips between each origin-destination pair.
To validate the methodology, two types of validations were carried out:
1. Internal Validation: this focuses on examining the dataset’s internal consistency and logical patterns. It involves a series of checks, comparisons, descriptive statistics, and visualizations within the dataset itself. The aim is to ensure that the data is coherent, free of anomalies, and the results align closely to expected outcomes. Key aspects of internal validation include:
a. Consistency Checks: Verifying that the data values are within logical and expected ranges. For example, ensuring all percentages values are between 0 and 100.
b. Descriptive Statistics: Generating summary statistics such as mean, median, standard deviation, and percentiles to understand the distribution and central tendencies of the data.
c. Visualisations: Using plots and maps to visually inspect patterns and detect any inconsistencies or unusual outcomes.
These checks help ensure that the OD matrices are internally consistent and reflect realistic travel behaviour within each city.
2. External validation: it involves comparing the OD matrix outputs with reliable external datasets to evaluate their accuracy and reliability. This step is essential for verifying the results derived from mobile phone app data aligning with established data sources and known patterns of urban mobility. The external validation process includes:
a. Benchmarking against external datasets: Comparing the observed results with credible external data sources such as Scottish Household Survey to validate travel patterns and behaviours observed in the city.
Through external validation, the OD matrices’ credibility is enhanced by demonstrating that the observed patterns are consistent with real-world data and established urban mobility trends.

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. It has a time coverage of 5 years from 2019 to 2023.

Access and restrictions:
Averaged Origin-Destination (OD) Matrices are available for non-commercial academic research use only. The data is available to request as Safeguarded data under UBDC's End User Licence.

More information:
• Other related outputs: https://www.ubdc.ac.uk/news/data-for-insights-into-mobility

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