Integrating land-cover data with data on population and household characteristics to assess densification along the BRT ROUTE in the city of Tshwane SATC 2018 CSIR ICC, Pretoria, Gauteng, South Africa Presented by N Dudeni-Tlhone Team: E PETZER, Dr S KHULUSE-MAKHANYA, JP HOLLOWAY and A GXUMISA. Confidential

Strategic Research Panel (SRP) project Background Strategic Research Panel (SRP) project Importance of Earth Observation/Remote sensing for spatial planning Indicator development Integration with official statistics/data in the public domain Densification along BRT Monitoring of the SDGs SDG 11: Sustainable Cities and Communities Target 11.2 Public transport access and convenience Background This is a sub-component/ task/ case study activity undertaken under the SRP project. We often lack spatial data for planning and decision making

Estimate current densification patterns along the BRT route Objectives Estimate the proportion of the City of Tshwane (CoT) population with convenient access to BRT (A Re Yeng) service Estimate current densification patterns along the BRT route population densities, building footprint and land use characteristics Background

500 m walking distance: 200 units/ha Methodology Estimate the proportion of the CoT with convenient access to BRT Based on the UN Habitat definitions/guidelines (SDG 11, Target 11.2- Public transport access and convenience) Walking distance standard of 500m from a rapid transit station Link SDG 11, 11.2 to CoT Rapid Transit Spatial Development that promotes various densification concept of around stations in terms of the 500 m and 700 meter waking distances. High residential development within the 1st 500m walking distances (200 units/ha). New nevelopments within concentration zones should preferably not be at densities of below 120 units per hectare. 500 m walking distance: 200 units/ha 500 m-700 m walking distance: 120 units/ha

Data requirements/ sources BRT route and bus stops Census 2011---population distribution and household characteristics Small Area frame Land cover data (built-up footprint) 2013/2014 National land-cover data set GTI SPOT Building count Route and bus stop data layer- for creating a 500m buffer from both sides of the each station Census data (only public and official source) for estimating population within the relevant buffers Land cover data sets (GTI and

BRT route Main route with 76 bus stops, 2 trunks and several feeder routes from PTA North CBD Hatfield covering a total distance of 80 km.

Data pre-processing analysis SAL layer and Bus stops/buffer Total of 4524 SALs in CoT with 204 (5%) of them spatially located within the BRT route Discussion of census and buffer layer---and how the data were extracted for analysis

Proportion with convenient access to BRT=5% Results Estimation: 𝑝 = 𝑛 𝑁 , where 𝑛 =138 056 (Buffer population) and 𝑁=2 921 364 (CoT population) Proportion with convenient access to BRT=5%

Characteristics of the CoT/ buffer population   Rest of Tshwane BRT Buffers Main variable Variable category N % n Age Age 0-14 years 2 921 278 23 138 048 12 Age15-64 years 72 84 Age 65- 120 years 5 4 Car ownership Yes 911 477 44 45 973 37 No 56 63 Hearing No difficulty 2 630 268 97 112 058 98 Some difficulty 3 2 Mobility 2 637 366 112 339 Sight 2 638 669 91 112 604 92 9 8 Employment status Employed 2 101 205 51 116 252 47 Unemployed 16 13 Economically Inactive 29 40 Migration Gauteng 2 826 874 86 118 665 Other Provinces 10 27 Outside SA

Population densities along the buffer Discuss the results eg. Min =2 351, max=37 518 people per buffer area of roughly 0.79 km2. Variability of estimates…..

Building footprint/ land-use along BRT Building types along BRT services buffers—Building land-use

LC-14 Discuss the results eg. Min =2 351, max=37 518 people per buffer area of roughly 0.79 km2. Variability of estimates…..

Varying densities along the BRT route Conclusion Potential for integrating EO and official stats for monitoring relevant transport indicators Proportion of population with convenient access Building density Varying densities along the BRT route Potential for densification at the less dense parts to support optimal usage of BRT and possibly other public transport modes No desirable population density thresholds were determined

Thank you Strictly confidential