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Transnet - Swazi Rail link – KwaZulu Natal Section Socio-economic impact analysis Draft

5 July 2013 Page 2

Glossary

Corridors : A corridor is a linear strip of land or area, connecting large activity nodes, traversing urban or inter-urban areas, surrounding a major transport facility or facilities providing an appropriate regional level of mobility and accessibility to adjacent areas, and containing a high concentration of population and mixed land uses” and “… accommodate major linear transport routes like heavy and light rail and/or freeways, large shopping concentrations etc., social, cultural and sporting facilities as well as a large amount of residential accommodation”.

Density : The number of units per unit of land area, e.g. dwelling units/ hectare. There are five measures of density:

i. population density: people / hectare. ii. gross dwelling unit density: dwelling units / total land area of a project or suburb including roads, public open space and non-residential land uses.

iii. net dwelling unit density: dwelling units / land occupied by residential plots only.

iv. building density: area of buildings / hectare.

v. settlement density: (dwelling units / total land occupied by settlement) also known as average gross dwelling unit’s density.

Densification : Densification is the increased use of space both horizontally and vertically within existing areas/ properties and new developments, accompanied by an increased number of units and/or population threshold.

Efficiency : Development that maximises development goals such as sustainability, integration, accessibility, affordability, and quality of living, relative to financial, environmental, and social costs, including on-going and future costs. Infill Development: Development of vacant or under-utilised land within existing settlements in order to optimise the use of infrastructure, increase urban densities and promote integration.

Integrated Development Plan: The strategic municipal development plan, reviewed on an annual basis, required by the MSA (Act 32 of 2000) which guides municipal decisions and budgets.

Land Use Management: Establishing or implementing any measure to regulate the use or a change in the form or function of land, and includes land development. Land Use Management System : A system used to regulate land use in a municipality, including a town planning or zoning scheme, or policies related to how land is used on a plot by plot basis.

Nodes: Nodes are focused areas where a higher intensity of land uses and activities are supported and promoted. Typically any given municipal area would accommodate a hierarchy of nodes that indicates the relative intensity of development anticipated for the various nodes, their varying sizes, and their dominant nature.

Spatial planning: planning of the way in which different activities, land uses and buildings are located in relation to each other, in terms of distance between them, proximity to each other and the way in which spatial considerations influence and are influenced by economic, social, political, infrastructural and environmental considerations.

Spatial Development Framework: A Spatial development Framework (SDF) is a core component of a Municipality’s economic, sectoral, spatial, social, institutional, environmental vision. In other words it is a tool for moving towards a desired spatial form for the Municipality.

Sector Plans: Municipal plans for different functions such as bio-diversity conservation, housing, transport, local economic development and disaster management. They may also be geographically based, for example a sub-region, settlement within a local Municipality or a component of that settlement.

Stakeholders : Agencies, organisations, groups or individuals who have a direct or indirect interest in a development intervention or its evaluation.

Town Planning Scheme or Zoning Scheme: A legal instrument for regulating the use of land in terms of provincial or national legislation, see Land Use Management System.

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Urban Edge: The urban edge is defined as an indicative boundary within the municipality with the sole purpose of containing physical development and sprawl and re-directing growth towards a more integrated, compact and efficient urban form.

Acronyms

AU Animal unit

CMIP Comprehensive Municipal Infrastructure Plan

CRC Capital Replacement Cost

DEA Department of Environmental Affairs

DFA Development Facilitation Act (Act 67 of 1995)

DoH Department of Health

GVA Gross value added

IDP Integrated Development Plan

LED Local Economic Development

LM Local Municipality

LUMS Land Use Management System

MSA Municipal Systems Act (Act 32 of 2000)

MTREF Medium Term Revenue and Expenditure Framework

NEMA National Environmental Management Act (Act 107 of 1998)

NSDP National Spatial Development Perspective

PGDS Provincial Growth and Development Strategy

SANParks South African National Parks

SDF Spatial Development Framework

SEA Strategic Environmental Assessment

SWOT Strengths, Weaknesses, Opportunities, Threats

VIP Ventilated Improved Pit Latrine

WSA Water Services Act (Act 108 of 1997)

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Contents 1 Introduction ....................................................................................................................................... 7 2 Regional Setting ............................................................................................................................... 7 3 Socio Economic Profile .................................................................................................................... 9

3.1 Data and data sources ............................................................................................................ 9

3.2 Demographic consideration ..................................................................................................... 9

3.2.1 Size ...................................................................................................................................... 9

3.2.2 Population age distribution ................................................................................................ 11

3.2.3 Population growth rate ....................................................................................................... 13

3.2.4 Future expected growth ..................................................................................................... 13

3.2.5 Spatial aspects of the population ....................................................................................... 14

3.3 Labour and Economic Analysis ............................................................................................. 16

3.3.1 Description of the labour force ........................................................................................... 16

3.3.2 Employment productivity ................................................................................................... 17

3.3.3 Economic structure and performance................................................................................ 21

4 Land Use ........................................................................................................................................ 26 4.1 Zululand District Municipality ................................................................................................. 27

4.1.1 uPhongolo Local Municipality ............................................................................................ 27

4.2 uMkhanyakude District Municipality ...................................................................................... 27

4.2.1 Jozini Local Municipality .................................................................................................... 28

4.2.2 The Big 5 False Bay Local Municipality ............................................................................. 28

4.2.3 Mtubatuba Local Municipality ............................................................................................ 29

4.3 uThungulu District Municipality .............................................................................................. 29

4.3.1 Mfolozi Local Municipality .................................................................................................. 29

4.3.2 Mhlathuze Local Municipality ............................................................................................. 30

5 Identified Risks and Benefits .......................................................................................................... 30 6 Works Cited .................................................................................................................................... 32

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Index of figures Figure 1: Household sizes per Population Group ................................................................................. 11 Figure 2: Population Pyramid uPhongolo LM ........................................................................................ 12 Figure 3: Population Pyramid Jozini LM ................................................................................................ 12 Figure 4: Population Pyramid The Big 5 False Bay LM ........................................................................ 12 Figure 5: Population Pyramid Mtubatuba LM ........................................................................................ 12 Figure 6: Population Pyramid Mfolozi LM .............................................................................................. 12 Figure 7: Population Pyramid Umhlathuze ............................................................................................ 12 Figure 8: Average annual population growth rate per LM ..................................................................... 13 Figure 9: Forecasted Population Growth per LM .................................................................................. 14 Figure 10: Composition of the labour force ........................................................................................... 16 Figure 11: Changes in employment in 1995 and 2011 - uPhongolo LM ............................................... 20 Figure 12: Changes in employment in 1995 and 2011 - Jozini LM ....................................................... 20 Figure 13: Changes in employment in 1995 and 2011 – The Big Five False Bay LM .......................... 20 Figure 14: Changes in employment in 1995 and 2011 - Mtubutuba LM ............................................... 20 Figure 15: Changes in employment in 1995 and 2011 - Mbonambi LM ............................................... 20 Figure 16: Changes in employment in 1995 and 2011 - uMhlatuze LM ............................................... 20 Figure 17: Combined GVA per economic sector (R'million) .................................................................. 22 Figure 18: Comparative GVA ................................................................................................................ 22 Figure 19: Tress index (10 industries) – KwaZulu Natal Section Part 1 ............................................... 23 Figure 20: Tress index (10 industries) - KwaZulu Natal Section Part 2 ................................................ 23 Figure 21: Illegal vehicle and pedestrian movement ............................................................................. 31

