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Understanding the temporal and spatial interactions between transit ridership and urban land-use patterns: an exploratory study

Understanding the temporal and spatial interactions between transit ridership and urban land-use... The land-use characteristics of urban areas continually change, and thus the activity patterns of the significant trip generators evolve. Efficient public transit planning needs to perform frequent estimates of the spatio-temporal distribution and dynamics of different activities in urban areas and measure the likely consequences of changes. Automated data collection systems usually collect transit ridership data (e.g., automated passenger count (APC)). Many transit agencies also generate General Transit Feed Specification (GTFS) data and make them publicly available. This study explores the use of APC, GTFS, and land-use data to examine various land-use and transit ridership interactions at the stop, route, and zonal levels using visualization, data mining, and statistical analysis techniques. Results show that transit ridership at the bus stop level gives a better understanding of each bus stop's unique land use. Zonal-level transit ridership patterns reveal the different trip generations and attraction roles of the neighboring land usage. This study could provide additional insights on the interaction between the temporal changes in population from the perspective of transit use and the associated land uses. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Public Transport Springer Journals

Understanding the temporal and spatial interactions between transit ridership and urban land-use patterns: an exploratory study

Demissie, Merkebe Getachew; Kattan, Lina
Public Transport , Volume 14 (2) – Jun 1, 2022
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References (72)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022
ISSN
1866-749X
eISSN
1613-7159
DOI
10.1007/s12469-022-00296-2
Publisher site
See Article on Publisher Site

Abstract

The land-use characteristics of urban areas continually change, and thus the activity patterns of the significant trip generators evolve. Efficient public transit planning needs to perform frequent estimates of the spatio-temporal distribution and dynamics of different activities in urban areas and measure the likely consequences of changes. Automated data collection systems usually collect transit ridership data (e.g., automated passenger count (APC)). Many transit agencies also generate General Transit Feed Specification (GTFS) data and make them publicly available. This study explores the use of APC, GTFS, and land-use data to examine various land-use and transit ridership interactions at the stop, route, and zonal levels using visualization, data mining, and statistical analysis techniques. Results show that transit ridership at the bus stop level gives a better understanding of each bus stop's unique land use. Zonal-level transit ridership patterns reveal the different trip generations and attraction roles of the neighboring land usage. This study could provide additional insights on the interaction between the temporal changes in population from the perspective of transit use and the associated land uses.

Journal

Public Transport – Springer Journals

Published: Jun 1, 2022

Keywords: Transit ridership; Land use; Automated Passenger Count Data (APC); General Transit Feed Specification data (GTFS); Data mining; Transit demand

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