USING STATISTICS FOR LONG TERM SPATIAL PLANNING: THE ILEMBE 2050 REGIONAL

SPATIAL DEVELOPMENT PLAN

Tindall Kruger and Pravina Govender

13 September 2013

SUPPORTED BY:

StratPlanJeff McCarthy

Mott McDonaldGoba

ILEMBE DISTRICT MUNICIPALITY

THE 2050 PLAN – BASIC APPROACH

• The Ilembe Regional Spatial Development Plan is intended to provide long term spatial planning guidance to all stakeholders in Ilembe.

• The District is a recognised growth node in South Africa. For the purpose of the plan the Ilembe Team (supported by Iyer Urban Design Studio and StratPlan), based on a range of statistics, explored various growth scenarios for the District.

• The selection of the preferred scenario was influenced by socio-economic development trends and the proposed development trajectory reflected in the 2012 National Development Plan.

• The selected High Road Scenario was further developed to better understand future population profiles, housing demand, and economic development in the District.

• This understanding formed the basis for the preparation of short (2020), medium (2030) and long term (2050) spatial development plans.

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USING STATISTICS – THE APPROACH

• Step 1: Developing the Scenarios• Step 2: Unpacking the Scenarios• Step 3: Understanding the Implications• Step 4: Determining the Spatial Impact• Step 5: Developing the Plan

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Assumptions:• The economy stagnates

growing at between 1-2%

• HIV/AIDS continue to have major impact

• New urban / housing development limited

Assumptions:• The economy grows at

between 3-5% • Neighbouring areas low

growth rates (in-migration)• The impact of HIV/AIDS on

population growth has been significantly reduced

• New urban / housing development

STEP 1 - DEVELOPING THE SCENARIOS

Assumptions:• The economy grows at

between 5-7% for an extended period

• In-migration from neighbouring countries and Districts as a result of economic growth

• As per previous

SCENARIO 1LOW ROAD SCENARIO 2 SCENARIO 3

HIGH ROAD

1% POPULATION GROWTH PA

Implications:• Current growth rates

maintained

2% POPULATION GROWTH PA

Implications:• Above average

population growth rates

3% POPULATION GROWTH PA /

5% ECON. GROWTH

Implications:• High population growth

rates

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STEP 2 – UNPACKING THE SCENARIOS

2010 2030 2050 -

500,000

1,000,000

1,500,000

2,000,000

2,500,000 5

77,3

60

704

,489

859

,610

594

,680

883

,663

1,3

13,0

76

612

,342

1,1

05,9

58

1,9

97,4

84

OVERALL POPULATION GROWTH SCENARIOS2010 to 2050

Scenario 1 - 1% growth pa Scenario 2 - 2% growth pa Scenario 3 - 3% growth pa

YEARS

NUM

BER

OF

PEO

PLE

Sc 3: Nearly 4 times the current

population by 2050

Sc 2: Double the current population

Sc 1: Approx. 300k increase

Sc 3: Double the current population

by 2030

Note: In the period mid-1990 to mid-2000s RSAs nine major cities grew at a rate of 1.92% 5

2050

2030

2010

- 500,000 1,000,000 1,500,000 2,000,000

91,851

91,851

91,851

364,678

298,870

244,937

1,540,955

715,237

275,554

2010 to 2050 RURAL AND URBAN GROWTH

Urban Rural (Current) Rural Scattered

A further 1.2m people to be

accommodated in urban areas (3.9% growth over term)

A further 120k people to be

accommodated in rural areas

(1% growth, not considering backlog)

Scattered rural population remains stagnant or decline

(0% growth)

TOTAL POPULATION 2010 Population 612,342 2030 Population 1,105,958 2050 Population 1,997,484

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STEP 3 – UNDERSTANDING THE IMPLICATIONS

STEP 3 – UNDERSTANDING THE IMPLICATIONS

SOME ASSUMPTIONS FOR ILEMBE:• In 40 years the current 0-20 year old will be the 40-60 group• Fertility rates will decrease and in-migration will increase• HIV/AIDS will continue to impact more on current 20-40 group,

as well as on 0-20 group• Male / female distribution will become more equal (currently 45:55 in some areas)

THREE PATTERNS OF POPULATION CHANGE

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INFORMING THE THINKING

Declining fertility rates

Increasing crude death rates

(per 1 000 of population)

(Substantially)

lower life expectancy

An ageing population

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STEP 3 – UNDERSTANDING THE IMPLICATIONS