Index of tables Table 1: Population Size uPhongolo Local Municipality .......................................................................... 9 Table 2: Population Size Jozini Local Municipality .................................................................................. 9 Table 3: Population Size The Big 5 False Bay Local Municipality ........................................................ 10 Table 4: Population Size Mtubatuba Local Municipality ........................................................................ 10 Table 5: Population Size Mfolozi Local Municipality ............................................................................. 10 Table 6: Population Size uMhlathuze Local Municipality ...................................................................... 10 Table 8: Household size according to population group ....................................................................... 11 Table 9: Municipal demographic projections ......................................................................................... 13 Table 10: Population per EA type .......................................................................................................... 14 Table 11: KwaZulu Natal LM labour force (2011) ................................................................................. 16 Table 12: Employment per sector (KwaZulu Natal LMs) ....................................................................... 18 Table 13: Employment distribution per sector ....................................................................................... 19 Table 14: GVA output per labour unit (R’million) ................................................................................... 21 Table 15: Location coefficient: South Africa .......................................................................................... 24 Table 16: Location coefficient: Kwazulu-Natal ...................................................................................... 24 Table 17: Location coefficient: Sisonke ................................................................................................. 25

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Index of maps Map 1: Transnet - Swazi Rail link Alignment ........................................................................................... 7 Map 2: Transnet - Swazi Rail link Alignment - KwaZulu Natal Section ................................................... 8 Map 3: Population distribution ............................................................................................................... 15 Map 4: Land Cover ................................................................................................................................ 26

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Socio-Economic Impact Assessment 1 Introduction The aim of this document is to provide a socio-demographic profile that captures the relevant characteristics of the areas in KwaZulu Natal that will be affected by the Transnet-Transnet - Swazi Rail link.

This baseline socio-economic profile of the study area will be developed through a desktop review of available documentation and will address the following aspects:

• The regional setting of the study area;

• A socio-economic profile of the population residing in the study area;

• Existing land uses and infrastructure in the vicinity of the project-related infrastructure and along the proposed railway line routes; and

• Issues and concerns regarding the proposed undertaking when considering the above mentioned aspects.

2 Regional Setting The study area of this project, as indicated in Error! Reference source not found. , relates to the areas directly affected by the alignment of the Transnet - Swazi Rail link as well as all associated infrastructure. The rail link traverses the provinces of Mpumalanga and KwaZulu Natal, which form the main focus of the study, as well as the neighbouring country of Swaziland, that will be excluded from this study.

Map 1: Transnet - Swazi Rail link Alignment

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KwaZulu Natal is situated in the west of South Africa, and stretches between the Indian Ocean in the south and east, the Drakensberg mountain range in the west, and the Lebombo Mountains in the north. Due to its location the province share borders with three neighbouring countries and three provinces, and it is an important gateway to Swaziland, Mozambique and Lesotho, and domestically it borders Mpumalanga to the north, the Free State to the west and the Eastern Cape to the southwest.

KwaZulu Natal is the fifth largest South African province in terms of geographical size, but is one of the largest contributors to country’s economic output. It also features the largest total population per province (9.9 million). Its land area is 94,701km2 which constitutes 7.6% of South Africa’s total land area.

Six local municipalities, situated in three district municipalities in KwaZulu Natal will be affected by the proposed line. These municipalities, as indicated in Map 2 are:

• Zululand District Municipality

- Uphongolo Local Municipality (KZN 262).

• uMkhanyakude District Municipality

- Jozini Local Municipality (KZN 272);

- The Big 5 False Bay Local Municipality (KZN 273);

- Mtubatuba Local Municipality (KZN 275).

• uThungulu District Municipality

- Mfolozi (previously Mbonambi) Local Municpality (KZN 271);

- uMhlathuze Local Municipality (KZN 282).

Map 2: Transnet - Swazi Rail link Alignment - KwaZu lu Natal Section

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3 Socio Economic Profile

3.1 Data and data sources In terms of the approach to the analysis the data was described at the local municipal level and in the conclusions trends and tendency as extrapolated to draw conclusions on the focus areas of the project. Secondly, local economies and demographic areas are open and it is practically impossible to isolate a local or part of a local economy. The approach therefore was, where appropriate, to do the analysis on a comparative basis by comparing the municipality with the profile of the District Municipality, the economy or demographics of Kwazulu-Natal and also with the broader context of the national economy.

3.2 Demographic consideration The population of a municipal area forms part of the ultimate objective of the development process, as well as being a subject in the process, since the people provide labour and entrepreneurship for production and also consume the output of production. Demography does not form part of economic analysis but needs to be taken into account as the population forms the basis of all economic activity in the area.

3.2.1 Size

The size of the population and in particular the number of households are some of the most important determinants of the needs of the inhabitants. These needs are expressed in the demand for infrastructural and social services and the potential on the extent of involvement in economic activities. It also forms the basis from which all other calculations are made.

Table 1: Population Size uPhongolo Local Municipali ty

Population Size for Uphongolo Local Municipality - 2011

Population Group Male Female Total Percentage

Black population 58 494 66 373 124 867 98

Coloured population 60 46 106 0

Asian population 98 83 181 0

White population 992 950 1 942 2

Table 2: Population Size Jozini Local Municipality

Population Size for Jozini Local Municipality- 2011


Black population 85278 99675 184962 99.4

Coloured population 95 89 184 0.1

Asian population 256 189 445 0.2

White population 274 259 533 0.3

98%

2%Black population

Colouredpopulation

Asianpopulation

Whitepopulation

99.4%

Blackpopulation

Colouredpopulation

Asianpopulation

Whitepopulation

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Table 3: Population Size The Big 5 False Bay Local Municipality

Population Size for The big 5 False bay Local Munic ipality – 2011






Table 4: Population Size Mtubatuba Local Municipali ty

Population Size for Mtubatuba Local Municipality - 2011






Table 5: Population Size Mfolozi Local Municipality

Population Size for Mfolozi Local Municipality - 20 11






Table 6: Population Size uMhlathuze Local Municipal ity

Population Size for uMhlathuze Local Municipality - 2011






The composition of the population is given as a composite as there is a similar trend in all the six local municipalities. The largest segment of the population is the Black African group. It accounts for no less that 87.9% where least prevalent. In some local municipalities like Jozini and Mfolozi local

99%

0%

0%1%

Black population

Coloured population

Asian population

White population

88%

1%4%

7%

Black population

Colouredpopulation

Asian population

White population

92%

2%

1% 5%

Blackpopulation

Colouredpopulation

Asianpopulation

Whitepopulation

96%

1%0%

3%Black population

Colouredpopulation

Asian population

White population

5 July 2013 Page 11

97%

0%0% 3%

KZN262: Uphongolo

99%

0%1%

0%

KZN272: Jozini

96%

4%

KZN273: The Big 5 False Bay

97%

1%2%

KZN275: Mtubatuba

99%

1%

KZN281: Mfolozi

97%

3%

KZN262: Uphongolo

municipalities, the figure is as high as 99%. It is followed by a relatively low white population. The third highest segment is then the coloured population group with exception to Mfolozi and uMhlathuze local municipality where there is a comparatively larger Asian population. Table 7: Household size according to population gro up

Uphongolo Local

Municipality

(KZN262)

Jozini Local Municipality

(KZN272)

The Big 5 False Bay

Local Municipality

(KZN273)

Mtubatuba Local

Municipality (KZN275)

Mfolozi Local Municipality

(KZN281)

uMhlathuze Local

Municpality (KZN282)

Black African 27919 (97.0%) 38427 (98.9%) 7646 (95.6%) 33989 (85.7%) 25149 (98.3%) 74221 (85.7%)

Coloured 22 (0.1%) 45 (0.1%) 20 (0.3%) 158 (0.8%) 43 (0.2%) 705 (0.8%)

Indian or Asian 54 (0.2%) 130 (0.3%) 22 (0.3%) 123 (4.0%) 56 (0.2%) 3482 (4.0%)

White 716 (2.5%) 135 (0.3%) 292 (3.7%) 584 (9.2%) 310 (1.2%) 7926 (9.2%)

Other 60 (0.2%) 113 (0.3%) 20 (0.3%) 51 (0.3%) 26 (0.1%) 275 (0.3%)

TOTAL 28771 38850 8000 34905 25584 86609

Figure 1: Household sizes per Population Group

3.2.2 Population age distribution

A population pyramid graphically displays a population’s age and gender composition by showing numbers or proportions of males and females in each age group; the pyramid provides a clear picture of a population’s characteristics. The sum total of all the age-gender groups in the pyramid equals 100 per cent of the population.

