csir built environment - erln.gtac.gov.za

Economies of Regions Learning Network

CSIR Built Environment

August 2014

G Mans

Table of contents

1. CSIR SPS’s role (relating to today’s discussion)

2. Process of producing data / indicators which

are spatially integrated and more detailed

3. Data produced / available

4. Value of integrated data: some examples

Knowing the strengths of specific places, how

much of what is where?

5. Our data need

1. CSIR, SPS’s role re. this discussion

Collaboration Innovation R&D

Policy &

Intervention

Investment

Priorities/

Needs

Spatial

Analyses &

Data

Beneficiation

Decision & research

Support Tools,

Technologies,

Platforms, Viewers

• Spatially specific/differentiated (non-

admin area)

• Comparative analyses (between

places, and between sectors)

• Regional linkages (across the

border?) and interactions/networks

• Temporal

Trends

• Future

implications

Regions, Cities /towns /settlements, City-regions and Cities

Regional Development, Co-ordinated investment, Infrastructure

investment, Land-use and Infrastructure Planning

DIM

EN

SIO

NS

BU

ILD

ING

BLO

CK

S

SET Outputs

Human

Capital

Development

CONTEXT:

KEY DATA ISSUES ?

1. CSIR, SPS’s role re. this discussion

Enhance the spatial evidence used in regional as well as

metro level planning processes and spatial analyses,

through:

– Development of spatially explicit and integrated data

sets (with a national coverage)

• E.g: Economic, Population, Employment, Migration, as well as

indicators / composite indices

– Providing access to spatial data and analytical tools,

disseminated via web-based portals

• E.g: gap.csir.co.za; stepsa.org; www.sarva.org.za

1. CSIR, SPS’s role re. this discussion

• However, CSIR adds value to existing datasets by

using it in different spatial modelling processes.

• Through this new enhanced datasets and/or

indicators are produced

• CSIR is not a primary data producer

Primary dataEnhanced data

/ indicatorsAnalysis Understanding

Policy implications

CSIR

2. Detailed spatially integrated data

• Many datasets are too course to support targeted planning and

decision making, need more detail

2. Detailed spatially integrated data

• Basic spatial units support data (1) disaggregation and (2) data

integration

2. Detailed spatially integrated data

• Disaggregation through dasymetric mapping

Production points

(ancillary data)

Focused data

2. Detailed spatially integrated data

• Disaggregation through dasymetric mapping

3. Data produced / available (eg.)

• GVA as well as derived employment per sector

Primary sector Agriculture, forestry and fishing (SIC1)

Mining and quarrying (SIC2)

Secondary sector Manufacturing (SIC3)

Electricity, Gas and Water supply (SIC4)

Construction (SIC5)

Tertiary sector

Wholesale and retail trade; Repair of motor vehicles, motor cycles and personal and household

goods; Hotels and restaurants (SIC6)

Transport, Storage and Communication (SIC7)

Financial Intermediation, Insurance, Real Estate, and Business Services (SIC8)

Community Social and Personal Services (SIC9)

Government Services (SIC10)

3. Data produced / available

• Change in number of poor households (Population: 1996, 2001 and 201)

• Other census variables on request

4. Value of integrated data

Economic Activity Natural Resources

Poverty Economic Activity

4. Value of integrated data

4. Value of integrated data

4. Value of integrated data

• Population growth and migration

4. Value of integrated data

• Modelling of future growth, land use, transport and

infrastructure scenarios

• Metro / urban (agent based using UrbanSim)

• Regional (LU use implications)

UrbanSim tracks profile of households/jobs associated with each development template.

Massive potential for projecting consumption patterns of municipal services: Water, energy, waste water,

solid waste, public transport, libraries, revenue, …

UrbanSim tracks profile of households/jobs associated with each development template.

Massive potential for projecting consumption patterns of municipal services: Water, energy, waste water,

solid waste, public transport, libraries, revenue, …

5. Data need

• Ancillary data for (1) dasymetric mapping as well as (2) urban &

regional modelling:• Enterprise data: address; turnover; personnel

• Workforce data: e.g. IRP showing employer address; employee address

• Above cover wide range of possibilities:• Dasymetric mapping of all economic sectors

• Day-time night-time population estimates

• Transport modelling

• Logistics modelling

• Infrastructure investment priorities / opportunities

• Economic cluster analysis

• Public transport planning

• Etc.

Thank you