A spatial-temporal geo-spatial database model for transport justice. case study: Cape Town, South Africa

This research project develops a database model for the analysis of spatial and temporal differences in potential accessibility and mobility across the various public transport modes in the context of Cape Town, South Africa. This database model provides the foundation on which further transport justice tools are to be created. These transport justice tools aim to assist with redressing shortcomings in transport planning and operations which branched from amongst others, the apartheid land use transportation planning model and the effects it has on people until today. The ultimate goal of the research was to create a database model that served as the foundation for transport justice tools to use in transport justice analysis. The first tool was a Space-Time Cube model with potential accessibility, potential mobility and time being the three respective axes. This cube represents the three parameters of a particular TAZ region for specific modes of public transportation. This cube can be used to perform analysis on the TAZ regions of interest, e.g. to analyse and compare the levels of potential accessibility, potential mobility across time in the area. The second tool provides a two- dimensional Temporal Aggregation of the Space-Time Cube. This allows us to study particular hours of the day of interest for potential accessibility and mobility of all possible TAZ regions of interest for the City of Cape Town. Income and racial demographics and population data can be used with both of these transport justice tools to assist the analysis. Having more information about the potential accessibility and mobility, especially temporally will assist the user in making better decisions for planning their use of public transportation systems and operations. The service provider can use this database model to identify disparities in the potential accessibility and mobility of transport services they are providing. The government could benefit from this research by identifying regions that have potential accessibility and mobility deficiencies, possibly due to poor transport planning of areas where previously disadvantaged people were displaced. In addition, the government can identify which regions require improvements in potential accessibility and mobility for example, by looking at population, race, and income data of the areas that fall within this potential accessibility and mobility deficit. Using the Temporal Aggregation Python tool created for this project showed Accessibility levels are low at 06h00, then increases at 10h00, then decreases at 16h00 again. This was due to taking operational hours of the opportunities into account in the accessibility calculation as well as how frequently the public transit operates in the peak and off-peak periods of the day. The PMI levels are high at 06h00, then decreases at 10h00, then increases at 16h00 again. This was due to how frequently the public transit operates in the peak and off-peak periods of the day. This indicates that a person would reach destinations much faster when there is an increase in the availability of a particular public transit mode in the off-peak hours. Further analysis can be done on each mode of transport to analyse the potential accessibility and mobility both spatially and temporally. Deductions have been made about this analysis to determine the fairness of these modes of transport with respect to potential accessibility and mobility.

Grantor dc:publisher.institution

Department of Civil Engineering

Year dc:date.issued

2025

Author dc:creator

• Kotzee, Brent

Advisor dc:contributor.advisor

• Zuidgeest, Marcus

• Transport justice
• database

Language dc:language.iso

en

Handle dc:identifier.uri

http://hdl.handle.net/11427/41658

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/41658