The population pyramid of the six local municipalities show larger numbers in the younger age groups, this indicates rapid growth. There are also a large number of people in the economically active age group (15-56 years). There are also a significantly higher number of people in the 65 years plus age groups which might point to a significant number of retired people settling in the area.

Migrant labour is not a factor in the municipalities as there are about equal amounts of males and females in the municipal area. However, there are anomalies in some cohorts between 20 years and 50 years. There is no apparent reason that explains this.

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Figure 2: Population Pyramid uPhongolo LM

Figure 4: Population Pyramid The Big 5 False Bay LM

Figure 5: Population Pyramid Mtubatuba LM

Figure 6: Population Pyramid Mfolozi LM

Figure 7: Population Pyramid Umhlathuze

-3 000 000 -2 000 000 -1 000 000 0 1 000 000 2 000 000 3 000 000

0 - 4

10 - 14

20 - 24

30 - 34

40 - 44

50 - 54

60 - 64

70 - 74

80 +

Population 2011 - uPhongolo

Male Female

-3 000 -2 000 -1 000 0 1 000 2 000 3 000

0 - 4

5 - 9

10 - 14

15 -19

20 - 24

25 - 29

30 - 34

35 - 39

40 - 44

45 - 49

50 - 54

55 - 59

60 - 64

65 - 69

70 - 74

75 - 79

80 +

Population 2011 - Big 5 False Bay

Male Female

-15 000 -10 000 -5 000 0 5 000 10 000 15 000

0 - 4

5 - 9

10 - 14

15 -19

20 - 24

25 - 29

30 - 34

35 - 39

40 - 44

45 - 49

50 - 54

55 - 59

60 - 64

65 - 69

70 - 74

75 - 79

80 +

Population 2011 - Mtubatuba

Male Female

-10 000 -5 000 0 5 000 10 000

0 - 4

10 - 14

20 - 24

30 - 34

40 - 44

50 - 54

60 - 64

70 - 74

80 +

Population 2011 - Mfolozi

Male Female-30 000 -20 000 -10 000 0 10 000 20 000 30 000

0 - 4

10 - 14

20 - 24

30 - 34

40 - 44

50 - 54

60 - 64

70 - 74

80 +

Population 2011 - Umhlathuze

Male Female

-15 000 -10 000 -5 000 0 5 000 10 000 15 000 20 000

0 - 4

10 - 14

20 - 24

30 - 34

40 - 44

50 - 54

60 - 64

70 - 74

80 +

Population 2011 - Jozini LM

Male Female

Figure 3: Population Pyramid Jozini LM

5 July 2013 Page 13

3.2.3 Population growth rate

The population growth rate and future projections are of great importance for planning purposes. A negative or below-average growth rate is indicative of an out-migration of people – normally due to a lack of economic growth and the concomitant loss of job opportunities in the municipal area. The reverse is true for an above-average growth rate.

The annual growth rate is calculated by looking at the incremental increase/decrease from the 2001 to 2011 census years expressed as a percentage, over the number of observation years in order to get an annual average. Mtubatuba had the highest growth rate of 1.9% as compared to the other local municipalities.

Figure 8: Average annual population growth rate per LM

3.2.4 Future expected growth

Population and household growth is one element that determines the long-term demand for goods and services. Based on historical population figures from 2000 to 2011, a trend analysis was done for the municipality. The trend analysis is based on historical data. This data was used to determine the municipal growth rate and extrapolate the figures to give a projected growth for the municipality up to 2025.

Table 8: Municipal demographic projections

Local Municipality Attribute 2001 2011 2015 2020 2025 KZN272: Jozini

Population 183,669 186,503 187,552 188,871 190,199

Households 33,589 38,849 41,109 44,120 47,351

HH size 5.5 4.8 4.6 4.3 4.0

KZN273: The Big 5 False Bay

Population 31,828 35,257 36,659 38,490 40,412

Households 6,214 7,998 8,866 10,085 11,472

HH size 5.1 4.4 4.1 3.8 3.5

KZN275: Mtubatuba

Population 145,179 175,425 189,097 207,696 228,123

Households 24,826 34,905 40,350 48,367 57,976

HH size 5.8 5.0 4.7 4.3 3.9

KZN282: uMhlathuze

Population 288,698 334,458 354,156 380,418 408,628

Households 67,127 86,609 96,118 109,484 124,710

1.3%

1.4%

0.5%

0.1%

1.0%

1.9%

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%

2.0%

KZN281: Mfolozi KZN282:

uMhlathuze

KZN262:

UPhongolo

KZN272: Jozini KZN273: The Big 5

False Bay

KZN275:

Mtubatuba

5 July 2013 Page 14

Local Municipality Attribute 2001 2011 2015 2020 2025

HH size 4.3 3.9 3.7 3.5 3.3

KZN262: Uphongolo Population 120,080 127,238 130,018 133,580 137,238

Households 24,814 28,772 30,477 32,752 35,197

HH size 4.8 4.4 4.3 4.1 3.9

KZN275: Mflolozi Population 106942 122869 122869 122869 122869

Households 19143 25584 25584 25584 25584

HH size 5.6 4.8 4.8 4.8 4.8

Figure 9: Forecasted Population Growth per LM

3.2.5 Spatial aspects of the population

This section investigates how the population of the within the six local municipalities is distributed and in what type of areas people lives. This helps to visualise the data presented previously in this section. The table below shows the population per Enumerator Area type in the municipality. The data shows that the municipality’s population is largely formal in nature with little informal and traditional population.

Table 9: Population per EA type

Fo

rma

l

resi

de

nti

al

Info

rma

l

resi

de

nti

al

Tra

dit

ion

al

resi

de

nti

al

Fa

rms

Pa

rks

an

d

recr

ea

tio

n

Co

lle

ctiv

e l

ivin

g

qu

art

ers

Ind

ust

ria

l

Sm

all

ho

ldin

gs

Va

can

t

Co

mm

erc

ial

KZN272: Jozini 10097 0 173180 79 109 210 145 0 1900 782

KZN273: The Big 5 False Bay 3642 189 28449 2933 45 0 0 0 0 0

KZN275: Mtubatuba 22585 0 146864 1733 160 264 0 2947 593 280

KZN282: uMhlathuze 128056 4481 182659 9038 150 6907 942 0 404 1822

KZN262: Uphongolo 16957 1116 86492 21713 30 39 0 0 638 253

KZN281: Mfolozi 2014 563 117313 2523 75 74 0 0 144 182

Total 183351 6349 734957 38019 569 7494 1087 2947 3679 3319

0

50 000

100 000

150 000

200 000

250 000

300 000

350 000

400 000

450 000

2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

KZN281: Mfolozi KZN282: uMhlathuze KZN262: UPhongolo

KZN272: Jozini KZN273: The Big 5 False Bay KZN275: Mtubatuba

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The map presents the population data spatially. One can immediately see specific population concentrations. uMhlathuzi, Mtubatuba and the Jozini show the most densely populated areas in the study area. The rest of the population is spread out. It is interesting to note that the population concentration areas are close to main access routes, emphasising the importance of accessibility in development.

