ADDRESSING RURAL DEVELOPMENT THROUGH FUNCTIONAL REGIONS
Districts of Dr Ruth Segomotsi Mompati, Ngaka Modiri Molema and John Taolo Gaetsewe
October 2013
Prepared For:
Department of Rural Development and Land Reform Rural Infrastructure Development Clinton Heimann [email protected]
Prepared By:
CSIR, Built Environment Elsona van Huyssteen Johan Maritz
Table of Contents
1. Purpose ...... B1 2. Orientation and key facts ...... B3 3. Which are the areas in the priority rural districts that are under immense developmental pressure due to large numbers of population or a growing population? ...... B9 3.1 Population size and density ...... B10 3.2 Population – Growing or declining ...... B12 3.3 Migration impacts on the area ...... B20 3.4 Surrounding area and/or settlement under pressure of settlement growth or change ...... B20 4. Where are the places in the priority rural districts that are under immense pressure due to high levels of service backlogs and social vulnerability (including low income, high dependency and low employment ratios)? ...... B23 4.1 Household Income and unemployment ...... B24 4.2 Social Vulnerability ...... B26 4.3 Number of service backlogs ...... B29 5. Where are the economic development strengths, sectors and areas in the priority rural districts? ...... B39 5.1 High levels of economic activity or growth ...... B40 5.2 Economic analysis by main economic sectors – employment perspective ...... B43 5.3 Areas with good market accessibility and high ‘demand’ potential ...... B59 6. Where are the prime rural zones/areas that should be prioritised for consolidation and the protection of prime rural production areas/zones? ...... B62 6.1 Agricultural production and agro-processing potential ...... B64 6.2 Other resource areas ...... B67 7. Within high density rural areas or outstretched regions, which anchor points, can play a key role as government service nodes and market concentration areas for government and economic services, both at local level and regional level? ...... B73 7.1 Identification of Regional Centres of Excellence ...... B73
Bi 7.2 Identification of Potential Rural Nodes ...... B83 8. Summary of Key Interventions ...... B87
List of Tables
Table 2.1: Population and economic score card ...... B8 Table 4.1: District and local municipal population and socio-economic trends and service level backlogs ...... B30 Table 4.2: Settlement/towns specific population and socio-economic trends and service level backlogs ...... B34 Table 5.1: Comparative economic activity per local municipality – employment focus ...... B47 Table 7.1: CLUSTER 1: Summary of population in Regional Service Centres and Towns ...... B78 Table 8.1: Summary of investment priorities ...... B87 Table 8.2: Basic Services – Summary of investment priorities ...... B88 Table 8.3: Rural Production Zones – Summary of investment priorities ...... B90 Table 8.4: Key Service Nodes – Summary of investment priorities ...... B93 Table 8.5: Rural regional centres of excellence - Summary of investment priorities ...... B95
List of Figures
Figure 1.1: Priority districts – Group 1 ...... B1 Figure 2.1: Orientation map showing key towns and natural area – Group 1 ...... B5 Figure 2.2: SA Functional settlement areas and service regions ...... B6 Figure 3.1: Regional overview of population and low income earning households distribution ...... B11 Figure 3.2: Population growth depicted in functional settlement areas and service regions 1996-2011 ...... B13 Figure 3.3: MODIS settlement change detection 2001-2005...... B14 Figure 3.4: MODIS settlement change detection 2006-2012...... B15 Figure 3.5: Settlement related MODIS change detection 2001-2012 ...... B16 Figure 3.6: Settlement related change (MODIS change detection 2001-2012) in relation to the traditional authority areas ...... B17
Bii Figure 3.7: Settlement related population change in relation to the traditional authority areas (Population growth and decline mapped per mesozone (50km2) ...... B18 Figure 3.8: Migration trends focusing on 23 districts ...... B21 Figure 3.9: Areas under pressure due to a combination of high densities, growth and in-migration of population ...... B22 Figure 4.1: Household Income Group ...... B24 Figure 4.2: Employment status ...... B25 Figure 4.3: Age distribution ...... B26 Figure 4.4: Percentage population younger than 14 years ...... B27 Figure 4.5: Dependency ratio (non-economically active in relation to economically active population) ...... B28 Figure 4.6: Regional overview of population growth and decline in relation to service point backlogs for basic services ...... B32 Figure 4.7: Regional indication of pockets of high basic service demands, high population densities and growth...... B37 Figure 5.1: Economic strengths and growth (1996-2009) ...... B41 Figure 5.2: National significance in resource based economy ...... B42 Figure 5.3: Economic contribution of the various sectors at LM level (2009) ...... B44 Figure 5.4: Employment for the various sectors at LM level (2009)...... B45 Figure 5.5: Education and skills levels ...... B46 Figure 5.6: Strengths in Wholesale Retail and Trade (SIC 6)...... B49 Figure 5.7: Strengths in Manufacturing (SIC 3) ...... B50 Figure 5.8: Economic Strengths: Electricity, gas and water supply (SIC 4) ...... B51 Figure 5.9: Economic Strengths: Financial Intermediation, insurance, real estate and business services (SIC 8) ...... B52 Figure 5.10: Economic Strengths: Transport, Storage and Communications (SIC 7) ...... B53 Figure 5.11: Economic Strengths: Community, Social, Personal and Government Services (SIC 9 & 10) ...... B55 Figure 5.12: Economic Strengths: Agriculture, Forestry and Fishery (SIC 1) ...... B56 Figure 5.13: Economic Strengths: Mining and Quarrying (SIC 2) ...... B57 Figure 5.14: Economic vulnerabilities/hot spot areas ...... B58 Figure 5.15: High population and market concentrations in areas surrounding big towns and service centres ...... B60 Figure 6.1: Agricultural resource potential in sparsely populated areas – North West Northern Cape Cluster ...... B65 Figure 6.2: Rural Production Zones: Agriculture production and areas with highest market potential ...... B66 Figure 6.3: Economic Strengths: Tourism attraction regions ...... B68 Figure 6.4: Rural Production and Demand Zones: Tourism Attraction Points (blue) in relation to levels of accessibility (green high and red remote) ...... 69 Figure 6.5: Rural Production Zones: Mining potential and risks ...... B70 Figure 6.6: Rural Production Zones: Carbon Sequestration Potential ...... B72
Biii Figure 7.1: Network of economic anchor points and settlements ...... B77 Figure 7.2: Functional areas playing a significant economic and service centre role in priority district ...... B81 Figure 7.3: High density settlements beyond 30 km access of significant service centres ...... B82 Figure 7.4: Potential focus for extending rural node role ...... B84 Figure 7.5: Differentiation in existing rural concentration and anchor points ...... B86
Biv PART B
Development Realities and Trends: Northern Cape and North West Priority Districts
1. Purpose
The purpose of this report is to provide an overview of the developmental realities and critical considerations for infrastructure investment in the Northern Cape and North West priority rural districts of Dr Ruth Segomotsi Mompati, Ngaka Modiri Molema and John Taolo Gaetsewe.
Figure 1.1: Priority districts – Group 1
B1 Transforming infrastructure investment is regarded as a potential catalyst, not only in changing the fate of the 23 most distressed districts in the country, but also for rural development in the broader South African context. However, given the high density of some areas and concentrated settlement and the characteristics of these selected areas, innovative practices will need to be pioneered to move towards the Vision 2030 and the interrelated targets of: (i) economic growth and employment creation; (ii) increased quality of life and a higher human development index; and, (iii) a lower dependency on carbon intensive resources, as set out in the National Development Plan (2011).
In this section, an overview is provided of the analyses of development realities, opportunities and trends characterising the Northern Cape and North-West cluster of districts to inform the identification of high impact intervention areas. As set out in Part A, the value of priority investment areas is foreseen firstly in supporting the implementation of existing catalytic projects, secondly, in identifying future catalytic projects, and thirdly, in informing strategic development choices in IDPs, sector plans, as well as in the broader rural development framework.
This overview forms part of a larger study which incorporated a range of spatial and data analyses undertaken for all 23 priority rural districts in South Africa. The study is intended to provide evidence to identify priority investment areas for high impact (catalytic) projects, especially those related to government’s service and infrastructure investment (Action Plan 6, as well as SIP11 and also informing SIP6).
The structure of this Part (B) of the report will be as follows:
Section 1: Purpose and structure of the report Section 2: Background and orientation to the North West-Northern Cape cluster of districts Sections 3-7: Key development and investment realities and trends in the region in relation to key questions: o Section 3: Which of the areas in the priority rural districts are under immense developmental pressure due to large numbers of population and a growing population? o Section 4: Which of the areas in the priority rural districts are under immense pressure due to high levels of service backlogs and social vulnerability (including low income, high dependency and low employment ratios) o Section 5: Where are the economic development strengths, sectors and areas in the priority rural districts? o Section 6: Where are the areas that should be prioritised for consolidation and protection of prime rural production areas/zones? o Section 7: Within high density rural areas or outstretched regions, which are the anchor points that can play a key role as government service nodes and market concentration areas for government and economic services, both at the local and regional levels? Section 8: Summary of key interventions and priority investment areas to guide local, regional, as well as sector specific investment in the area, in support of economic transformation.
B2 An evaluation of the 1st Round of Catalytic Projects (as identified by the respective District Municipalities) in relation to key development realities and proposed investment priorities is set out in Part C. Maps and tables of the key evidence will be provided to assist districts in answering these key questions.
2. Orientation and key facts
The districts that form part of the priority district analyses in this cluster are: John Taolo Gaetsewe in Northern Cape, and Ngaka Modiri Molema, and Dr Ruth Segomotsi Mompati in North West Province.
The following map (Figure 2.1) provides an orientation of the Eastern Cape cluster of distressed districts by mapping the local municipalities, major land uses such as settlements, traditional authority areas, mountainous areas, national parks and agricultural land capability. These characteristics will all be discussed in greater detail below.
In order to establish a more nuanced understanding of settlement dynamics in the Priority districts, an update and analyses of the South African Functional Settlement Area typology was undertaken. Figure 2.2 provides the settlement typology for the cluster of districts. This typology is based on population density, employment, urban functional index and economic activity.
