A Dataset on Public Bus Transportation during Normal and Grand Prix Seasons in the Macao Area

The study investigates public bus transportation data in Macau during normal and Macau Grand Prix seasons. Utilizing real-time data collected from the Transport database, a comparative analysis highlights variations in bus operational metrics such as passenger flow, arrival times, and traffic conditions between standard and event periods. The findings reveal significant spikes in passenger volume and increased traffic congestion associated with the Grand Prix, emphasizing how large-scale events impact public transport dynamics. Through Principal Component Analysis (PCA) and correlation heatmaps, the research illustrates differences in transportation patterns, providing insights essential for enhancing service delivery and operational planning. This dataset aims to serve as a critical resource for future transport policy development and smart city initiatives, advocating for better utilization of data generated by public transport authorities. These insights aim to optimize resource allocation and improve overall urban mobility during major events in the region.

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Publication Details

Journal
Scientific Data
Published
2025-07-26
DOI
https://doi.org/10.1038/s41597-025-05660-y
Citations
1
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
2.18
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article

A Dataset on Public Bus Transportation during Normal and Grand Prix Seasons in the Macao Area

Song-Kyoo Kim, Junbo Wang
1 citations
Scientific Data
Transportation Planning and Optimization
2.18
article

A Dataset on Public Bus Transportation during Normal and Grand Prix Seasons in the Macao Area

Song-Kyoo Kim, Junbo Wang
article en
1 citations

Abstract

The study investigates public bus transportation data in Macau during normal and Macau Grand Prix seasons. Utilizing real-time data collected from the Transport database, a comparative analysis highlights variations in bus operational metrics such as passenger flow, arrival times, and traffic conditions between standard and event periods. The findings reveal significant spikes in passenger volume and increased traffic congestion associated with the Grand Prix, emphasizing how large-scale events impact public transport dynamics. Through Principal Component Analysis (PCA) and correlation heatmaps, the research illustrates differences in transportation patterns, providing insights essential for enhancing service delivery and operational planning. This dataset aims to serve as a critical resource for future transport policy development and smart city initiatives, advocating for better utilization of data generated by public transport authorities. These insights aim to optimize resource allocation and improve overall urban mobility during major events in the region.

Scientific DataVol. 12(1)
Macao Polytechnic University (MO)
Openalex Percentile: Top 12%
Transportation Planning and Optimization
2.18
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A Dataset on Public Bus Transportation during Normal and Grand Prix Seasons in the Macao Area — Song-Kyoo Kim, Junbo Wang · Scientific Data (2025) | TGRS Research Map | TGRS