Map 3: Population distribution

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3.3 Labour and Economic Analysis In the analysis of the labour and employment situation in a municipal area, it is necessary to focus attention on the size and spatial distribution of the labour force. Secondly, the characteristics of the labour market should be analysed. To this end, it is necessary to examine the supply of labour, which is derived from figures on the economically active population in a municipal area. The demand for labour, on the other hand, is an indication of employment opportunities, which are determined by the economic structure of an area along with the level and growth in economic activities. Unemployment, and in a sense trans frontier commuting, provides an indication of the difference between supply and demand and implies that equilibrium in the labour market necessitates both expansion of economic activity and the curtailment of population growth.

Figure 10: Composition of the labour force

A third issue that should be addressed is involvement in the peripheral sector, as not all potential workers are active in the labour market. Finally, the quality of the labour force needs to be analysed as it provides information on the employability of the workers.

The term labour force refers to those people who are available for employment in a certain area. Figure 8 illustrates the different components of the labour force and the relationship between them.

Formally employed refers to people who are selling their labour or who are self-employed in the formal sector of the economy, for pay or profit. Informally employed includes all people who are active, for pay or profit, in the informal or unregistered sector of the economy. Unemployed are persons actively looking for a job, but who are not in any type of paid employment.

3.3.1 Description of the labour force

Table 10: KwaZulu Natal LM labour force (2011)

UPhongolo Local

Municipality


The Big Five False Bay

Local Municipality

Mtubatuba Local

Municipality

Mbonambi Local

Municipality

uMhlathuze Local

Municipality

Description Number Number Number Number Number Number

Population 144,573 217,005 36,853 49,189 123,984 348,142

Economically active 59,302 81,591 17,903 27,581 56,789 188,400

Formal and informal (Total) 21,037 19,455 6,489 17,560 19,773 88,328

Formal 16,869 14,922 4,836 14,003 14,562 69,235

Formal - Highly skilled 3,168 2,936 831 2,868 1,770 12,441

Formal - Skilled 6,129 6,329 2,136 5,868 5,704 29,385

Formal - Semi- and unskilled 7,572 5,657 1,869 5,268 7,087 27,409

Informal 4,168 4,533 1,652 3,556 5,211 19,093

Unemployed 7,872 8,546 1,020 1,532 6,138 17,754

Unemployment rate (%) 27.2 30.5 13.6 8.0 23.7 16.7

Labour force participation rate (%) 35.5 23.8 36.2 63.7 34.8 46.9

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Table 10 describes the labour force of the LMs in KwaZulu Natal that will be directly affected by the proposed rail link. According to the 2011 data acquired from the Quantec database the LMs have a varying rate of employment. The unemployment rate varies between 8% and 30% for the Mtubutuba LM and Jozini LM respectively. This is accompanied by a labour force participation rate ranging between 24% and 64% for the same extreme LMs.

Although this data is regarded as a good representation of the actual situation, the size of the informal sector, which includes subsistence agriculture (highly applicable in the municipal areas), is difficult to establish with a reasonable degree of accuracy and can easily be under-estimated. One reason for this is that people involved in informal activity often classify themselves as unemployed.

3.3.1.1 Labour force participation rate

Obtaining the participation rates, involves calculating the labour force or the economically active population relative to the potential labour force, (i.e. the population in the age group 15 to 64 years). These rates reflect the percentages of the said population that are actually economically active.

The following figures describe each of the most important elements over time. This is done to establish patterns in the Labour force and to assess any changes that might have taken place.

3.3.1.2 Economic active population

The economic active population includes the formally employed, the unemployed, and those persons active in the informal/ unregistered sector. The terms ‘supply of labour’ and the ‘labour force’ are used as synonyms for the economically active population.

The number of people in the economically active population is highly dependent on the population age distribution. The percentage of the population that is economically active range between approximately 40% to 50%.

3.3.1.3 Employment

The population employed in the formal sector exceeds the informal sector employment and the unemployed population. Employment rates are highly influenced by the regional and national economic climate, and during economic hardship the formal sector employment tend to decrease. This usually lead to an increase in unemployment, but also often an increase in informal sector employment as people who lose their jobs undertake entrepreneuring ventures.

3.3.1.4 Labour force participation rate

Labour force participation rate indicates the labour force (economically active population) as a percentage of the population in the age group 15– 64 years

An increase in the participation rate can be the result of more women entering the labour market or the outflow of the potential economically active people from a municipal area due to harsh economic conditions, which would ‘artificially’ increase the participation rate. A low participation rate in a municipal area can be ascribed to the large number of male migrant workers moving out of the municipal area or the proliferation of peripheral activities in the municipal area. The latter does seem to be the case for some of the LMs, especially those close to the borders of the neighbouring countries.

3.3.2 Employment productivity

Employment is always a priority for the Council and it is obvious that development and growth strategies will have to support job creation.

3.3.2.1 Employment per sector

The table below shows the employment per sector. The structure of employment and the extent of the link between employment and the level of economic activity is important.

5 July 2013 Page 18

Table 11: Employment per sector (KwaZulu Natal LMs)

Agr

icul

ture

[S

IC: 1

]

Min

ing

[S

IC: 2

]

Man

ufac

turin

g

[SIC

: 3]

Util

ities

[S

IC: 4

]

Con

stru

ctio

n

[SIC

: 5]

Tra

de

[SIC

: 6]

Tra

nspo

rt

[SIC

: 7]

Bus

ines

s se

rvic

es

[SIC

: 8]

Com

mun

ity s

ervi

ces

[S

IC: 9

2, 9

5-6

, 99,

0]

Gen

eral

gov

ernm

ent

[SIC

: 91,

94]