A city is a place that together with its functionally linked urban areas is home to a population of more than 400 000 people; it has significant multi-nodal economies; plays a significant role in the region in terms of service delivery and the economy; plays a major role in government and commercial service delivery; has a relatively high economic growth rate; and attracts people. A regional centre is a medium and high order town that plays a prominent role in offering services to the hinterland. These towns typically have large populations in densely settled areas, or are towns in resource-rich areas that are relatively accessible, or are smaller towns playing a key service function in a more isolated and less accessible area. Service centres are smaller towns that seem to fulfil a particular service role within the local area. These centres may have a small service index but serve a large population, or serve a small population in a sparsely populated or isolated area. Local and niche towns are small towns that fulfil a local function or fulfil a particular niche function. Such towns have a smaller population and economic activity and are geographically more evenly distributed throughout the country than settlements in other categories. High density rural areas are densely populated but play a very limited service role and are often under traditional land ownership1.
1 Van Huyssteen, E.; Biermann, S.; Naudé, A. & Le Roux, A. (2009). Advances in spatial analysis to support a more nuanced reading of the South African space economy, in Urban Forum, Vol. 20, pp195–214. B3 Figure 2.2 highlights that in this region Mahikeng/Mmabatho and Lichtenburg are the only RSCs and they play a key role in providing access to government and economic services to the surrounding areas. Given the sparsely populated nature of the region, the rest of the population is largely concentrated within several medium sized Service Towns, Local / Niche Towns and some Dense Rural areas.
To some extent the eastern parts of North West fall under the influence of the Gauteng City Region while Kimberley is a key focus area for higher order services for the Northern Cape and the most north-westerly areas of North West Province. The area is sparsely populated with densities ranging from 8 persons per km2 to 30 persons per km2. The Ngaka Modiri Molema District is the most populous and has the highest density. The area faces huge developmental challenges. More than 70% of the population live in settlements in most of the local municipalities, whilst other areas such as Joe Morolong, Kagisano/Molopo and Tswaing are amongst the most sparsely settled of the priority rural districts.
As indicated in Table 2.1, more than 60% of the population are living within, or within very close proximity to settlements, in 11 of the 13 local municipalities. Of these, the following municipalities have been calculated to have more than 70% of their population in or within close proximity to settlements – i.e. Lekwa-Teemane, Mamusa, Naledi, Ga-Segonyana, Gamagara, Ditsobotla, Mahikeng and Ratlou.
B4
Figure 2.1: Orientation map showing key towns and natural area – Group 1
B5
Figure 2.2: SA Functional settlement areas and service regions
B6 The table on the following page (Table 2.1) provides a snapshot scorecard of development in the three districts and the respective local municipalities with regards to population size, predominant settlement type, population growth rate and the contribution of each local municipality and respective district to the national economy, in terms of Gross Value Added (GVA). The table also highlights the 3 top sectors with respect to both GVA and employment provision.
In most of the districts, the Government Service and Community Sector is the largest contributor in terms of economic activity, as well as in terms of employment. Only in the John Taolo Gaetsewe District Municipality (DM) does Mining overtake this sector in terms of GVA but not in terms of employment. Specifically in the least populous but highly centralised region of the Gamagara Local Municipality (LM), Mining plays a significant role in terms of economic activity and job creation. This activity is concentrated around the Kathu service town along with its Sishen iron ore mine. In this region, the Transport, Storage and Communication sector also plays a large role and this is most likely to be related to the export of the ore. Agriculture plays a role in some LMs in the Dr Ruth Segomotsi Mompati District, where it is the second highest employment sector as well as in the LMs of Ratlou and Tswaing. The Retail and Wholesale Trade sector also plays a significant role in some LMs. It is important to note that only in Lekwa-Teemane does Manufacturing score as the 3rd highest employer thus indicating that beneficiation of primary products is not occurring in any significant way.
B7 Table 2.1: Population and economic score card
MUNICIPALITIES: POPULATION SETTLEMENT TYPE POPULATION ECONOMIC ACTIVITY GVA CONTRIBUTION TO GVA BY CONTRIBUTION TO DISTRICT & LOCAL % of population in Non-settlement areas ANNUAL GROWTH (% of national) ECONOMIC SECTOR EMPLOYMENT BY / Settlements ** RATE (%) ECONOMIC SECTOR No. of % of [highlighted: non-settlement ≥ 40%] [highlighted: growth [highlighted: GVA % of 3 highest economic sectors 3 highest economic people national ĦĦ Where more than 80% in settlements rate ≥ national rate national ≥ population % of in descending order sectors in descending (2011) population of 1.86%] national] order Dr Ruth Segomotsi 463 788 0.90 34/66 0.78 0.35 Mompati DM Greater Taung 177 628 0.34 37/63 -0.15 0.10 Kagisano/Molopo 105 782 0.20 51/49 0.45 0.06 8/92 Lekwa-Teemane 53 244 0.10 ĦĦ 2.97 0.05 Mamusa 60 352 0.12 26/74 2.63 0.05 Naledi 66 782 0.13 26/74 1.57 0.09 47/53 John Taolo Gaetsewe DM 224 813 0.43 1.01 0.48 Gamagara 41 622 0.08 ĦĦ 9/91 6.05 0.28 18/82 Ga-Segonyana 93 650 0.18 ĦĦ 3.17 0.14 96/4 Joe Morolong 89 541 0.17 -1.25 0.06 Ngaka Modiri Molema DM 842 704 1.63 29/71 1.43 1.03 Ditsobotla 168 904 0.33 29/71 1.97 0.27 Mahikeng 291 539 0.56 22/78 1.30 0.51 Ramotshere Moiloa 150 701 0.29 35/65 0.12 1.16 Ratlou 107 339 0.21 24/76 0.60 0.04 Tswaing 124 221 0.24 45/55 2.30 0.09 ** “Non-settlement” = areas largely characterised by dense rural and sparse rural settlement (average < 100 people/km², excluding areas with average 10 people/km² with economic activity in services sector) “Settlement” = areas largely characterised by dense settlements, towns & cities (average >100 people/km² OR 10 people/km² with economic activity in services sector) Definition as used in SACN/Presidency/dplg/CSIR Functional Settlement Typology (2008) Source: Functional Settlement Profile, 2013 CSIR/DRDLR Update (CSIR, Geospatial Analyses Platform, 2013)
LEGEND: Key for Economic Sectors
SIC 1: Agriculture, forestry & fishing SIC 4: Electricity, gas & water supply SIC 7: Transport, storage & communication
SIC 8: Financial intermediation, insurance, SIC 2: Mining & quarrying SIC 6: Wholesale & retail trade; Repair of motor real estate & business services vehicles, motor cycles and personal & household SIC 9 & 10: Community social & personal SIC 3: Manufacturing goods; Hotels & restaurants services, as well as government services
B8 3. Which are the areas in the priority rural districts that are under immense developmental pressure due to large numbers of population or a growing population?
In isolated areas with high demand and backlogs for basic services, high population densities, high levels of social vulnerability and a limited range of short term investment options such as is evident in most of these 23 priority districts, investment in basic services provide a major opportunity for creating a value chain of capital and maintenance employment opportunities. The opportunity also exists to try and apply alternative technologies linked to the green economy and possible linked industries, as well as skills development. This is especially the case in growing settlements where investment in basic services will continue to take place in future. The key is thus in identifying those areas where government has to invest in basic services – but where investment can be transformed to also be catalytic in terms of economic development. The following has been considered.
QUESTION 1: Identify high density settlements with large and growing populations
1. Population Size & Density
2. Growing Population
3. In-migration to the area
4. Surrounding area and/or settlement under pressure of settlement growth or change
B9 3.1 Population size and density
The population in these districts is relatively small. The share of the national population for each of the districts is 1.63 %, 0.43% and 0.9% respectively for Ngaka Modiri Molema, John Taolo Gaetsewe and Dr Ruth Segomotsi Mompati Districts. Figure 3.1 shows the population density in shades of yellow to brown - the latter being the densest. The areas shaded grey have less than 100 persons per mesozone (i.e. less than 100 persons per 50 km2). The map clearly illustrates both the general low density and the concentration within selected settlements. The largest population is in Mmabatho and in the vicinity of Kuruman and Lichtenburg.
In terms of population dynamics, the Northern Cape and North West Districts (Cluster 1) have relatively small population sizes, lower densities and lower levels of population growth than the other districts but have challenges in addressing basic service backlogs largely due to distances and the sustainability of water resources. In such areas, backlogs in service access are expected to be addressed within the next five years.
In meeting the needs of the population it is essential to also consider the socio-economic status of the population. A dot density map of the households earning less than R 38 000 per year has been overlaid on the total population density (see black dots on the map). A similar concentrated trend is evident especially in the Taung, Kuruman, Madibogo and Mmabatho areas. The households earning less than R 38 000 per annum make up communities which are unlikely to be able to financially contribute significantly towards health, education or basic service delivery and thus require specific attention.
B10
Figure 3.1: Regional overview of population and low income earning households distribution
B11 3.2 Population – Growing or declining
The previous map (Figure 3.1) shows the distribution and density of the population. From this it is evident that the biggest part of the District is quite sparsely populated. The highest population pressure is centred on the towns and settlements. Given that government needs to plan to meet the demand for investment, job creation and services delivery in these areas, it is essential as a first step to take cognisance of the growth or decline of population in any of the areas and specifically the rate of growth of settlements which has an impact on the demand, effectiveness and financial viability of infrastructure implementation. The latter either due to a rapid rate of delivery being required which has specific cash flow implications or through redundant investment due to a declining population. A time series analysis conducted by the CSIR (utilising an innovative Temporal Analyses Tool to compare the StatsSA data of 1996 with that of 2001 and 2011 for the recently updated settlement typology) enabled an analysis of growth and decline per area and settlement across the region. Figure 3.2 provides an indication of this population change at a national scale. In this cluster of districts we clearly see areas of both decline and growth. Decline is evident mainly in the more isolated areas away from main roads and towns. With the mainly sparsely populated areas, growth has mostly been below the national average. However, 22 towns/areas in the region have grown by more than 4%, with Mmabatho (Mahikeng) being the one with the largest growth. The main centres of growth are Mmabatho (Mahikeng), Kuruman, Vryburg, Lichtenburg, Schweizer-Reneke, Itsoseng and Taung. From this analysis of urban growth, it is also clearly evident that the Taung, Kathu and Kuruman areas have grown significantly, with growth rates higher than most other towns even in comparison with other service centre towns across the country (Figure 3.2).