0 - 10

11- 20

21 - 30

31 - 40

41 - 50

51 - 60

61 - 70

71 - 80

81 - above

15 10 5 0 5 10 15

-13.28

-12.00

-7.74

-5.11

-3.54

-2.53

-1.44

-0.68

-0.19

13.20

12.41

8.76

6.60

4.66

3.41

2.51

1.46

0.47

2007 POPULATION PYRAMID (560 380 people – 53.5% female)

%MALE % FEMALE

Percent

Age

Clas

s

15 10 5 0 5 10 15

-10.00

-10.50

-9.50

-7.00

-5.00

-4.00

-2.00

-1.50

-1.00

10.00

10.50

9.50

7.00

4.50

3.50

2.00

1.50

1.00

2050 POPULATION PYRAMID(1 997 484 people – 49.5% female)

%MALE % FEMALE

Percent

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AGE MALE FEMALE TOTAL

0 - 10 199,748 199,748 399,497

11- 20 209,736 209,736 419,472

21 - 30 189,761 189,761 379,522

31 - 40 139,824 139,824 279,648

41 - 50 99,874 89,887 189,761

51 - 60 79,899 69,912 149,811

61 - 70 39,950 39,950 79,899

71 - 80 29,962 29,962 59,925

81 + 19,975 19,975 39,950

TOTAL 1,008,729 988,755 1,997,484

STEP 3 – UNDERSTANDING THE IMPLICATIONS

2050 POPULATION IN AGE CATEGORIES

2007 205026% 20%24% 21%17% 19%12% 14%

8% 10%6% 8%4% 4%2% 3%1% 2%

100% 100%

DISTRIBUTION

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STEP 4 – THE SPATIAL IMPACT (HOUSING)

House or brick structure (separate)

Flat in block

Town/cluster/etc house

Traditional dwelling

Informal dwelling (settlement)

Workers hostel

Room/flatlet on shared

House/flat/room in back yard

Informal in back yard

Other

0% 5% 10% 15% 20% 25% 30% 35% 40% 45%

39%

4%

1%

34%

9%

6%

3%

2%

2%

0%

2007 % HOUSING TYPE (124 526 units)HOUSING TYPETOTAL 2050 HOUSING

NEEDUNITS TO BE PROVIDED PER ANNUM

Other -

-

Informal in back yard -

-

House/flat/room in back yard

-

-

Room/flatlet on shared 2,628 Existing

Workers hostel 2,628 Existing

Informal dwelling (settlement) 10,513 Existing

Traditional dwelling 52,565 Existing

Town/cluster/etc house 63,078 62,169 1,554

Flat in block 78,848 73,592 1,840

House or brick structure (separate) 315,392 266,325 6,658

TOTAL 525,654 401,128 10,052 Note: Household size: 3.8 people0% 10% 20% 30% 40% 50% 60% 70%

60%

15%

12%

10%

2%

1%

1%

2050 % HOUSING TYPE (525 654 units)

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STEP 4 – THE SPATIAL IMPACT (ECONOMIC)

SECTOR ILEMBE 2010

2050 5% GROWTH

Manufacturing R 2,987 R 20,909

Finance, insurance, real estate and business services

R 2,033 R 11,536

Wholesale and retail trade, catering and accommodation

R 1,519 R 7,931

Agriculture R 1,008 R 7,210

Transport, storage and communication

R 738 R 6,489

General government R 965 R 4,326

Electricity, gas and water R 95 R 3,605

Tourism R 3,605

Construction R 290 R 2,884

Community, social and personal services

R 521 R 2,884

Mining and quarrying R 85 R 721

TOTAL R 10,241 R 72,099

GVA IN R’000,000

Mining and quarrying

Community, social and personal services

Construction

Tourism

Electricity, gas and water

General government

Transport, storage and communication

Agriculture

Wholesale and retail trade, catering and accommodation

Finance, insurance, real estate and business services

Manufacturing

0% 5% 10% 15% 20% 25% 30% 35%

1%

4%

4%

5%

5%

6%

9%

10%

11%

16%

29%

2010 AND 2050 GVA CONTRIBUTION PER SECTOR

2050 GVA CONTRIBUTION 2010 GVA CONTRIBUTION

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STEP 4 – THE SPATIAL IMPACT (ECONOMIC)

MANUFACTURING EXAMPLE:

• 7 076 ha industrial land generates R31 billion in eThekwini (R4.4 million per hectare)

• 4 752 ha industrial land will generate R20.9 billion in iLembe

• Current supply in Ilembe is 807 ha• Additional demand for 2050 is 3 954 ha

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STEP 5 – THE PLAN (EXISTING)

Existing Denser Development is shown in BROWN

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STEP 5 – THE PLAN (SHORT TERM)

Short-TermDevelopment is shown in ORANGE

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STEP 5 – THE PLAN (MEDIUM TERM)

Medium-TermDevelopment is shown in YELLOW

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STEP 5 – THE PLAN (LONG TERM)

Long-TermDevelopment is shown in LIGHT YELLOW

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THE LESSONS LEARNT

• Using statistical analysis as a tool for long term spatial planning is essential as it introduces reality into the process (something that is often lacking in these processes)

• Accurately predicting the future is impossible, but starting from a solid information base increases the probability of getting it right

• The iLembe 2050 Plan provides decision makers with a firm foundation for guiding future spatial development

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