Tot

al

uPho

ngol

o

1996 15,900 625 1,339 82 1,089 2,477 552 674 1,403 1,512 25,654

2001 13,249 252 1,343 124 876 2,528 511 921 2,153 1,968 23,927

2006 8,816 143 1,595 103 1,422 2,980 564 1,029 3,095 2,976 22,724

2011 2,834 221 1,587 67 1,916 3,099 709 1,131 4,057 5,415 21,037

Avg. Change -4.8% -3.6% 1.4% -0.9% 4.2% 1.5% 1.9% 5.1% 12.0% 17.0% -1.0%

Jozi

ni

1996 2,720 871 433 19 980 1,917 376 765 2,235 2,194 12,509

2001 2,112 123 259 24 585 1,927 380 994 2,997 2,443 11,844

2006 2,523 80 698 16 677 3,507 622 1,206 3,563 2,991 15,882

2011 1,277 155 1,244 7 762 5,158 1,046 1,436 4,072 4,300 19,455

Avg. Change -3.2% -4.9% 9.8% -3.8% -1.6% 9.7% 11.1% 6.3% 5.1% 6.3% 3.2%

Big

Fiv

e

1996 3,757 13 183 5 306 735 310 129 358 435 6,230

2001 2,069 13 220 30 371 944 266 316 609 613 5,451

2006 1,866 9 426 30 291 1,726 156 265 718 745 6,232

2011 782 14 552 26 233 2,686 117 213 805 1,062 6,489

Avg. Change -4.8% 2.0% 13.1% 97.5% -0.9% 16.6% -3.6% 8.1% 8.6% 10.3% 0.1%

Mtu

batu

ba

1996 5,393 53 1,152 14 516 1,423 307 507 1,112 1,739 12,216

2001 3,676 53 983 24 472 2,016 273 943 1,617 2,100 12,158

2006 3,743 53 1,506 22 717 3,089 378 1,037 2,139 2,862 15,546

2011 1,586 99 1,912 15 921 4,045 565 1,152 2,615 4,650 17,560

Avg. Change -4.3% 8.6% 3.9% 0.7% 4.7% 12.2% 5.1% 10.9% 8.4% 10.9% 2.4%

Mbo

nam

bi

1996 8,193 1,152 2,195 27 2,144 2,470 1,084 765 1,386 640 20,056

2001 7,324 521 1,625 30 1,055 2,215 784 1,024 2,360 944 17,882

2006 5,917 457 2,821 47 1,360 3,534 1,187 1,421 2,089 899 19,733

2011 2,045 831 3,917 48 1,667 4,762 1,934 1,724 1,926 920 19,773

Avg. Change -4.5% -1.3% 4.3% 3.6% -1.8% 5.0% 4.3% 8.6% 3.4% 4.1% -0.2%

uMhl

athu

ze

1996 8,902 3,931 9,706 214 7,091 12,856 5,618 7,432 10,664 9,600 76,015

2001 9,041 1,804 12,338 348 6,206 15,868 4,961 10,059 13,592 10,355 84,572

2006 9,164 1,402 12,046 345 5,773 17,800 4,774 11,269 14,273 11,426 88,272

2011 3,772 2,600 10,677 274 5,400 17,992 5,415 12,751 15,121 14,326 88,328

Avg. Change -3.4% -1.7% 1.4% 2.0% -1.4% 2.8% -0.1% 5.4% 2.6% 3.3% 1.3%

The most noticeable is the differential growth rates in employment creation between the sectors. The agriculture industry has seen a decline in all of the LMs and the industries of the tertiary sector has seen an increase for all 6 of the LMS. The total employment for most of the LMs has also increased with the exception of two (Mbonambi and uPhonglo) that saw a slight decrease. The implication of job losses in the agriculture industry is important since these workers are jobless and have to leave

5 July 2013 Page 19

farms. They usually end up in informal settlements on the urban periphery. This lead to a high number of people being affected that subsequently implies a need for about new households to be provided with services. The variation in primary and secondary sector employment and the steady growth in the tertiary sector emphasis the role of the LMs as service centres.

Table 12 shows the employment distribution per sector. These figures are expressed in terms of the distribution of employment across the sectors. It should be noted that the largest economic sectors (GVA contributors) are not necessarily the biggest contributors to employment creation.

Table 12: Employment distribution per sector A

gric

ultu

re

[SIC

: 1]

Min

ing

[S

IC: 2

]

Man

ufac

turin

g

[SIC

: 3]

Util

ities

[S

IC: 4

]

Con

stru

ctio

n

[SIC

: 5]

Tra

de

[SIC

: 6]

Tra

nspo

rt

[SIC

: 7]

Bus

ines

s se

rvic

es

[SIC

: 8]

Com

mun

ity

serv

ices

[S

IC:

92, 9

5-6,

99,

0]

Gen

eral

go

vern

men

t [S

IC: 9

1, 9

4]

Tot

al

UPhongolo Local Municipality 13.5% 1.0% 7.5% 0.3% 9.1% 14.7% 3.4% 5.4% 19.3% 25.7% 100.0%

Jozini Local Municipality 6.6% 0.8% 6.4% 0.0% 3.9% 26.5% 5.4% 7.4% 20.9% 22.1% 100.0%

Big Five False Bay Local Municipality 12.0% 0.2% 8.5% 0.4% 3.6% 41.4% 1.8% 3.3% 12.4% 16.4% 100.0%

Mtubatuba Local Municipality 9.0% 0.6% 10.9% 0.1% 5.2% 23.0% 3.2% 6.6% 14.9% 26.5% 100.0%

Mbonambi Local Municipality 10.3% 4.2% 19.8% 0.2% 8.4% 24.1% 9.8% 8.7% 9.7% 4.7% 100.0%

uMhlathuze Local Municipality 4.3% 2.9% 12.1% 0.3% 6.1% 20.4% 6.1% 14.4% 17.1% 16.2% 100.0%

3.3.2.2 Changes in employment

Employment is not a static issue and changes in employment are very important. The figures below provide a comparison between the employment situation in in the respective LMs in 1995 and in 2011.

From the tables the overall decrease in primary sector employment becomes evident. The drastic decrease in agriculture employment can be seen, as well as the decrease in mining and quarrying (with the exception of Mtubutuba LM that saw a very slight (almost constant) increase).

The secondary sector employment is very variable in each of the six LMs. Uphongolo and Mtubutuba saw an increase over each of the secondary sector industries. The other municipalities all saw an increase in manufacturing, but a decrease in the construction sector.

All tertiary sector industries increased in all six of the LMs.

3 July 2013 Page 20

Figure 11: Changes in employment in 1995 and 2011 - uPhongolo LM Figure 12: Changes in employment in 1995 and 2011 - Jozini LM

Figure 13: Changes in employment in 1995 and 2011 – The Big Five False Bay LM Figure 14: Changes in em ployment in 1995 and 2011 - Mtubutuba LM

Figure 15: Changes in employment in 1995 and 2011 - Mbonambi LM Figure 16: Changes in employment in 19 95 and 2011 - uMhlatuze LM

0%

10%

20%

30%

40%

50%

60%

70%

19952011

0%

5%

10%

15%

20%

25%

30%

19952011

0%10%20%30%40%50%60%70%

1995

2011 0%10%20%30%40%50%60%

1995

2011

0%5%

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

19952011

0%

5%

10%

15%

20%

25%

19952011

5 July 2013 Page 21

3.3.3 Economic structure and performance

3.3.3.1 Gross value added

Economic performance of a municipal area’s economic system, in terms of factors such as production activity, can be measured by the Gross Value Added (GVA). The analysis will focus on the GVA produced by the primary, secondary and tertiary economic sectors over time; the GVA produced by each LM and compare the GVA of the six LMs.

The primary sector of the economy involves changing natural resources into primary products. Most products from this sector are considered raw materials for other industries. Major businesses in this sector normally include agriculture, agribusiness, fishing, forestry and all mining and quarrying industries.

The secondary sector generally takes the output of the primary sector and manufactures finished goods or where they are suitable for use by other businesses, for export, or sale to domestic consumers. This sector is often divided into light industry and heavy industry. The sector is made up of manufacturing, electricity, gas and water, and construction.

The tertiary or services sector consists of the "soft" parts of the economy, i.e. activities where people offer their knowledge and time to improve productivity, performance, potential, and sustainability. The basic characteristic of this sector is the production of services instead of end products. Businesses in this sector include wholesale and retail trade, catering and accommodation, transport, storage, communication, finance, insurance, real estate, business services, community, social and personal services, and general government.

3.3.3.2 Labour output

The table below shows the GVA output per labour sector for each of the LMs over the past 16 years.