With regards to the settlement related changes in this time period, the growth evident from the StatsSA 1996-2011 data analyses is confirmed through an indication of concentrated change as picked up though change detection analyses undertaken across the region through a remote sensing process using MODIS imagery. This process assists in identifying the highest intensity of settlement related change that took place over a certain time period, with most changes seeming to relate to an increase in density or extension of the existing built up areas (even though change can also be due to the demolition of structures or in some cases land degradation in close proximity to settlements). MODIS imagery identified settlement changes that took place across the region and specifically more accurately identified the spatial locus of the change. The intensity in the Taung/Hartswater area is evident in Figure 3.3 which picked up increased change in the period between 2001 and 2005. For the period 2006 to 2012 (Figure 3.4), the change seem more concentrated in the Atamelang and Mmabatho/Mahikeng areas.
B12
Figure 3.2: Population growth depicted in functional settlement areas and service regions 1996-2011
B13
Figure 3.3: MODIS settlement change detection 2001-2005
NOTE: Maps prepared in early stage of project - Moshaweng now Joe Morolong
B14
Figure 3.4: MODIS settlement change detection 2006-2012
NOTE: Maps prepared in early stage of project - Moshaweng now Joe Morolong.
B15 In the following figures, the intensity of total changes between 2001 and 2012 is depicted. Figure 3.5 shows the change for all areas, whilst in Figure 3.6 changes are highlighted in relation to the traditional authority areas (the areas bordered by the thick pink lines). From these figures, it is evident that the majority of areas of change lie within the traditional authority areas.
Figure 3.5: Settlement related MODIS change detection 2001-2012
NOTE: Maps prepared in early stage of project- Moshaweng now Joe Morolong.
B16
Figure 3.6: Settlement related change (MODIS change detection 2001-2012) in relation to the traditional authority areas
B17 Figure 3.7: Settlement related population change in relation to the traditional authority areas (Population growth and decline mapped per mesozone (50km2) B18 Making use of the identified areas of change from the MODIS imagery and the StatsSA data, the level of population changes was mapped per small area (mesozone within the CSIR Geo Spatial Analyses Platform – GAP). The settlement related change in population numbers is clearly visible in Figure 3.7. It is noted that except for growth in large towns, all other growth is within areas under the management of traditional authorities. Within these areas, even though settlement change is noted, population data also points to several areas of decline. Such decline is also noted between Mmabatho/Mahikeng and Madibogo. (See Figures 3.3-3.7)
A detailed analysis of growth rates and service backlogs per town is set out in Section 4.3, providing a clear indication of how these growth trends also influence service point backlogs and the need for government investment in the region.
IMPLICATIONS:
A regional concentration trend is clearly evident in the Northern-Cape and North West priority districts. The towns of Kathu, Kuruman, Taung and the Mmabatho/Mafikeng Regional Centre are playing a key role in this region. Together with high density settlements north of Ganyesa, to the east of Kuruman and in the Atamelang town and Atamelang area, these areas seem to be under the biggest pressure for service delivery and continued growth. The role of these towns and settlements is thus critical in addressing the needs of the people in this region. These areas of population concentration provide critical service anchor points and developmental focus areas in this sparsely populated rural region. The towns and dense settlements also create effective intervention opportunities to address basic service backlogs by a transformative approach. Population densities, poverty levels and settlement change detection also points to the importance of land management and governance within traditional authority areas.
B19 3.3 Migration impacts on the area
At a national scale it is clear that there is migration out of rural districts. Figure 3.8 illustrates the net migration occurring within the 23 priority districts. Some districts show strong net out-migration, for example Amatole, Vhembe, Mopani and Ngaka Modiri-Molema. It is also noticeable that internal migration (within districts) is occurring especially to sites where there is growth, for example the mining areas around Burgersfort and Steelpoort in the Sekhukhune District. Key settlements/towns such as Kuruman and Richards Bay are showing net positive migration which confirms a trend of people moving from rural, more isolated regions to towns where services and facilities can be better accessed. It is also noticeable that there is a strong trend to migrate from the Ngaka Modiri Molema DM area to the Gauteng City Region.
3.4 Surrounding area and/or settlement under pressure of settlement growth or change
In spite of out-migration and slow growth or even decline, the natural population and settlement growth is still significant resulting in continued demand for access to basic services and rising pressures on municipalities to address backlogs and provide (and maintain) services in a sustainable way. The following map shows areas where the greatest population pressures occur. In numeric terms, Ngaka Modiri Molema DM is experiencing the highest pressures. Please refer back to the earlier figure (Figure 3.7) if only population numbers or growth rather than pressure are being considered.
B20
Figure 3.8: Migration trends focusing on 23 districts
B21
Figure 3.9: Areas under pressure due to a combination of high densities, growth and in-migration of population
B22 4. Where are the places in the priority rural districts that are under immense pressure due to high levels of service backlogs and social vulnerability (including low income, high dependency and low employment ratios)?
Access to the basic services of water, electricity and sanitation is enshrined in the Constitution. Many people, especially the rural poor, 21 years after democracy, still do not have reliable access to these services and most cannot afford to pay for them. Thus, in identifying areas where there is a high demand on government to provide services, it is critical to understand the level of affordability of such services. The starting point is thus to review the level of income and unemployment within the regions as follows.
Question 2: Identify areas characterised by high levels of household service demand, unemployment and vulnerability
1. Low levels of household income and high unemployment rates
2. Social vulnerability
3. Number of service backlogs (household level)
B23 4.1 Household Income and unemployment
As can be seen from the following graph (Figure 4.1), over 15 % of households in all 3 districts have no income, and a further 10 to 12% earn less than R 800 per month, with the majority in the R 801 to R 3 180 income brackets. This limits the ability of households to pay for education, health or services. John Taolo Gaetsewe has the greatest percentage of households with a monthly income of more than R3 180. It is also the district with the highest employment, with the majority of these jobs most probably dependent on the mines and government posts (see Section 5, Figure 5.4). Dr Ruth Segomotsi Mompati is the most populous district but also has the largest number of households in low income brackets and the lowest employment rate.
Household Income Groups Percentages
John Taolo Gaetsewe
No income
less R800 pm Ngaka Modiri Molema
Group 1 Group R801- R3180pm
R 3181- R12816pm Dr Ruth Segomotsi Mompati R12 816- 51 166
more than R 51 166pm 0% 10% 20% 30% 40% 50% 60% 70% 80% 90%100%
Figure 4.1: Household Income Group
B24 Employment Status Employed
John Taolo Gaetsewe Unemployed
Ngaka Modiri Molema Discouraged work-
Group1 seeker
Other not Dr Ruth Segomotsi Mompati economically active
Not applicable 0% 20% 40% 60% 80% 100%
Figure 4.2: Employment status
B25 4.2 Social Vulnerability
Within the more rural districts, one of the most outstanding features is the large percentage of youth, see Figures 4.3 and 4.4. In terms of absolute numbers this has a major impact in the Ngaka Modiri Molema area, with almost 600 000 of a population of just over 800 000 being under 34 years of age.
Whilst the population numbers are significantly smaller in the Dr Ruth Segomotsi Mompati District, a staggering 35% of the population are under the age of 14 years. This also has tremendous implications for education and health services in future.
Age distribution
John Taolo Gaetsewe
0-14 15-34
Ngaka Modiri Molema 35 - 65 Group 1 Group 66 - 120 Age Groups
Dr Ruth Segomotsi Mompati
0 200000 400000 600000 800000 1000000
Figure 4.3: Age distribution
B26 The large number of youth and the high unemployment rate result in a very high rate of dependency on those that are working. At a national scale there is a 60 % dependency rate. This is much higher in this cluster and the dependency burden (the number of those not economically active in relation to the working population) is bordering on 70% in the Dr Ruth Segomotsi Mompati District (see Figure 4.5)
Percentage of population younger than 14 years
John Taolo Gaetsewe
Ngaka Modiri Molema Group1
Dr Ruth Segomotsi Mompati
32 32.5 33 33.5 34 34.5 35 35.5
Figure 4.4: Percentage population younger than 14 years
B27 Dependency Ratio
John Taolo Gaetsewe
Ngaka Modiri Molema Group1
DependencyRatio
Dr Ruth Segomotsi Mompati
National Non-Metro Average
54 56 58 60 62 64 66 68 70 72
Figure 4.5: Dependency ratio (non-economically active in relation to economically active population)
B28 4.3 Number of service backlogs
In order to identify investment priority areas, an extensive analysis was undertaken of service point backlogs across the region, with a specific focus on water, sanitation and electricity. The following tables show the ratio of people living in non-settlements versus settlements, the population growth rate, population below 14 years, dependency ratio, income levels and a measure of the level of water, sanitation and energy service levels. As in most of the 23 priority districts, there is evidence of concentrations of population and poverty which places a huge burden on development, service delivery and job creation within the towns and smaller settlements. Water availability remains a challenge in this sparsely populated and mainly arid area. The western regions which are the most arid are also the most sparsely populated and here the challenges for providing services effectively and viably will be even greater. The number of service backlog points has been calculated per household.
Table 4.1 presents an overview of the key service related statistics at an LM and DM level. Following on this, Table 4.2 provides a more detailed breakdown of the service backlogs at a settlement level. That is a breakdown of the backlog in services as well as information on the population size and growth status is presented for every town, settlement or rural area of a district.
Given the fact that these are rural areas, the analysis provides evidence of relatively high population concentrations with substantial population living in the Regional Service Centres, Service Towns and Local/ Niche Towns and the Dense Rural settlements. Only in three districts does the non-settlement population exceed 40%, with Joe Morolong being the most dispersed and sparsely populated. Three LMs namely Leka- Teemane, Gamagara and Ga-Segonyana have over 80% of their population in settlements (mostly mining towns). Given that these are rural areas, the highly centralised nature of the settlement population is advantageous from a service provision perspective. It is more cost effective to provide basic water, sanitation and electricity as well as other social services to populations which are clustered rather than dispersed. It reduces the lengths of distribution piping, and the provision of education and health services is also more efficient when economies of scale are possible. Despite this, there are still many people who remain far from areas where they can cost effectively be provided with conventional reticulated services and/or provided with full time higher order social facility services. With respect to water, sanitation and electricity services, the opportunity to explore the application of alternative and more “Green” service provision is presented, while in the case of social services there will need to be a high reliance on periodic services, such as e-government or agency type services.
Table 4.1 indicates the backlog of all the 3 basic services and shows in the form of ratios what the level and extent of service provision is each of the LMs. The table also presents a breakdown of the income categories per LM. Joe Morolong is the area with the highest percentage of low income people; it also has the most distributed population. This extensive arid area, although not having the smallest population with respect to size is home to less than 90 000 people of which 82 % of the households have an annual income of less than R 38 000. Although the majority of households seem to have access to electricity, they do not generally have access to water within 200 meters of their dwelling and depend largely on pit latrines for sanitation.
