Accessibility impact analysis of new public transit projects in Cairo, Egypt

Abstract

The New Urban Communities (NUC), built around Cairo, developed to relieve congestion and pull away residents from the crowded core, have not successfully attracted a significant number of residents. Since NUCs are not well connected by official public transport to the inner city, their residents rely on private cars and informal or expensive private mass transit to reach the job markets of inner Cairo. Although in official strategy plans, no direct link is drawn between the difficulty of moving between and within NUCs and their low occupancy rates, NUCs can be attractive places to live for diverse socio-economic groups if their accessibility to jobs and points of interest were improved. There is growing interest from the World Bank and the Egyptian government to invest in public transport routes in the Greater Cairo Region to improve job accessibility and relieve traffic congestion.

Applying existing methods to measure the impact of different routes on job accessibility requires data on the location and density of jobs which is not readily available in many data-poor cities in the global south. A novel method was applied to produce a job density data set, combining scraped location and categorical data on businesses from online directories with official census and survey data on job numbers and industry types. This thesis explores the locations of employment opportunities in the absence of official data and the accessibility of the population to these opportunities in the Greater Cairo Region in order to assess the different levels of accessibility to jobs by public transport and inform the priorities of future investment in public transport provision. The research results in recommendations on where 3 routes, out of 10 given corridors, should be placed based on the impact of these new transit lines towards job accessibility.

Using location-based accessibility models combined with a novel approach to developing job location data, the work identifies bus routes that performed the best in getting the largest number of people to jobs given considerations of socio-economic equity.