Table 13: GVA output per labour unit (R’million)

UPhongolo Local Municipality


The Big Five False Bay Local

Municipality

Mtubatuba Local Municipality

Mbonambi Local Municipality

uMhlathuze Local Municipality

Prim

ary

Sec

tor

Sec

onda

ry

Sec

tor

Ter

tiary

S

ecto

r

Prim

ary

Sec

tor

Sec

onda

ry

Sec

tor

Ter

tiary

S

ecto

r

Prim

ary

Sec

tor

Sec

onda

ry

Sec

tor

Ter

tiary

S

ecto

r

Prim

ary

Sec

tor

Sec

onda

ry

Sec

tor

Ter

tiary

S

ecto

r

Prim

ary

Sec

tor

Sec

onda

ry

Sec

tor

Ter

tiary

S

ecto

r

Prim

ary

Sec

tor

Sec

onda

ry

Sec

tor

Ter

tiary

S

ecto

r

1995 396 208 409 143 77 472 83 31 124 116 144 339 278 355 430 1095 2278 3864

1996 486 220 436 188 73 497 88 35 140 139 146 370 398 363 442 1603 2881 4120

1997 511 231 452 183 71 506 83 41 153 137 148 389 431 349 448 1722 3150 4274

1998 544 220 473 175 63 527 79 43 167 133 137 419 466 310 451 1773 3276 4484

1999 501 219 499 127 58 542 69 47 183 126 133 446 408 297 464 1410 3607 4695

2000 515 241 532 118 58 568 66 55 200 133 143 482 449 311 483 1430 4173 4958

2001 517 268 575 106 61 600 65 66 217 131 157 521 439 323 515 1432 4375 5233

2002 529 277 615 103 65 641 69 69 232 136 169 561 423 351 557 1358 4644 5488

2003 520 294 663 105 69 698 70 72 245 151 184 610 445 382 609 1435 4660 5774

2004 488 330 707 110 84 749 71 82 250 159 214 660 446 443 658 1411 4738 5978

2005 415 369 774 107 105 834 65 94 262 159 252 736 423 529 738 1274 4935 6348

2006 401 412 841 118 132 919 70 108 272 156 298 815 394 633 816 1179 5133 6671

2007 391 459 928 130 166 1023 75 124 296 165 349 895 387 763 933 1163 5430 7066

2008 386 474 999 144 203 1112 83 139 311 198 385 972 395 887 1027 1122 5461 7338

2009 326 491 1014 150 226 1191 82 140 323 203 399 1026 363 840 1098 1046 4231 7399

2010 345 524 1091 138 265 1243 84 154 352 212 443 1089 394 953 1136 1107 4622 7626

2011 336 562 1187 140 291 1330 84 156 386 216 485 1186 397 993 1226 1131 4900 7938

% G

row

th

Per

ann

um

-0.9 10.1 11.2 -0.1 16.3 10.1 0.1 24.0 12.4 5.0 14.0 14.7 2.5 10.6 10.9 0.19 6.8 6.2

5 July 2013 Page 22

It is not possible to draw any specific conclusion regarding labour productivity. The interplay between labour and capital is not assessed. In agriculture there was a decline in GVA output per labour unit. All other labour units reported an increase in GVA output to labour. If one assumes that these labour units show significant opportunities for substituting labour with capital, then one might conclude that there was an overall increase in labour productivity over the assessment period.

Figure 17: Combined GVA per economic sector (R'mill ion)

Figure 17 indicates the largest and strongest growing economic sector over the complete study area is the tertiary sector. This means its economy is dominated by the service sector. The secondary sector has shown some increase in recent years, but the effect of the international recession can be clearly seen in 2009. The primary sector is getting smaller and does not contribute a lot to the economy in terms of GVA.

Figure 18 compares total the GVA contribution of each of the studied LMs. Interestingly is the significant contribution of uMhlathuze LM compared to the other LMs. This is attributed to the significant role Richard Bay situated in this LM plays in exports and other secondary activities. The decline in 2009, coinciding with the international recession is most likely due to fewer exports and lower economic activity that goes hand in hand with a recession.

Figure 18: Comparative GVA

3.3.3.3 Diversification and concentration in the ec onomy

The level of diversification or concentration of a municipal area’s economy is measured by a tress index. A tress index of zero represents a totally diversified economy. On the other hand, the higher

0

2 000

4 000

6 000

8 000

10 000

12 000

14 000

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

GV

A (

R'm

illio

n)

GVA output per Sector

Total Primary sector Total Secondary sector Total Tertiary sector

0

2 000

4 000

6 000

8 000

10 000

12 000

14 000

16 000

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Tota

l GV

A (

R'm

illio

ns)

Total GVA contribution per LM

UPhongolo Local Municipality Total Jozini Local Municipality Total

The Big Five False Bay Local Municipality Total Mtubatuba Local Municipality Total

Mbonambi Local Municipality Total uMhlathuze Local Municipality Total

5 July 2013 Page 23

the index (closer to 100), the more concentrated or vulnerable the municipal area’s economy to exogenous variables, such as adverse climatic conditions, commodity price fluctuations, etc.

The following two figures display the respective tress indices for the LMs compared to each other, as well as the national and provincial rates.

Figure 19: Tress index (10 industries) – KwaZulu Na tal Section Part 1

Figure 20: Tress index (10 industries) - KwaZulu Na tal Section Part 2

Figure 19 shows that the tress indices of the uPhongolo LM and Jozini LM follow a similar trend to the national and provincial indices, with uPhongolo showing a slightly higher level of diversification. The Big Five False Bay LM however has shown a decrease in diversification over the past 10 years, increasing the vulnerability of the LM.

The Tress indices indicated in Figure 20 for the three LMs follow the same pattern and are very similar to the provincial and national indices.

3.3.3.4 Location coefficient

Basic/Non-Basic ratios are calculated in order to determine the drivers of an economy. The ratio is expressed as the employment in a sector in the local economy divided by the total employment in the local economy. This is in turn divided by the same ratio for the district, provincial or national economy. A ratio greater than one, implies that there is relatively more employment in this sector than in the corresponding economy it is compared to. It therefore generates more than what can locally be consumed and the sector is thus a net exporting sector. This implies that it generates income for the local economy. The opposite is then true for ratios smaller than one.

0

10

20

30

40

50

60

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Tress Index - 1

South Africa Kwazulu-NatalUPhongolo Local Municipality Jozini Local MunicipalityThe Big Five False Bay Local Municipality

0

10

20

30

40

50

60

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Tress Index - 2

South Africa Kwazulu-Natal Mtubatuba Local MunicipalityMbonambi Local Municipality uMhlathuze Local Municipality

5 July 2013 Page 24

Table 14: Location coefficient: South Africa

Ag

ricu

ltu

re,

fore

stry

an

d

fish

ing

Min

ing

an

d q

ua

rry

ing

Ma

nu

fact

uri

ng

Ele

ctri

city

, g

as

an

d w

ate

r

Co

nst

ruct

ion

Wh

ole

sale

an

d r

eta

il t

rad

e,

cate

rin

g a

nd

acc

om

mo

da

tio

n

Tra

nsp

ort

, st

ora

ge

an

d

com

mu

nic

ati

on

Fin

an

ce,

insu

ran

ce,

rea

l

est

ate

an

d b

usi

ne

ss s

erv

ice

s

Co

mm

un

ity

, so

cia

l a

nd

pe

rso

na

l se

rvic

es

Ge

ne

ral

go

ve

rnm

en

t

P5D06M02: UPhongolo Local Municipality 5.90 0.28 1.10 1.26 1.62 0.79 0.89 0.42 1.11 1.33

P5D07M02: Jozini Local Municipality 2.74 0.21 0.84 0.16 0.56 1.55 1.27 0.43 1.52 1.42

P5D07M03: The Big Five False Bay Local Municipality 5.23 0.09 1.14 1.56 0.67 2.34 0.31 0.26 0.86 0.96

P5D07M05: Mtubatuba Local Municipality 4.28 0.16 1.33 0.35 0.66 1.27 0.84 0.33 0.94 1.52

P5D08M01: Mbonambi Local Municipality 3.79 1.00 1.93 0.72 1.02 1.10 1.58 0.44 0.36 0.18

P5D08M02: uMhlathuze Local Municipality 1.32 0.83 1.74 1.08 0.91 0.86 1.37 0.59 1.06 0.69

When compared at a national level the Agriculture, Manufacturing, trade and government sectors show the best performance. At this level agriculture is all LMs strongest performing sector. uMhlathuze however shows the best performance in wholesale and retail trade that is attributed to the Richard Bay Port and associated activities.