B29 Table 4.1: District and local municipal population and socio-economic trends and service level backlogs
MUNICIPALITIES: POPULATION SETTLEMENT POPULATION POPULATION DEPENDENCY WATER SERVICE SANITATION ENERGY SERVICE INCOME LEVELS (% DISTRICT & (% of ANNUAL BELOW 14 RATIO INDEX (% of SERVICE INDEX INDEX households annual LOCAL population in GROWTH YEARS (%) households) (% of house- (% households) income) **Non- RATE (%) holds) settlements/ Settlements) No. of % of [highlighted: [highlighted: [highlighted: No. of Piped in dwelling or Flush/ Pit Electricity/ No (R0-R38 200/ people national non- growth rate ≥ >35%] unemployed within 200 metres/ latrine/ Other electricity R38 201-R307 600/ (2011) population settlement national rate dependent on Piped not within 200 [highlighted: [highlighted: No More than ≥ 40%] of 1.86%] the employed metres/ No piped Other ≥ 20%] electricity ≥ 50%] R307 600) ĦĦ Where > [highlighted: ≥ 7 water [highlighted: No [highlighted: R0- 80% in persons] piped water ≥ 20%] R38 200 ≥ 85%] settlements Dr Ruth Segomotsi 463 788 0.90 34/66 0.78 35 5 48/48/4 36/50/14 81/19 79/19/2 Mompati Greater Taung 177 628 0.34 37/63 -0.15 20/77/3 11/78/11 89/11 84/15/1 Kagisano/Molopo 105 782 0.20 51/49 0.45 35/54/11 16/66/18 74/26 83/16/1 Lekwa-Teemane 53 244 0.10 ĦĦ 8/92 2.97 97/2/1 91/3/6 86/14 70/28/2 Mamusa 60 352 0.12 26/74 2.63 76/20/4 64/20/16 81/19 76/22/2 Naledi 66 782 0.13 26/74 1.57 78/20/2 69/12/19 77/23 67/28/5 John Taolo Gaetsewe 224 813 0.43 47/53 1.01 34 4 41/56/4 31/56/13 87/13 68/28/4
Gamagara 41 622 0.08 ĦĦ 9/91 6.05 96/3/1 88/7/5 88/12 44/44/12 Ga-Segonyana 93 650 0.18 ĦĦ 18/82 3.17 40/58/2 27/58/15 91/09 64/32/4 Joe Morolong 89 541 0.17 96/4 -1.25 16/76/8 9/77/14 82/18 82/16/2 Ngaka Modiri 29/71 Molema 842 704 1.63 1.43 33 5 51/35/14 32/57/11 81/19 74/23/3 Ditsobotla 168 904 0.33 29/71 1.97 66/23/11 48/35/17 74/26 72/24/4 Mahikeng 291 539 0.56 22/78 1.30 53/27/20 33/62/5 85/15 68/27/5 Ramotshere 150 701 0.29 35/65 57/35/8 27/66/7 82/18 77/21/2 Moiloa 1.16 Ratlou 107 339 0.21 24/76 0.60 16/72/12 5/80/15 84/16 86/13/1 Tswaing 124 221 0.24 45/55 2.30 49/41/10 38/46/16 74/26 78/19/3 ** “Non-settlement” = areas largely characterised by dense rural and sparse rural settlement (average < 100 people/km², excluding areas with average 10 people/km² with economic activity in services sector) “Settlement” = areas largely characterised by dense settlements, towns & cities (average >100 people/km² OR 10 people/km² with economic activity in services sector) Definition as used in SACN/Presidency/dplg/CSIR Functional Settlement Typology (2008) Source: Functional Settlement Profile, 2013 CSIR/DRDLR Update (CSIR, Geospatial Analyses Platform, 2013)
B30 The service backlogs are shown in detail for each town and settlement type grouped by local municipality areas in Table 4.2 and in Figures 4.6 and 4.7. The service backlogs used are defined and calculated as follows:
Water backlog = no piped water with 200m of dwelling Electricity backlog = no electricity for lighting Sanitation backlog = no access to a flush or pit toilet Total service backlogs = sum of all backlogs (may be 3 per household) Percentage backlog = index of backlog in relation to total households in area.
It is important to consider that the ability of households in these areas to pay for basic services is restricted to a very small portion of the population. Most residents have a very low income. Low income is defined as households with an income of less than R 38 201 per annum (see Figure 4.1). In most areas, more than 70% of households are in this “low income” category.
In deciding on the rate and type of service delivery, note should be taken of the rate of population growth or decline. Several areas of decline are noted with the most significant being the rural areas of Joe Morolong and Ditsobotla and to a lesser extent the rural areas of Kagisano. Areas of decline relating to towns in the Greater Taung area such as at Manthestad and Pudimoe and Setlagole in Ratlou are evident. Certain areas have grown rapidly and/or increased significantly. Mmabatho has shown the largest increase, followed by Itsoseng, Kuruman, Lichtenberg, Bloemhof, Schweizer-Reneke, Kathu, Vryburg and Coligny. Several smaller places such as Van Zylsrus, Hotazel and Piet Plessis have grown rapidly but from a low base. This is further evidence of the concentration trend noted at a national level. The population for this cluster has not grown significantly overall and the growth and decline trends can be ascribed to internal population shifts. Table 4.2 provides a summary view of population growth and decline in the District, while in Figure 4.6 this data is combined with a data layer showing areas where there is a backlog for basic services. Note the cluster of service backlog points in the vicinity of Kuruman, Pudimoe/Taung, Setlagole/Madibogo, Itsoseng and Mmabatho. Figure 4.7 is a combination map showing pockets where there is high demand for basic services, the highest population densities and areas of growth. These areas should be prioritised for attention with regard to the provision of services, specifically for water and sanitation.
B31
Figure 4.6: Regional overview of population growth and decline in relation to service point backlogs for basic services
B32 Key for Table 4.2: Definitions of symbols and categories of growth
GROWTH CATEGORIES Major Decline (7000)-(25000) Decline (1000)-(7000) Minor Decline (500)-(1000) Stable (500)- 500 Small Increase 500-1000 Increase 1000-8000 High Increase 8000-25000 Significant Increase 25000 plus SYMBOLS Δ Less than 2% growth ΨΨΨ More than 4% growth ΦΦ More than 10000 growth in population
B33 Table 4.2: Settlement/towns specific population and socio-economic trends and service level backlogs
CLUSTER 1: Dr Ruth Segomotsi Mompati POPULATION HOUSEHOLDS SERVICE BACKLOGS INCOME STATUS
1996 2001 2011
TOWN OR SETTLEMENT TOWN OR SETTLEMENT LOCAL MUNICIPALITY TYPE DESCRIPTION
CHANGE 1996 - 2011 GROWTH BELOW BELOW GROWTH 2%NATIONAL LARGE INCREASE RAPID GROWTH GROWTH STATUS GROWTH
NUMBER NUMBER SIZE WATER WATER SANITATION SANITATION ELECT-RICITY TOTAL POINTS TOTAL BACKLOG % POOR HOUSE-HOLDS POOR LESS THAN LESS 70% POOR Greater Taung Dense Rural in LM 35 945 36 200 37 729 1 784 Δ Increase 10 250 3.5 3 431 1 157 1 215 5 803 56.6 9 054 Greater Taung High Density Settlements in LM 51 609 49 775 49 002 (2 607) Δ Decline 13 236 3.8 4 157 1 781 1 585 7 524 56.8 11 764 Greater Taung Local or Niche Town Manthestad 4 998 4 642 2 987 (2 011) Δ Decline 890 5.2 237 74 148 459 51.6 783 Greater Taung Local or Niche Town Pudimoe 15 441 13 294 13 745 (1 696) Δ Decline 3 961 3.4 1 036 455 326 1 816 45.9 2 717 ••• Greater Taung Local or Niche Town Reivilo 3 000 3 684 3 155 155 Δ Stable 804 4.6 60 215 243 518 64.4 598 Greater Taung ServiceTown Hartswater ST 7 649 8 256 7 071 (578) Δ Minor decline 2 102 3.9 774 159 156 1 090 51.8 1 839 Greater Taung ServiceTown Taung ST 34 801 36 487 35 790 989 Δ Small increase 9 836 3.7 2 104 906 832 3 842 39.1 7 605 Greater Taung Sparse Rural in LM 28 165 29 477 28 149 (16) Δ Stable 7 538 3.9 2 063 863 1 066 3 992 53.0 6 510 Kagisano/Molopo High Density Settlements in LM 14 284 16 513 16 644 2 360 Δ Increase 4 188 3.9 957 872 969 2 798 66.8 3 450 Kagisano/Molopo Local or Niche Town Ganyesa 14 540 16 713 19 207 4 667 Increase 5 339 3.1 1 284 611 809 2 704 50.7 4 097 Kagisano/Molopo Local or Niche Town Morokweng 12 230 12 738 14 741 2 511 Δ Increase 4 023 3.2 1 685 508 1 149 3 342 83.1 3 413 Kagisano/Molopo Local or Niche Town Piet Plessis 328 1 067 1 506 1 178 ΨΨΨ Increase 441 2.4 95 106 138 339 76.8 369 Kagisano/Molopo Sparse Rural in LM 57 758 54 050 53 684 (4 074) Δ Decline 14 540 3.7 4 572 2 965 4 417 11 954 82.2 12 342 Lekwa-Teemane High Density Settlements in LM 264 885 1 383 1 119 ΨΨΨ Increase 373 2.4 4 9 19 31 8.3 282 Lekwa-Teemane Local or Niche Town Bloemhof 14 769 22 040 27 062 12 293 ΦΦ ΨΨΨ Large increase 7 127 3.1 68 310 1 305 1 682 23.6 5 097 Lekwa-Teemane Local or Niche Town Christiana 15 421 16 727 20 475 5 054 Increase 6 017 2.8 164 452 565 1 181 19.6 4 267 Lekwa-Teemane Sparse Rural in LM Sparse Rural in LM 6 395 3 317 4 324 (2 071) Δ Decline 1 411 2.3 48 163 182 392 27.8 846 ••• Mamusa Local or Niche Town Amalia 3 045 4 117 5 155 2 110 ΨΨΨ Increase 1 260 3.3 319 285 301 905 71.8 1 008 Mamusa ServiceTown Schweizer-Reneke ST 27 018 34 434 39 221 12 203 ΦΦ Large increase 9 332 3.7 652 859 1 301 2 811 30.1 7 042 Mamusa Sparse Rural in LM 13 214 9 821 15 976 2 762 Δ Increase 4 032 2.4 726 1 112 1 209 3 047 75.6 3 059 Naledi Dense Rural in LM 714 2 072 3 101 2 387 ΨΨΨ Increase 856 2.4 85 273 247 605 70.6 676 Naledi Local or Niche Town Stella 1 546 1 391 4 542 2 996 ΨΨΨ Increase 1 115 1.2 123 480 411 1 013 90.9 839 Naledi ServiceTown Vryburg ST 34 614 40 942 44 911 10 297 ΦΦ Large increase 12 796 3.2 1 019 1 664 2 697 5 381 42.0 8 291 ••• Naledi Sparse Rural in LM 17 191 11 914 14 228 (2 963) Δ Decline 3 805 3.1 324 1 081 963 2 368 62.2 2 621 •••
