ACCESS AND MOBILITY IN GAUTENG’S PRIORITY TOWNSHIPS

1. ACCESS AND MOBILITY IN GAUTENG’S PRIORITY TOWNSHIPS WHAT CAN THE 2011 QUALITY OF LIFE SURVEY TELL US? Christo Venter Department of Civil Engineering, UP July 2014

2. Background

4. OBJECTIVES DATA • Gauteng City Region Observatory (GCRO) 2011 QoL Survey (n=16,700) • Modes, trip purposes • Origins, destinations, travel times & costs • School travel • Satisfaction & problems with transport • GIS analysis • Explore patterns of access and mobility • Focus on GPG’s 27 major townships in Gauteng • Implications for transport and spatial planning

5. 27 PRIORITY TOWNSHIPS

6. ANALYTICAL FRAMEWORK ACCESSIBILITY • “The ease of reaching opportunities from a particular location, given the available transport system” • Primarily a function of location and transport connectivity • MOBILITY • “The actual amount of travel undertaken, or the costliness of doing so” • Function of accessibility AND personal mobility choices/constraints WhereAIi = Access Index for origin area i tij= Travel time (in minutes) between origin i and destination area j Aj= Number of job opportunities in destination zone j • High expenditure of either money or travel time • Most frequent trip (Work, job-hunting, or non-work) • Measured as % of people exceeding 75th percentile value of travel cost/income value, or one-way travel time for Gauteng

7. Low access; High expense: Disadvantaged location, users forced to incur high travel cost to interact High access; High expense: Advantaged, use good location to travel more and further - Mobility + - Access + High access; Low expense: Advantaged, good location is used to reduce travel costs Low access; Low expense: Disadvantaged, travel so costly that users suppress travel ANALYTICAL FRAMEWORK ACCESSIBILITY MOBILITY

8. ACCESSIBILITY BY RAIL AND TAXI

9. ACCESSIBILITY BY RAIL AND TAXI Good rail & taxi access

10. ACCESSIBILITY BY RAIL AND TAXI Good rail & taxi access Rail present but less accessible

11. ACCESSIBILITY BY RAIL AND TAXI Good rail & taxi access Rail present but less accessible Taxi makes up for poorer rail access

12. ACCESSIBILITY BY RAIL AND TAXI Good rail & taxi access Rail present but less accessible Taxi makes up for poorer rail access Location & PT disadvantaged

14. ACCESS VS MOBILITY INNER ACCESSIBLE High access Low expense Short commutes High income

15. WAGE GRADIENTS

16. ACCESS VS MOBILITY INNER MOBILE High access High expense Long commutes to large labour pools INNER ACCESSIBLE High access Low expense Short commutes Higher income

17. WAGE GRADIENTS

18. ACCESS VS MOBILITY INNER MOBILE High access High expense Long commutes to large labour pools MEDIUM ACCESS (Med access Med expense) INNER ACCESSIBLE High access Low expense Short commutes Higher income

19. WAGE GRADIENTS

20. MEDIUM ACCESS TOWNSHIPS • Internal movement • Many destinations, besides CBD • Optimal incomes at around 20-30km from home

21. ACCESS VS MOBILITY OUTER MOBILE Low access High expense Long commutes competing for few jobs INNER MOBILE High access High expense Long commutes to large labour pools MEDIUM ACCESS (Med access Med expense) OUTER IMMOBILE Low access Excluded, Low earnings INNER ACCESSIBLE High access Low expense Short commutes Higher income

22. WAGE GRADIENTS

23. Outer Immobile Mobile by choice Outer mobile

24. VARIATION WITHIN SETTLEMENTS • Looking at area-wide location can mask differences among households within a settlement ** Households in informal housing are significantly worse off

25. CONCLUSIONS AND IMPLICATIONS • Mobility and accessibility together presents rich picture • Location along core-periphery gradient remains important • Core of what? City or City-region? • Beneficial: • Opportunities within settlement • Proximity to city-region core & large job pools • Rail • Good taxi connectivity, if no rail • Most townships cluster around average mobility • Signs of immobility and disengagement from urban economy • Need to serve many 20-30km trips along low-density routes – can BRT and rail fulfil this role?

26. Acknowledgments GCRO (funding & data) Willem Badenhorst (MandalaGIS) - maps