Table 15: Location coefficient: Kwazulu-Natal

Ag

ricu

ltu

re,

fore

stry

an

d

fish

ing

Min

ing

an

d q

ua

rry

ing

Ma

nu

fact

uri

ng

Ele

ctri

city

, g

as

an

d w

ate

r

Co

nst

ruct

ion

Wh

ole

sale

an

d r

eta

il t

rad

e,

cate

rin

g a

nd

acc

om

mo

da

tio

n

Tra

nsp

ort

, st

ora

ge

an

d

com

mu

nic

ati

on

Fin

an

ce,

insu

ran

ce,

rea

l

est

ate

an

d b

usi

ne

ss s

erv

ice

s

Co

mm

un

ity

, so

cia

l a

nd

pe

rso

na

l se

rvic

es

Ge

ne

ral

go

ve

rnm

en

t







In the provincial context Agriculture remains the best performer. Trade and governmental services also show good overall performance. Mbonambi and uMhalthuze however displays the best performance in the mining and quarrying sector.

When economic sectors are analysed in terms of how well it functions at district level, some important aspects emerges. With the exception of Mbonambi LM, agricultural contribution is no longer seen as such an important economic sector (it still plays an important role in some of the LMs, but not all). This indicates that other local municipalities in the district contribute much more to this sector than the studied LMs.

5 July 2013 Page 25

Table 16: Location coefficient: Sisonke

Ag

ricu

ltu

re,

fore

stry

an

d

fish

ing

Min

ing

an

d q

ua

rry

ing

Ma

nu

fact

uri

ng

Ele

ctri

city

, g

as

an

d w

ate

r

Co

nst

ruct

ion

Wh

ole

sale

an

d r

eta

il t

rad

e,

cate

rin

g a

nd

acc

om

mo

da

tio

n

Tra

nsp

ort

, st

ora

ge

an

d

com

mu

nic

ati

on

Fin

an

ce,

insu

ran

ce,

rea

l

est

ate

an

d b

usi

ne

ss s

erv

ice

s

Co

mm

un

ity

, so

cia

l a

nd

pe

rso

na

l se

rvic

es

Ge

ne

ral

go

ve

rnm

en

t







From Table 16 the following are deduced: uPhongolo LM is a large contributor to the construction sector when compared to the greater Zululand district municipality, it however also contributes significantly to agriculture, manufacturing, electricity, and community services. Jozini LM is mostly contributing to transport services. The Big Five False Bay LM contributes mostly to the utilities industry, but also has a large contribution to agriculture and trade. Mtubatuba LM contributes largely to governmental services, followed by manufacturing and agriculture. Mbonambi LM contributes mostly to the primary sector, and uMhlathuze to utilities, mining, manufacturing, and government services.

5 July 2013 Page 26

4 Land Use The Province is characterised by a large number of scattered rural settlements and villages, with a vast number of these settlements and villages occurring within the affected District Municipalities of Zululand, uMkhanyakude and uThungulu.

The presence of villages, informal settlements, and formal urban areas increase towards the coastline with the most significant urban conurbation located within the eThekweni Metropolitan Municpality. Although the majority of urban areas are predominantly located in a southerly location along the coastline and towards the inland, an extensive urban area is however found towards the north at Richards Bay within the uMhlathuze Local Municpality. Richards Bay represents one of the largest secondary activity nodes in the Province.

Richards Bay Port and the Port of Durban together handle approximately 78% of South Africa’s cargo tonnage. Richards Bay is also the operational centre for South Africa’s aluminium industry while Richards Bay Coal terminal ensures the country’s position as the second largest exporter of steam coal in the world.

Map 4 indicates the land cover of the areas in KwaZulu Natal that will be directly affected by the proposed rail alignment.

Map 4: Land Cover

The following high-level observations can be made from the image:

• The start of the section at Jozini dam; • Primarily forest, woodland and plantations; • The only formal urban/built up areas are at the start and the end at Richards Bay.

The following sections will provide a more detailed description of the land cover of the affected areas.

5 July 2013 Page 27

4.1 Zululand District Municipality The Zululand District Municipality is situated in the north-eastern part of KwaZulu Natal and has an area of 15,307 km2. The district’s economic and settlement pattern are largely rural, primarily due to the fact that it was previously a “homeland”, and subsequently severely deprived from of government investment in infrastructure and services for many years. Zululand remains one of South Africa’s poorest districts, and needs investment into basic infrastructure and economic activities. This region has been selected as one of the focus areas for national government’s integrated sustainable rural development strategy (ISRDS) programme, aimed at creating employment.

4.1.1 uPhongolo Local Municipality

The following land uses are significant

• The line traverses through forest, woodlands and plantations. These are predominantly game ranches.

• From a wider perspective, Pongolapoort dam, Phongola Nature Reserve and Pongolapoort Nature Reserve are situated to the east of the existing railway line (Zululand District Municipality, 2011).

4.1.1.1 Protected and Sensitive Areas

Protected and sensitive areas should at all times be considered in order to safe guard the well- being of the natural environment against the adverse impacts of physical development. Ithala Game Reserve is located North of Louwsberg and is 26328 Ha in extent. Pongolapoort Biosphere Reserve and Phongola Nature Reserve are located on the north eastern corner of uPhongolo local municipality and just south of Pongola.

4.1.1.2 Agriculture

Small pockets of high agricultural potential land are located on the west of uPhongolo local municipality next to Ithala game reserve. Agricultural produce opportunities of sugar cane, seasonal vegetables and sub-tropical fruits have been sited along the valley planes of Pongola. Agriculture outside of the afore-mentioned areas is only then limited to stock and game farming. (Zululand District Municipality, 2011).

4.1.1.3 Mining

While it is generally discussed that there is opportunities for small scale coal mining in the entire Zululand district, more efforts should be made to present the opportunity areas spatially.

4.1.1.4 Tourism

The sector in the entire district is unable to attract tourists because it falls short of packaging its natural assets in attractive fashion. This shortcoming is set to be addressed through tourism projects like the Pongolapoort dam proposals.

4.2 uMkhanyakude District Municipality uMkhanyakude District Municipality is bound to the east by Swaziland; the north by Mozambique; the east by St Lucia Wetland Park which runs along the Indian Ocean and the south by uThungulu district municipality. It is 12,819 km2 in extent. The most extensive land uses within the district are the vacant/unspecified/grazing areas with on medium to high potential agricultural potential. The area also has a sufficient amount of protected areas. Of note is the St Lucia wetland park which runs thin and long along the Indian Ocean. Low density dispersed settlements have mushroomed along the district. This situation necessitates a need for a more strategic intervention in order to avoid encroachment on protected areas (Umkhanyakude Local Municiapality).

5 July 2013 Page 28

4.2.1 Jozini Local Municipality

The following land uses are significant:

• There are many areas of conservation and environmental interest within the Jozini area, namely the Ndumu game reserve and the Pongola floodplain;

• The structuring elements of the area include, the Lebombo Mountain Range, Jozini Dam, the Ingwavuma, Pongolo and Mkuze Rivers as well as the two hospitals within the area, i.e. Ubombo and Ingwavuma. These elements present both opportunities and obstacles to the development of the municipality in terms of tourism attractions and the provision of infrastructure and services;

• The inherent potential of the municipality includes areas of high agricultural potential and a number of tourism and historical sites, such as, the Makhatini Flats, Mkuze Farms, Dingaan’s Grave, Border Cave and Usuthu Gorge;

• Jozini’s location provides for a number of transfrontier opportunities, as mooted in the Lebombo SID, along the international borders of Swaziland and Mozambique, including the Cecil Mack Pass etc;

• There are a number of urban areas (nodes) as well as a population settlement pattern; and some areas within the Jozini municipality have limited potential, both in terms of access to tourism and conservation areas and good soils. In such areas, survival strategies, including improved methods of subsistence agriculture should be pursued.