B34 CLUSTER 1: John Taolo Gaetsewe POPULATION HOUSEHOLDS SERVICE BACKLOGS INCOME STATUS
1996 2001 2011
TOWN OR SETTLEMENT TOWN OR SETTLEMENT LOCAL MUNICIPALITY TYPE DESCRIPTION
CHANGE 1996 - 2011
GROWTH BELOW BELOW GROWTH NATIONAL 2%NATIONAL LARGE INCREASE
RAPID GROWTH
GROWTH STATUS GROWTH
NUMBER NUMBER
SIZE
WATER WATER
SANITATION SANITATION
ELECT-RICITY
TOTAL POINTS TOTAL
BACKLOG %
POOR HOUSE-HOLDS POOR
LESS THAN LESS 70% POOR Gamagara High Density Settlements in LM 244 198 1 232 988 ΨΨΨ Small increase 231 0.9 3 11 9 22 9.6 130 ••• Gamagara Local or Niche Town Dibeng 4 020 4 141 6 608 2 588 ΨΨΨ Increase 1 233 3.4 14 58 43 115 9.3 695 ••• Gamagara Local or Niche Town Olifantshoek 7 260 7 124 10 039 2 779 Increase 2 132 3.3 40 280 199 519 24.3 1 161 ••• Gamagara ServiceTown Kathu ST 9 308 11 490 19 864 10 556 ΦΦ ΨΨΨ Large increase 5 940 1.9 42 156 755 953 16.0 2 117 ••• Gamagara Sparse Rural in LM 981 473 3 879 2 898 ΨΨΨ Increase 1 271 0.4 9 39 304 351 27.6 639 ••• Ga-Segonyana Dense Rural in LM 4 040 5 220 6 516 2 476 ΨΨΨ Increase 1 791 2.9 558 246 211 1 016 56.7 1 268 Ga-Segonyana High Density Settlements in LM 6 333 8 862 12 110 5 777 ΨΨΨ Increase 3 191 2.8 1 042 627 304 1 973 61.8 2 291 Ga-Segonyana ServiceTown Kuruman ST 44 300 48 877 64 639 20 339 ΦΦ Large increase 18 892 2.6 4 013 2 612 1 524 8 150 43.1 11 362 ••• Ga-Segonyana Sparse Rural in LM 8 767 7 321 10 385 1 618 Δ Increase 2 940 2.5 909 554 327 1 790 60.9 2 291 Joe Morolong Dense Rural in LM 16 021 16 271 16 319 298 Δ Stable 3 979 4.1 1 535 440 623 2 598 65.3 3 405 Joe Morolong Local or Niche Town Hotazel 383 1 232 1 237 854 ΨΨΨ Small increase 423 2.9 12 55 99 166 39.2 241 ••• Joe Morolong Local or Niche Town Santoy 1 289 1 016 990 (299) Δ Stable 339 3.0 10 44 79 133 39.2 193 ••• Joe Morolong Local or Niche Town Van Zylsrus 503 1 100 1 406 903 ΨΨΨ Small increase 481 2.3 14 62 112 188 39.2 274 ••• Joe Morolong Sparse Rural in LM 91 914 77 577 69 589 (22 325) Δ Major decline 18 485 4.2 6 652 2 720 3 411 12 783 69.2 15 435
B35
CLUSTER 1: Ngaka Modiri Molema POPULATION HOUSEHOLDS SERVICE BACKLOGS INCOME STATUS
1996 2001 2011
TOWN OR SETTLEMENT TOWN OR SETTLEMENT LOCAL MUNICIPALITY TYPE DESCRIPTION
CHANGE 1996 - 2011 BELOW GROWTH NATIONAL 2% LARGE INCREASE RAPID GROWTH STATUS GROWTH NUMBER SIZE WATER SANITATION ELECT-RICITY POINTS TOTAL BACKLOG % HOUSE-HOLDS POOR LESS THAN 70% POOR Ditsobotla Dense Rural in LM 6 533 6 363 8 305 1 772 Δ Increase 2 239 2.8 748 421 596 1 765 78.8 1 872 Ditsobotla High Density Settlements in LM 3 221 2 596 4 137 916 Δ Small increase 1 033 2.5 183 223 303 709 68.6 749 Ditsobotla Local or Niche Town Biesiesvlei 2 533 5 598 5 473 2 940 ΨΨΨ Increase 1 371 4.1 321 342 749 1 413 103.0 1 117 Ditsobotla Local or Niche Town Coligny 9 785 17 181 18 703 8 918 ΦΦ ΨΨΨ Large increase 4 576 3.8 600 2 057 2 774 5 431 118.7 3 601 Ditsobotla Local or Niche Town Sheila 911 1 078 982 71 Δ Stable 255 4.2 30 24 26 80 31.2 177 ••• Ditsobotla RegionalCentre3 Lichtenburg RSC 27 159 33 833 41 794 14 635 ΦΦ Large increase 11 797 2.9 644 1 081 2 516 4 241 36.0 6 790 ••• Ditsobotla ServiceTown Itsoseng ST 28 999 53 641 49 144 20 145 ΦΦ ΨΨΨ Large increase 12 860 4.2 3 085 614 1 071 4 771 37.1 9 663 Ditsobotla Sparse Rural in LM 51 293 27 281 40 366 (10 927) Δ Major decline 10 367 2.6 2 427 2 625 3 531 8 583 82.8 8 077 Mafikeng Dense Rural in LM 36 570 36 440 41 092 4 522 Δ Increase 10 378 3.5 4 924 1 205 3 010 9 139 88.1 8 346 Mafikeng High Density Settlements in LM 9 279 9 548 9 452 173 Δ Stable 2 847 3.4 355 124 482 961 33.7 2 225 Mafikeng Local or Niche Town Ottoshoop 679 1 194 1 191 512 ΨΨΨ Small increase 332 3.6 51 74 135 260 78.4 258 Mafikeng Local or Niche Town Rooigrond 128 1 839 2 780 2 652 ΨΨΨ Increase 664 2.8 420 60 216 696 104.8 522 Mafikeng Local or Niche Town Slurry 326 1 032 953 627 ΨΨΨ Small increase 232 4.4 80 30 70 181 78.0 170 Mafikeng RegionalCentre2 Mmabatho RSC 167 887 187 504 212 553 44 666 Δ ΦΦ Significant increase63 374 3.0 16 357 2 662 7 383 26 402 41.7 41 088 ••• Mafikeng Sparse Rural in LM 29 128 21 856 23 518 (5 610) Δ Decline 6 414 3.4 2 062 546 1 733 4 341 67.7 4 733 Ramotshere MoiloaDense Rural in LM 22 073 22 548 23 873 1 800 Δ Increase 5 929 3.8 1 942 510 971 3 423 57.7 5 015 Ramotshere MoiloaHigh Density Settlements former BOP 8 064 9 135 11 840 3 776 Increase 2 599 3.5 552 156 521 1 229 47.3 2 232 Ramotshere MoiloaHigh Density Settlements in LM 25 045 26 586 27 532 2 487 Δ Increase 7 894 3.4 1 464 578 1 193 3 236 41.0 5 745 Ramotshere MoiloaLocal or Niche Town Dinokana 22 786 24 198 22 711 (75) Δ Stable 5 709 4.2 1 101 189 811 2 101 36.8 4 834 Ramotshere MoiloaLocal or Niche Town Moshana 9 381 8 830 10 387 1 006 Δ Increase 2 590 3.4 1 322 52 264 1 639 63.3 2 287 Ramotshere MoiloaLocal or Niche Town Motswedi 9 871 9 145 9 468 (403) Δ Stable 2 552 3.6 340 92 342 774 30.3 2 087 Ramotshere MoiloaLocal or Niche Town Zeerust 9 356 13 591 15 981 6 625 ΨΨΨ Increase 4 375 3.1 23 29 114 166 3.8 1 996 ••• Ramotshere MoiloaSparse Rural in LM 21 832 23 302 28 909 7 077 Increase 9 093 2.6 1 957 1 434 3 144 6 534 71.9 7 019 Ratlou Dense Rural in LM 4 178 5 498 4 908 730 Δ Small increase 1 131 4.9 418 242 264 924 81.7 974 Ratlou High Density Settlements in LM 38 912 45 520 45 544 6 632 Δ Increase 11 543 3.9 3 737 1 579 1 775 7 092 61.4 10 144 Ratlou Local or Niche Town Madibogo 26 243 24 113 22 044 (4 199) Δ Decline 5 434 4.4 1 789 378 487 2 655 48.9 4 667 Ratlou Local or Niche Town Setlagole 12 479 11 073 14 035 1 556 Δ Increase 3 414 3.2 2 588 750 575 3 913 114.6 2 807 Ratlou Sparse Rural in LM 16 728 19 803 20 808 4 080 Δ Increase 5 366 3.7 1 888 1 126 1 286 4 301 80.2 4 636 Tswaing Dense Rural in LM 7 830 13 453 12 003 4 173 Increase 3 088 4.4 960 250 530 1 741 56.4 2 608 Tswaing High Density Settlements in LM 23 761 29 698 30 677 6 916 Δ Increase 7 312 4.1 1 919 842 1 713 4 475 61.2 6 093 Tswaing Local or Niche Town Atamelang 5 514 5 977 6 247 733 Δ Small increase 1 751 3.4 101 133 138 373 21.3 1 135 ••• Tswaing Local or Niche Town Delareyville 2 168 5 017 8 161 5 993 ΨΨΨ Increase 2 092 2.4 678 468 1 085 2 230 106.6 1 603 Tswaing Local or Niche Town Ottosdal 11 942 18 766 15 901 3 959 Increase 3 563 5.3 416 643 828 1 888 53.0 2 832 Tswaing Local or Niche Town Sannieshof 6 235 7 613 7 051 816 Δ Small increase 1 938 3.9 199 324 420 943 48.7 1 373 Tswaing Sparse Rural in LM 34 880 33 604 44 181 9 301 Δ ΦΦ Large increase 10 889 3.1 2 386 2 285 3 347 8 018 73.6 8 337
B36
Figure 4.7: Regional indication of pockets of high basic service demands, high population densities and growth
B37
IMPLICATIONS:
The area is largely sparsely populated; however, there is a trend for people to move to towns and a more concentrated pattern of development is emerging. This, together with low levels of employment and high dependency ratios, has resulted in a network of towns and settlements that are characterised by concentrations of lower income households and significant backlogs in terms of service delivery for water, sanitation and to a lesser extent electricity. Given the serious constraints with regards to water availability, concentrated settlement patterns probably make service delivery more viable. Significant numbers of households are also settled in high density settlements in the former homeland areas, especially in and around Ganyesa, Taung and Madibogo. Huge backlogs and high unemployment create ideal opportunities for alternative approaches to basic service provision and job creation.
