A/Prof. Mark Zuidgeest ACCESSIBILITY EFFECTS OF RELOCATION AND HOUSING PROJECT FOR THE URBAN POOR IN AHMEDABAD, INDIA South African Cities Network/University of Pretoria, 09 April 2018
MOBILITY Ability to readily move people from place to place Key-words: Networks and modes: how to get there? Speed: how fast? Cost: how expensive? Indicators of success: Vehicle Kilometres Travelled (VKT) In other words: maximizing movement
ACCESSIBILITY Easiness to enter, reach, and use (aka access) The ease of reaching goods, services, activities and destinations (together called opportunities) (aka accessibility) Key-words: Opportunity: A chance for employment, leisure, etc Impedance: Difficulty of getting there Utility: Satisfaction experienced Indicator of success The ability to reach destinations
A PARADIGM SHIFT IS NEEDED "Just as automobiles are machines that provide mobility, urban environments - villages, towns and cities - can be thought of as machines that provide accessibility by minimizing the distance among people and their desired goods, service and activities (shops, schools, jobs, neighbors, etc.). [Litman, 2010]
CONCEPTUALIZING ACCESSIBILITY Travel is a derived demand, i.e. the demand for travel is derived from the demand for spatially-separated activities: 1. 2. 3. Behaviour and choices of people and companies. Locations and type of spatially bound activities, such as residing, working, recreation. Resistance to overcome a distance (impedance), in terms of time, costs and other factors, such as safety security, comfort etc. Point of Origin Transport network Point of destination (Impedance) (Utility/Ben efit)
CONCEPTUALIZING ACCESSIBILITY our focus
MEASURING ACCESSIBILITY Contour measures (cumulative opportunity) measures the cumulative number of (job) opportunities that can be reached in a given time or at certain threshold distance from a specified origin. Potential measures (activity based) discounts the number of (job) opportunities that can be reached from a specified origin.
ACCESSIBILITY MEASURES CONT D Indicator for the effectiveness of the transport system ability to reach employment areas, service locations, centre areas etc. Indicator for the availability of services securing a geographical match between resource allocation and resource needs
CASE STUDY AHMEDABAD, INDIA
AHMEDABAD Ahmedabad is the largest city of Gujarat state on the banks of Sabarmati river and the seventh largest city in India [total area = 190 km2]. Current population Ahmedabad city is about 5.5 million. In 1994 many mills faced liquidation and were officially closed leaving nearly 67,000 of workers jobless. The percentage of people living in low-income housing is about 40% (25% in slums, 15% in industry estates (chawls)) Jawaharlal Nehru National Urban Renewal Mission (JNNURM), 2005: urban poor housing relocation scheme Introduction of Bus Rapid Transit (BRTS) as well as Metro system (MRT) What are accessibility effects of the (proposed) relocation and public transport upgrading schemes for the urban poor?
CASE STUDY AHMEDABAD Conceptual framework Urban poor -Income -Education level Transport Physical condition of housing -Modes -Networks -Operation Employment -Location of jobs -Job type
DATA Analysis activity Key data sources Data source to test model assumptions Determining locations of the urban poor Locations of slums and chawls (remote sensing) Expert interviews Determining locations of employment Ahmedabad property tax data Expert interviews GIS based network modelling Various networks, AMTS and n.a. BRTS with their characteristics Mode use of urban poor BSUP housing locations Contour based accessibility modelling Gravity based accessibility Ahmedabad household modelling survey Distance decay curves Data source for model validation n.a. Focus Group discussions Focus Group discussions
INTEGRATED MULTI-MODAL TRANSPORT NETWORK Current and proposed public transport modes 3D ArcGIS mutli-modal network model, allowing for transfers
NETWORK SETTINGS
LOCATIONS OF THE URBAN POOR AND THEIR JOBS
DENSITY OF POTENTIAL WORKERS Remote sensing data to capture housing types Classify level of poverty (least poor, middle poor, very poor) Slums and chawls combined, Worker Density per 0.25ha Legend slum location river density potential workers [per.25 hect.] 7. - 10 10. - 25 25. - 90 90. - 400 400. - 1,970 ± 0 2.5 5 Km
LOCATIONS OF EMPLOYMENT Formal employment - all job sectors combined, 400 x 400m. Grid: Job sectors, partly as proxies for informal employment: Categorized as: Casual labour jobs Salaried jobs Self employment jobs Legend Employment [ jobs] 1-100 100-250 250-500 500-1000 1000-3000 roads river /lake ± Industrial Retail Government Education Transport and logistics Office and commercial jobs All jobs combined (shown here) 0 2.5 5 Km