4.2.1.1 Agriculture

There is aquaculture production by Jozini dam and parts of the Pangola River. Fish farming is crucial both as a tourist activity and to the livelihood of the local inhabitants in the local municipality. Sugarcane is the most dominant formal crop. Care should however be taken to ensure that sugarcane crop production practices do not negatively impact on the environment. Pressures on land have been exacerbated by afforestation, overgrazing and bad agricultural practices. This has led to soil degradation.

4.2.1.2 Protected Areas

Many of the major rivers within the Jozini local municipality have a high conservation status. They have therefore been able to preserve their ecological integrity and functionality. The Pongola River is one such example which has managed to generally retain good water quality.

4.2.1.3 Tourism

There local municipality has a high tourism attraction capacity. It has developed tourism features and infrastructure. Eco-tourism generates a large revenue stream for the locality which it then used for conservation initiatives. Prominent tourism activities include tiger fishing at Pongolapoort River.

4.2.2 The Big 5 False Bay Local Municipality


• There is thicket and bushland of which small pockets of it is commercial agriculture.

• From a wider perspective, large water bodies which stretch eastward towards the Indian Ocean are protected areas. They form part of the St Lucia wetland park. These do not directly impact on the railway line as they are further in proximity but are worth noting for future expansion purposes.

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4.2.2.1 Tourism

Tourism activities such as hunting, game farming and fishing are some of the more common attractions. Ecotourism is also a vital part of the Big 5 local municipality. As the name suggests, the Big Five (Lion, Elephant, Leopard, Cape buffalo and the Rhino) are found in game reserves within the area such as Hluhluwe game reserve and the Mfolozi game reserve. The Greater St Lucia wetland park also serves as a major attraction of regional significance (uMkhakude District Municipality, 2012).

4.2.3 Mtubatuba Local Municipality


• The line traverses through forest, woodlands and plantations. These are predominantly game ranches.

• From a wider perspective, there is a significantly wide traditional residential component on the cultivated land which is directly west of the railway line (uMkhakude District Municipality, 2012). Wetlands which form part of the St Lucia wetland park are also prevalent on the eastern side of the local municipality.

4.2.3.1 Agriculture

Mtubatuba local municipality has the greatest percentage of high agricultural potential. It is a 20.28% portion of the entire uMkhanyakude district municipality. The main agricultural produce is sugar cane and timber.

4.2.3.2 Tourism

The Mtubatuba local municipality has a good tourism attraction capacity. This is largely due to the unique natural features of the area. Tourism has thrived so well that secondary supporting sectors like commercial exploits and hospitality industries have emerged in the area.


Much of the eastern coastline (iSimangaliso/St Lucia wetland park) is a protected area. It was officially declared a natural heritage site. St Lucia lake is the largest estuarine in Southern Africa. The cleanliness of the watercourse is crucial for the survival of existing marine life.

4.3 uThungulu District Municipality The uThungulu District Municipality is situated in the North eastern part of the Kwa-zulu Natal. It is bound to the North by uMkhanyakude District Municipality, to the East by the Indian Ocean and UMzinyathi and Ilembe to the west and south respectively. The major primary urban centres are Richards bay, a harbour and an industrial town and Empangeni, an industrial and urban and rural service node.

4.3.1 Mfolozi Local Municipality


• The line traverses through forest, woodlands and plantations. These are predominantly game ranches. The area is characterised by high agricultural potential (Uthungulu District Municipality, 2012).

• From a wider perspective, there is a traditional residential component on the cultivated land to the west of the line.

4.3.1.1 Agriculture

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Mfolozi local municipality has the most concentrated agricultural activities within the entire uThungulu District Municipality. There is both commercial and traditional agriculture. The former is primarily made up of sugar cane and forestry while traditional agriculture is mainly for subsistence purposes (Uthungulu District Municipality, 2012).

4.3.1.2 Tourism

The development of the N2 gateway cultural village and the development of the Mbonambi Craft Emporium are set to be major anchoring tourism projects in the municipality.

4.3.2 Mhlathuze Local Municipality

• The line traverses through a combination of forests woodlands and plantations; cultivated areas; water bodies and urban built up regions. The latter is characterised by formal settlements in Richards Bay.

4.3.2.1 Agriculture

Sugar cane, citrus and cotton are the major crops in the area. They are irrigated by the uMhlathuze river which gets regulated supply from the Phobane dam.

4.3.2.2 Mining

There is heavy mineral mining in Richardsbay and in Empangeni. These intense activities are also supported by regulated water supply from the Phobane dam. The Richards bay coal terminal is located on the harbour along the Indian Ocean. It has quite an extensive storage capacity and currently serves the local coal mining plants within the local municipality. It is the largest coal export facility in the world.

4.3.2.3 Forestry

The region as whole is characterized by a land cover of forestry and plantations. Large scale forest projects include the Ongoye forest nature reserve which sits to the north west of the Richards bay town.


Enseleni nature reserve is 293 ha in extent and lies along the N2, North of the Richard bay town. It houses various plant species, bird species and wild life species. Richards bay game reserve represents another large protected area within the uMhlathuze local municipality. It is located along harbour arterial and currently has over 300 species of birds and a vast array of wildlife.

5 Identified Risks and Benefits Any development in the study area poses a threat to the existing natural environment. Considerable care should be taken to ensure that the environment is not adversely affected.

From a design point of view, increased frequency of travel and volume would take strain on the condition of the existing railway line infrastructure. Design standards would therefore have to be reviewed in order to meet the envisaged demand. The Pongola railway bridge is the longest railway bridge with which the train has to travel across water. Possibility of reinforcements to the bridge should be studied in further detail if the need should arise. Design elements need also take cognisance of flood potential of rivers where the rail traverses. Similar smaller scale examples also include the railway bridges north of Leeupoor station and Candove station to the south.

Illegal vehicle and pedestrian movement across the line pose a safety risk. This is a result of inter-settlement movements and movements towards better economic opportunities across the line. An example of this is cited in settlements like Shikishela and Mfekayi in the Mtubatuba local municipality

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where there is evidence of illegal movement towards the St Lucia Park where there are better employment opportunities in its vast amenities pool.

The railway line passes directly through concentrated small towns like Mkhuze in Jozini local municipality. This essentially poses a noise and air pollution risk for the inhabitants. Other examples are in the towns of Mtubatuba and obviously more denser settlements of Richards’s bay.

The railway generally cuts across agricultural farms and the relationship of the increased pollution and agricultural produce should be explored further.

There is a high prevalence of protected and sensitive areas within close proximity to the line and its reserve across the study area. Considerable efforts need to be taken to safeguard protection of such areas. These areas have proven pivotal for the growth of the local economies.

Figure 21: Illegal vehicle and pedestrian movement

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6 Works Cited uMkhakude District Municipality. (2012). Environmental Management Framework.

Umkhanyakude Local Municiapality. (n.d.). Umkhanyakude Spatial Development Framework.

Uthungulu District Municipality. (2012). Uthungulu District Municipality IDP.

uThungulu District Municipality. (2012). uThungulu District IDP .

Zululand District Municipality. (2011). Zululand District Municipality IDP.

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