B38 5. Where are the economic development strengths, sectors and areas in the priority rural districts?
The purpose of this analysis is to identify existing strongholds of economic activity and resource potential in districts, i.e. areas with relatively high economic activity and employment functions; economic diversification across sectors; and areas with resource based potential for agriculture, mining or natural resources. In addition, spatial concentrations of sector specific activity as well as employment and infrastructure investment initiatives need to be considered. In order to answer these specific questions, the analysis reviewed the economic data with respect to four sub-themes as indicated below.
Theme 3: Identify areas characterised by high levels of economic development and/or market accessibility
1. High levels of economic activity and/or growth
2. Areas with high levels of economic and government services - range of sectors
3. Areas with high market potential, measured by high levels of proximity to household income
4. High levels of accessibility
B39 5.1 High levels of economic activity or growth
Figure 5.1 provides an overview of the economic growth and decline of the 23 districts for the period 1996 to 2009. From this it is evident that large parts of Joe Morolong and the far north-west of Kagisano/Molopo are declining in economic terms while on the other hand Ga-Segonyana District with the main town of Kuruman has shown the highest growth in this cluster (between 5.1 and 7.5%). This is followed by Ditsobotla with between 2.6 and 5% growth in its economy. The economy of all other areas in the cluster has only grown between 0.1 and 2.5% per annum over this period.
In terms of economic activity, the significance of the resource base, in especially the northern and central parts of the country, is well recognised – particularly in terms of the potential for job opportunities within the National Development Plan. In terms of providing opportunities for up-scaling rural development, it is significant that more than 34% of the national agriculture gross domestic product in 2009 and almost 20% of that of mining was generated within the 23 priority districts. Given municipal growth trends for mining and agriculture production, it is evident that priority districts in the North West play a key role in national agriculture (Ditsobotla) and mining production (Gamagara) (see Figure 5.2).
B40
Economic strengths and growth – slow but upwards in the eastern parts
Eastern areas illustrating sustained growth 1996 -2009 (even though from low base)
The map indicates Economic GVA growth in the period 1996-2009 for 23 districts only. Taking all economic sectors into account: Mussina LM (Vhembe), Okhahlamba LM (Uthulelo), Ingwe
LM (Sisonke) , Matatiele LM (Alfred Nzo), Elundini LM (Joe Gqabi), and Ngquza Hill LM (OR Tambo) have shown the largest growth. Comparatively the districts in the western part of SA have performed poorly with some (Group1) showing a declining economy.
Figure 5.1: Economic strengths and growth (1996-2009) B41
Figure 5.2: National significance in resource based economy
B42 5.2 Economic analysis by main economic sectors – employment perspective
To identify where the economy is highly reliant on the services sector and specifically that of government services, a more detailed spatial- geographic analysis was conducted of economic activity for all 9 sectors for the 2009 data. The comparative overview of economic activity (using GVA as a proxy indicator) within the various municipalities for this time period is set out in the graph in Figure 5.3. If we review data from an employment perspective, the picture is somewhat different and we see a larger role played by a single sector, namely Community and Government services. (See Figure 5.4 and Table 5.1 that follow) The role that the Government and Community services sector plays in terms of both job creation and economic activity in the 3 districts is clearly evident – almost accounting for 50% of employment in the respective districts and being the largest contributor to the economy in both Dr Ruth Segomotsi Mompati DM and in Ngaka Modiri Molema DM. This highlights the critical role of the state within these areas even further.
In John Taolo Gaetsewe, mining is the largest contributor to the economy as well as being significant with respect to employment (23%) and is second to the Community Services and Government sector in terms of the number of people employed. Agriculture is significant with respect to employment in Dr Ruth Segomotsi Mompati although it only features in the top 3 categories of economic activity (using GVA as proxy) in three LMs. The importance of the Community and Government service sector and the Wholesale, retail and trade sector in the employment in the three districts’ economies is significant. This sector is also the largest contributor with respect to GVA at a district level in Dr Ruth Segomotsi and Ngaka Modiri Molema. Mining is the biggest contributor to GVA in the district of John Taolo Gaetsewe as well as in each of its LMs. Ditsobotla is the only LM outside John Taolo Gaetsewe where the Community and Government services sector is not the biggest sector in the economy. In Ditsobotla, the Finance and Business Services sector overtakes Community and Government Services from a GVA perspective. When it comes to employment, the Community and Government Services sector is the largest employer in all LMs, with the exception of Gamagara where mining is the largest employer (see Figure 5.3 and Table 5.1 below).
It is clear that in general the economies of this cluster are not highly diversified and there is a heavy dependency on the Government and Community sector for both GVA and employment. The only other sector to play a significant role is mining and retail services. Irrespective of the fact that mining of iron ore occurs in this region and that agriculture is a large contributor in Tswaing and Kagisano and is a relatively large employer, beneficiation of any significance of primary products is not apparent.
B43 CLUSTER 1 : GVA percentage per economic sector
60
40
20
0
Dr Ruth Segomotsi Mompati DM Ngaka Modiri Molema DM John Taolo Gaetsewe
Figure 5.3: Economic contribution of the various sectors at LM level (2009)
B44 60000 Agriculture, forestry and fishing (SIC 1) CLUSTER 1: Jobs per economic sector
50000 Mining and quarrying (SIC2)
40000 Manufacturing (SIC3)
30000 Electricity, Gas and Water supply (SIC 4)
20000 Wholesale and retail trade; Repair of motor vehicles, motor cycles and personal and household goods; Hotels 10000 and restaurants (SIC 6) Transport, Storage and Communication (SIC7)
0 Financial Intermediation, Insurance, Real
Estate, and Business Services (SIC8)
Naledi
Ratlou
Tswaing
Mamusa
Mafikeng
Gamagara Ditsobotla
Community Social and Personal Services,
JoeMorolong Ga-Segonyana
Greater Taung as well as Government Services (SIC9&10)
Lekwa-Teemane
Kagisano/Molopo RamotshereMoiloa
Dr Ruth Segomotsi Mompati John Taolo Gaetsewe Ngaka Modiri Molema
Figure 5.4: Employment for the various sectors at LM level (2009)
B45 Extremely low employment rates are once again evident in Table 5.1 – 9.3% employment for Dr Ruth Segomotsi Mompati, 11.5% for John Taolo Gaetsewe and 13.4% for Ngaka Modiri Molema. (The three largest employment sectors have been highlighted for each district; red for the highest, orange for second highest and yellow for third highest) These low employment rates are probably exacerbated by low skills levels. Figure 5.5 below provides a breakdown of the education levels for the three districts. This is compared to the national average for all other non- metro areas. These regions lag behind with respect to most categories. The districts have a larger percentage of the population with no schooling and less people with matric or post matric qualifications than the national average. Unlike national statistics those with matric or post matric qualifications makes up less than 20% of the population. There is a major drive to ensure a larger skills work force; however, it can be argued that aspects such as the lack of economic prospects, affordability, the absence of role models and high quality schooling in many areas, as well as the lack of access to higher order educational facilities has a negative impact on motivation, aspirations and ability to attain matric and post matric qualifications.
Education Level
John Taolo Gaetsewe No schooling
Grade 3 or less
Grade 4-6
Ngaka Modiri Molema Group1 Grade 7
some secondary Dr Ruth Segomotsi Mompati
Matric
Certificate /Dip with less than Grade 12
National Non-Metro Average Technical/ Other Tertiary non degree
Bachelors Degree or Higher 0% 20% 40% 60% 80% 100%
Figure 5.5: Education and skills levels
B46 Table 5.1: Comparative economic activity per local municipality – employment focus
Employment - number of jobs per sector
diation, diation,
Municipality
Local
District Municipality
Total 2009 Population
Percentage Employed
Total (R Millions) GVA
GVA asGVA % RSA GVA total
Employment for 2009 total
Agriculture, forestry and fishing (SIC 1) (SIC2)quarrying Mining and Manufacturing (SIC3) Electricity, supply Water Gas and (SIC 4) Repair Wholesale trade; retail and motorof cycles motor vehicles, andand household personal goods; restaurants and Hotels (SIC 6) Transport, and Storage Communication (SIC7) Financial Interme Insurance, and Estate, Real Business Services (SIC8) Personal Community Social and Government Services, as as well Services (SIC9&10) Dr Ruth Segomotsi Greater Taung 2114.08178 0.10 177628 13283 7.48% 303 331 559 70 1292 75 1243 9414 Mompati Kagisano/Molopo 1202.96482 0.06 105782 6724 6.36% 1413 364 243 51 759 153 399 3346 Lekwa-Teemane 971.55582 0.05 53244 5467 10.27% 1126 438 769 37 767 149 383 1792 Mamusa 1055.0101 0.05 60352 6232 10.33% 1418 477 179 24 942 45 779 2370 Naledi 2708.25387 0.13 91101 13715 15.05% 1593 84 788 168 2359 406 1807 6509 8051.86639 0.39 488107 45421 9.31% 12.89% 3.73% 5.59% 0.77% 13.47% 1.82% 10.15% 51.59%
John Taolo Gamagara 5833.03456 0.28 41622 8596 20.65% 208 3629 325 33 1031 385 579 2410 Gaetsewe Ga-Segonyana 2929.74619 0.14 93650 13126 14.02% 420 1439 500 44 2505 207 1425 6588 Joe Morolong 1286.51707 0.06 89541 4047 4.52% 603 1023 39 81 189 186 166 1765 10049.29782 0.48 224813 25769 11.46% 4.78% 23.64% 3.35% 0.61% 14.45% 3.02% 8.42% 41.77%
Ngaka Ditsobotla 5599.17651 0.27 168904 29895 17.70% 3973 354 3575 130 6274 474 4188 10936 Modiri Molema Mahikeng 10735.81487 0.51 291539 53549 18.37% 2071 1169 3621 252 8849 956 9207 27421 Ramotshere Moiloa 2553.72172 0.12 150701 13787 9.15% 570 446 889 169 3546 158 1414 6597 Ratlou 770.70905 0.04 107339 5142 4.79% 955 245 371 5 1282 23 0 2257 Tswaing 1817.61001 0.09 124221 10885 8.76% 2241 147 782 47 1631 258 760 5022 21477.03216 1.03 842704 113258 13.44% 8.66% 2.08% 8.16% 0.53% 19.06% 1.65% 13.75% 46.12%
B47 A spatial analysis of production points further provides a good indication of spatial distribution and proximity of jobs located in the specific sectors. The sectors include:
Wholesale and retail trade – SIC 6 (Figure 5.6) Manufacturing – SIC 3 (Figure 5.7) Electricity, gas and water supply – SIC4 (Figure 5.8) Financial intermediation, insurance, real estate and business services – SIC 8 (Figure 5.9) Transport, storage and communications – SIC 7 (Figure 5.10) Community, personal services and government services – SIC 9 & 10 (Figure 5.11) Agriculture, forestry and fisheries – SIC 1 (Figure 5.12) Mining and quarrying – SIC 2 (Figure 5.13).