LINKING POOR WORKERS AND JOBS Connecting workers and potential jobs (expert knowledge Ray (2010) and focus groups) Employment Urban poor Least poor Middle-poor Very poor Transport network Salaried Self employment Casual labour
DISTRIBUTION OF URBAN POOR CLASSES AND EMPLOYMENT CATEGORIES
SOCIALLY ECONOMICALLY WEAKER SECTION HOUSING (SEWSH) JnNURM, Basic Services to Urban Poor (BSUP) program Socially Economically Weaker Section Housing (SEWSH) scheme 21 SEWSH locations 976 new buildings relocating 78,080 poor Used as a scenario in this study
S1: IMPACT OF SEWSH RELOCATION PROGRAMME 18 18 7 7 11 10 8 10 12 9 5 6 17 19 11 13 14 8 12 9 16 15 5 6 17 19 13 14 16 15 4 4 1 1 20 20 21 21 3 3 Legend sewsh location SEWSH AMTS lines roads Legend Contour [min] sewsh location Contour [min] 0-10 10-20 20-30 30-45 45-60 river/lake ± Modes: Walking AMTS 0 Without BRTS/MRTS 2.5 5 Km AMTS lines 0-10 BRTS lines 10-20 MRTS metro 20-30 roads 30-45 45-60 river/lake Modes: Walking AMTS BRTS phase 12 Metro ± With BRTS/MRTS 0 2.5 5 Km
IMPACT OF SEWSH RELOCATION PROGRAMME Total job opportunities 1600000 1400000 45-60 1200000 30-45 20-30 1000000 10-20 800000 0-10 600000 400000 200000 0 SEWSH Id. Bars: walking (left), walking + AMTS (middle) and all modes (right)
IMPACT OF SEWSH RELOCATION PROGRAMME - 12 13 - = +/- 1 km using the roads - 17 - - 16 1314 - Legend 15 - - 14 16 - - 15 AMTS stops BRTS stops SEWSH location AMTS lines BRTS lines roads employment 0 Meters 500 250 0 2 1-10 - 4-6 5 4 1 1-20 0 1 Km 2 Km 0 1 2 Km Specifically looking at locations 1, 13, 14, 15, 16
IMPACT OF RELOCATION ON JOB ACCESSIBILITY 0-30 min walking Before relocation 78,000 jobs walking + AMTS 148,000 jobs all modes 215,000 jobs After relocation Winners 40,000 jobs 61,000 jobs 80,000 jobs 4 locations (5, 6, 10, 11) 17 locations (1-4, 7-9, 12-21) 3 locations (5,6, 10) 18 locations (1-4, 7-9, 11-21) 3 locations (5, 6, 10) 18 locations (1-4, 7-9, 11-21) 30-60 min Walking Before relocation 353,000 jobs walking + AMTS 798,000 jobs all modes 910,000 jobs After relocation Winners 155,000 jobs 545,000 jobs 637,000 jobs 6 locations (5-10) 15 locations (1-4, 11-21) 7 locations (5-11) 14 locations (1-4, 12-21) 9 locations (5 11, 19, 20) 12 locations (1-4, 12-18) Losers Losers Clearly the housing relocation project (versus BRTS/MRTS) has more losers than winners
CALCULATING POTENTIAL JOB OPPORTUNITIES The potential of opportunities for interaction Ai W j f (cij ) W j exp( cij ) j j with Wj the number of jobs in location j, cij the generalized cost of travelling between i and j, and f(cij) the distance decay function Distance decay functions (two modes):
CALCULATING POTENTIAL JOB OPPORTUNITIES City-wide Potential accessibility analysis (least poor to salaried jobs)
CITY-WIDE POTENTIAL ACCESSIBILITY ANALYSIS Ratio of job-based potential accessibility for all potential workers comparing all public transport options with walking and AMTS only. Impact mostly linear, and in close vicinity of the proposed systems. Relative to walking/amts alone
EFFECT OF BICYCLE FEEDERS (ALL POOR) ") 18 ") ")4 ")1 ") 11 ") ") ") ") 1 2 ") ") 1")6 1")5 1")4 13 17 ") 19 ") 20 9 8 5 6 10 ") Overall the level of potential accessibility for the locations improves by 135% on average for the 21 SEWSH locations ")7 ") 21 ")3 2 ") Legend SEWSH potential jobs 200,000 BRTS stops MRTS stations cycling contribution BRTS buslines walk + PT MRTS lines roads river / lake 0 2.5 5 Km ±
OVERALL PUBLIC TRANSPORT IMPACT 25,000,000 SEWSH 20,000,000 Least poor Middle poor Very poor 5,000,000 Very poor Middle poor Least poor SEWSH 0 k al W TS M A TS BR 1 TS BR 2 RT M The very poor workers benefit least + + + + 0 % 5 % 1 0 %1 5 % 10,000,000 In c r e a s e in p o t e n t ia l a c c e s s ib ilit y r e la t iv e t o w a lk in g a n d A M T S 15,000,000 14% 13% 8% 9% 4% 8% + BRTS 1 + BRTS 2 + MRT
CONCLUSIONS There is variation between accessibility to jobs for different urban poor groups. Compared to walking, the existing and proposed public transport improvements do improve job accessibility considerably. BRTS/MRTS impact is mainly in the vicinity of the systems. Cycling provides a good first/last-mile access to and from the proposed BRTS/MRTS, combining the strengths of both NMT/PT. The housing relocation scheme clearly hasn t considered transport and promotes exclusion These effects are likely to be exacerbated when including affordability.
PROJECT TEAM: CASE STUDY AHMEDABAD The World Bank group Nupur Gupta, Andrew Salzberg and Samuel Zimmerman University of Twente Faculty ITC Mark Zuidgeest (PI) (formerly), Mark Brussel and Martin van Maarseveen Frans van den Bosch and Nguyen Ngoc Quang Talat Munshi (CEPT University, Ahmedabad)