B48 Figure 5.6 below once again highlights the role of towns and settlements in this mainly rural area. As can be expected the main towns, i.e. Mmabatho/Mahikeng, Lichtenburg, Vryburg, Kuruman and Kathu are the main areas were income is derived from wholesale and retail trade.
Figure 5.6: Strengths in Wholesale Retail and Trade (SIC 6) B49 The main areas where manufacturing is found are Mmabatho/Mahikeng, Lichtenburg, and Kuruman, Kathu as well as a few smaller isolated locations as indicated on Figure 5.7 below, again stressing the role of towns in the development of these districts.
Figure 5.7: Strengths in Manufacturing (SIC 3)
B50 The main settlements and mines are as can be expected the locations where income is derived from electricity, gas and water supply.
Figure 5.8: Economic Strengths: Electricity, gas and water supply (SIC 4)
B51 Once again the larger towns are the main centres of activity for Financial, Intermediation, Insurance, Real Estate and Business Service sector.
Figure 5.9: Economic Strengths: Financial Intermediation, insurance, real estate and business services (SIC 8)
B52
Figure 5.10: Economic Strengths: Transport, Storage and Communications (SIC 7)
B53
Income from the Transport, Storage and Communications sector is somewhat more distributed and this is mainly along the main transport corridors thus clearly indicating the role that roads play within any region. It is noted that economic activity (GVA) for this sector is more concentrated in the more populated north-eastern sector closer to Gauteng and the two large centres of Mmabatho/Mahikeng and Lichtenburg. The exception is the area around Sishen/Kathu which can be related to iron ore transport. Given the distributed nature of these districts it is essential that the transport links within the area are well maintained to ensure the efficient flow of goods and services as well as ensuring that the community can reach government services or vice versa. The current condition of roads was not considered in this project and more detailed investigation of this aspect should be undertaken in conjunction with the National Department of Roads and the S’hamba Sonke Road Programme.
B54
Figure 5.11: Economic Strengths: Community, Social, Personal and Government Services (SIC 9 & 10)
As can be seen from Figure 5.11 above, the income derived from the Community, Social and Government Services sector is much more widely distributed across the entire cluster than is the case for the other economic sectors income. This is closely linked to the distribution of people in the area, many of whom have no employment and are thus very likely to depend on government grants for survival.
B55
Figure 5.12: Economic Strengths: Agriculture, Forestry and Fishery (SIC 1)
From Figure 5.12 above it can be seen that agriculture only makes a significant impact on the GVA in the eastern areas. The central areas around Vryburg was traditionally a major meat and dairy producing area, as well as producing a range of crops such as maize and groundnuts; however, in the 2009 data the evidence of this on GVA was negligible. This study could not investigate the reasons for this and more detailed investigation may be required. The cyclical drought conditions of the region as well as land degradation (See Figure 6.1) may be contributing factors. B56
Figure 5.13: Economic Strengths: Mining and Quarrying (SIC 2)
Sishen is the largest earning mining area in the region along with the mines north of Hotazel. Other isolated pockets of mine-related income are evident. Despite the small spatial extent of the mines, the income from this sector plays a significant part in the economy of John Taolo Gaetsewe. Limited beneficiation occurs and the transport of the mine output to other centres for beneficiation or export is required. This once again is an indication of the important role that the maintenance of transport infrastructure plays to ensure cost effective transport which enables mines to remain competitive and viable.
B57
Figure 5.14: Economic vulnerabilities/hot spot areas
B58
Figure 5.14 above has been generated utilising data from the South African Risk and Vulnerability Atlas. It has been developed to highlight the areas that are most vulnerable from an economic perspective. These are areas that are characterised by a low-economic base that is dependent on a single sector (in this case the Community and Government sector) as well as the residents having a low per capita income. The blue areas are the least vulnerable and the red areas are the most stressed.
5.3 Areas with good market accessibility and high ‘demand’ potential
From an analysis of population distribution, it is evident that a large portion of the population is actually located in close vicinity to bigger towns and service centres in the area. The same pattern is evident in analyses of proximity to household income levels in the area.
These areas are also marked by higher levels of road accessibility. For access to market concentrations (demand side), especially for the purposes of agriculture (i.e. dairy products) and manufacturing beneficiation, more opportunities are likely in areas with high levels of road infrastructure and accessibility which are found in areas surrounding big towns and service centres. The location of high potential agriculture land and tribal authority areas in relation to market demand areas are set out in more detail in Section 6.
Rural development needs to take cognisance of these opportunities.
B59
Figure 5.15: High population and market concentrations in areas surrounding big towns and service centres
B60
Implications:
It is evident that there is some economic potential in the area’s resource base (see Section 5.2 for more detail). The limits of agriculture and mining activities are also evident and land degradation, availability of water and the life span of the mines makes this more so. The most significant economic activities and employment levels are vested in the services sectors – government and community services, as well as retail, wholesale and trade. These are all services and activities that are anchored within towns and settlements in the region. The tendency of populations to gravitate to live in towns and the main sources of existing income (including grants) does, however, create some new market opportunities for agro-processing and lower and higher scale industrialisation. The (decline in the) beef and dairy industry needs further investigation. A budget and means to create sustainable job creation through road maintenance and provision and the maintenance of basic services such as water, sanitation and electricity should be supported.
B61 6. Where are the prime rural zones/areas that should be prioritised for consolidation and the protection of prime rural production areas/zones?
The existing economic activity, as reviewed in the previous section, provides a good indicator of the potential for continued future economic activity, job creation, institutional capacity and current natural resource potential within rural districts. Natural resources such as mining and agriculture are the only non-service sectors to play a significant role in the economic production of this district. Natural resource potential is considered to be a key aspect to support and grow the economy and employment of the priority districts and, as such, it is necessary to support infrastructure in areas that have, or can be prioritised, as prime rural production areas, i.e.:
Agricultural production, in areas with potential related to specific products – especially smallholder farming and also in traditional authority areas Agro-logistics and production in relation to areas where there is high potential. This also relates to areas with high levels of access to key markets. Natural resource asset and tourism areas that can support local and regional economies Urban agriculture potential and a focus on hydroponics within settlements Within all of the above – areas for beneficiation, such as traditional authority areas and state land, to explicitly be considered as a priority.
The following diagram provides a framework for the analysis of the rural districts with respect to key parameters to identify areas that should be prioritised and supported as key rural production areas or zones. As we have seen in the previous set of analyses, the towns and settlements of all levels play a pivotal role in these rural districts as they are areas of the highest population and economic activity. They also, in the case of the niche and service towns and regional services centres, play a significant role with respect to social, government, community and financial services in an extensive, sparsely populated hinterland. To this end, they can be considered the closest market areas for fresh produce and are most likely to be the centres for product consolidation, beneficiation, processing, agricultural extension services, logistics and transport services. Like healthy growing hinterlands depend on services in towns, the economic health of the towns in agricultural/rural areas in South Africa is closely linked to production within the surrounding areas or hinterland. In the following sets of analyses, the focus is placed on areas in the rural hinterland with the potential for investment; however, also keeping in mind the need to invest and support the social and economic infrastructure in the closest town.
B62 Areas with high agriculture Agro-processing Agriculture market Priority beneficiation Other Resource production potential access & potential areas Areas potential
High number of Land Tourism regions High levels of land capability Central location on road people & household reform/redistribution network and within income areas network of towns Mining areas Access to water High levels of State land accessibility Opportunities for product beneficiation Ecosystem service Crop/live stock production Traditional Areas with growing areas eg. carbon and potential Authority Areas economies and sequestration population Relevant infrastructure
Exclude degraded land & land already under settlement
B63
6.1 Agricultural production and agro-processing potential
The following maps provide a broad overview of agricultural potential and market access in relation to state and tribal authority land.
Figure 6.1 spatially identifies the land capability of this cluster as a primary information layer. It also maps the nature reserves and mountainous areas. As is clearly evident, the only high potential areas of any significance are in Ditsobotla and Tswaing approximately situated from Lichtenberg southwards to Ottosdal. In the vicinity of Mmabatho/Mahikeng there are small areas of high capability land in state ownership and in tribal authority areas. The agricultural production capability/proposals are based on research undertaken by the Agricultural Research Council on the most effective as well as marketable product for the specific areas. What is also strikingly evident are the extensive areas of land that are indicated as being degraded. Some of the latter are closely correlated to tribal authority areas and other commercial farming areas (extensive farming). The latter speaks to poor farming practices, droughts and overgrazing.
The analysis considers areas with agriculture potential and areas of degradation. In Figure 6.2 proposals for the most suitable types of agricultural products are indicated. The area with the highest agricultural potential is mapped in relation to the 30 minutes access zone around the two largest centres in this area, namely Mmabatho/Mahikeng and Lichtenburg which have significant populations and thus have good market potential for agricultural produce and or agro-processing potential. In addition to the indicated products, the hinterlands of large towns generally have the potential for vegetable faming, dairy and poultry production. These areas are also close to the major Gauteng market and high intensity market gardening making use of hydroponic production should be investigated. In addition, the still substantial markets of the smaller towns also need to be regarded as kept market areas.
B64
Figure 6.1: Agricultural resource potential in sparsely populated areas – North West Northern Cape Cluster
B65
Figure 6.2: Rural Production Zones: Agriculture production and areas with highest market potential
B66 6.2 Other resource areas
In addition to agricultural production, tourism, mining and eco-system services can provide opportunities for economic development in this area.
Tourism in this area is not substantial when seen in the context of South Africa’s other destinations; however, some potential does exist to develop this sector (Figure 6.3). The key destinations appear to be the main towns as well as the service towns along the major routes through the area. Key locations are Zeerust and its environs which is the most extensive cluster of attractions and accommodation, Mmabatho/Mahikeng, Lichtenburg, Vryburg, Kuruman, Olifantshoek and Schweizer-Reneke (Figure 6.4). These towns are located on the key access roads between Gauteng and key tourism destinations such as Botswana, Upington/Kalahari Gemsbok Park, Namibia and the Western Cape. In some cases, the tourism potential is also linked to business travel. Limited non-town destinations are noted which are likely to be niche game lodges/Green Kalahari related tourism. The area should capitalise on its location on the main though-routes by the development of good overnight accommodation, garages, rest areas and restaurants. The area can also aim to extend the duration of stays of travellers passing through by the development of agro-tourism (farm stays), wilderness adventures, small niche museums, monuments and other similar attractions. The road maintenance of the key routes, namely the N14, N18, N4 and R34 are key to maintaining the role of the area as a staging area/gateway to the surrounding game reserves and natural attractions. Some of the routes experience heavy vehicle traffic from the mines as well as from the distribution of retail goods and transport of animal feeds, maize and livestock and so the maintenance of roads and suitable traffic management is required to maintain safety.
B67
Figure 6.3: Economic Strengths: Tourism attraction regions
B68
Figure 6.4: Rural Production and Demand Zones: Tourism Attraction Points (blue) in relation to levels of accessibility (green high and red remote)
B69
Figure 6.5: Rural Production Zones: Mining potential and risks
B70 The spatial location of the mining potential in these districts is provided in Figure 6.5. The analysis also highlights the areas (largely mining towns) that are highly dependent on the mining sector in terms of employment and livelihoods.
Major tourism points in the area, agricultural resource areas and the location of mines, together with accessibility provide key areas for potential beneficiation and are areas of possible value chain and other linkages. Accessibility and supportive infrastructure is critical to manage these areas for regional benefit.
The sale of carbon credits or Carbon Sequestration is one avenue that the priority rural areas may be able to explore as a source of income for these regions. The Department of Environmental Affairs has conducted a range of studies to identify the potential for carbon sequestration in South Africa. The following detail map (Figure 6.6) of this cluster provides an indication of where any potential in this regard exists in this cluster. As can be seen, the potential is limited, specifically to an area close to Mmabatho/Mahikeng and a small area of Tswaing, both of which have medium potential.
B71
Figure 6.6: Rural Production Zones: Carbon Sequestration Potential
B72 7. Within high density rural areas or outstretched regions, which anchor points, can play a key role as government service nodes and market concentration areas for government and economic services, both at local level and regional level?
Given the centralisation trends, limited resource potential and current economic and market strengths, it is important to identify areas where the potential exists to cluster government, community services and economic services, thus forging an agglomeration of opportunities and synergies in addressing access to higher order social facilities and economic services. To support regional and rural development, a strong network of services places are required which can act as loci for development and services in the surrounding regions. CSIR has developed a typology of settlements of different orders for South Africa. This is the starting point for the identification of a network of places to support the development of the priority rural districts.
In order to identify key regional centres, settlements need to be analysed in terms of their densities and market potential for service, manufacturing and agro-processing activities as they play a strong role in providing access to government services and economic opportunities within sparsely populated area to which they are linked and which essentially form their functional hinterlands.
In terms of understanding, the functional interaction between areas and specifically between the priority districts and any economic anchor points has been investigated, as well as the identification of any possible regions with economic potential, through a number of functional regional analyses – many of which have been discussed earlier in this report. [This will be supplemented in more detail by a follow up project spearheaded by the Economic Development Department to identify economic areas of interaction.]
7.1 Identification of Regional Centres of Excellence In the analysis to establish which anchor points can be used to play a key role as government service nodes and areas of market concentration of the region, a set of key questions was developed and the framework outlined below was used to answer the questions and identify areas of specific types, namely:
areas with large and growing populations nodes that are strategically located to support rural regions areas of economic agglomeration strengths areas where higher order government service will have the most impact.
In each instance the sub-questions as indicated in the following framework were used to derive the identification of additional anchor points as well as being used to create a typology and differentiation of places.
B73
Areas where high order Areas with large & Nodes strategically Areas with economic growing population and agglomeration government services will located to support have high impact settlements rural regions strengths
6. Regional reach to large 1. Population Size 8. High economic 5. Central location on road population in poverty & Density network and within agglomeration potential network of towns and nodes 11. Target spatially 2. Population growth 9. High market disadvantaged (former potential (formal & homeland) areas 6. Highly accessible to informal) large part of population & 3. In-migration people living in poverty
10. Existing and/or 12. Consider the role of Administrative capitals 4. Surrounding area under growing economies (LM/DM/Former Home pressure of settlement growth 7. High regional reach/ land) or change function in surrounding rural hinterland
B74 Figure 7.1 provides the settlement typology for the cluster of districts. This typology is based on population density, employment, urban functional service index and economic activity. For more details see Table 7.1.
A city is a place that together with its functionally linked urban areas is home to a population of more than 400 000 people; it has significant multi-nodal economies; plays a significant role in the region in terms of service delivery and the economy; play a major role in government and commercial service delivery; has a relatively high economic growth rate; and attracts people. A regional centre is a medium and high order town that plays a prominent role in offering services to the hinterland. These towns typically have large populations in densely settled areas, or are towns in resource-rich areas that are relatively accessible, or are smaller towns playing a key service function in a more isolated and less accessible area. Service centres are smaller towns that seem to fulfil a particular service role within the local area. These centres may have a small service index but serve a large population, or serve a small population in a sparsely populated or isolated area. Local and niche towns are small towns that fulfil a local function or fulfil a particular niche function. Such towns have a smaller population and economic activity and are geographically more evenly distributed throughout the country than settlements in other categories. High density rural areas are densely populated but play a very limited service role and are often under traditional land ownership2.
The typology and hierarchy of towns help to understand the role and functions of towns and indicates that not all towns have the same function in the space economy, and motivates for a differentiated investment strategy. The long term development potential, the need for infrastructure and service delivery, and the role in development will be determined by the manner in which the town is affected by economic development trends and its ability to respond to these demands. It also illustrates why the approach to economic development in rural South Africa has to be intrinsically linked to the realities of economic anchors and networks of settlements, and the importance in maintaining and investing in services in these areas.
In the development of a network of local nodes, it is firstly important to identify Regional Service Centres, Service Towns and Niche/Local Towns. In this cluster of districts, there is a limited number of major service centres, with smaller towns also spread out through the region. These dense rural areas have a limited network of nodes or any potential for the creation of such required rural nodes. Given the sparsely populated character of this region, the analyses of the network of local and service towns and dense rural settlements that was undertaken has not indicated major additional rural nodes that can or should be established, except outside the District to the north.
The analysis of settlements has indicated that at a regional scale there are two Regional Service Centres (RSC), namely Mmabatho/Mahikeng and Lichtenburg, which play a dominant service anchor and urban role in this cluster. See Figure 7.1 showing the Settlement Typology for these districts and some of the surrounding areas.
There are a few Service Towns including Kuruman, Vryburg, Itsoseng, Taung, Schweizer-Reneke and Kathu. Vryburg which, although not having the population or urban functional index that the RSCs have historically had, still play a strategic role as regional and administrative
2 Van Huyssteen, E.; Biermann, S.; Naudé, A. & Le Roux, A. (2009). Advances in spatial analysis to support a more nuanced reading of the South African space economy, in Urban Forum, Vol. 20, pp195–214. B75 service centres within a very sparsely populated and vast hinterland. All the Service Towns as shown on the following Figure 7.1 play an extremely important role in servicing the population of those towns as well as the surrounding hinterland.
Kuruman and Kathu too are playing an increasingly important role, with both areas featuring amongst the 20 cities and towns with the highest annual population growth rates in the country over the 1996 to 2011 period. The catchment areas of the service towns become increasingly larger as the population density declines and residents tend to accept travelling longer distances to reach places and services as the norm. The low density of the region is related to the arid nature of the region and has a distinct east to west decline. The following table (Table 7.1) shows the population and the growth rate of the main towns in the region. Kathu, Kuruman and Lichtenberg are three of the fastest growing places in the region.
B76
Figure 7.1: Network of economic anchor points and settlements
B77 Table 7.1: CLUSTER 1: Summary of population in Regional Service Centres and Towns CLUSTER 1: Summary of population in Regional Service Centres and Towns POPULATION LOCAL Functional area - CHANGE DISTRICT MUNICIPALITY Town Type 1996 2001 2011 GROWTH STATUS MUNICIPALITY Town Name 1996 - 2011
Local or Niche Town Manthestad Dr Ruth Segomotsi Mompati 4 998 4 642 2 987 (2 011) Decline Local or Niche Town Pudimoe 15 441 13 294 13 745 (1 696) Decline Greater Taung Local or Niche Town Reivilo 3 000 3 684 3 155 155 Stable Service Town Hartswater ST 7 649 8 256 7 071 (578) Minor decline Service Town Taung ST 34 801 36 487 35 790 989 Small increase Local or Niche Town Ganyesa 14 540 16 713 19 207 4 667 Increase Kagisano/Molopo Local or Niche Town Morokweng 12 230 12 738 14 741 2 511 Increase Local or Niche Town Piet Plessis 328 1 067 1 506 1 178 Increase Local or Niche Town Bloemhof 14 769 22 040 27 062 12 293 Lekwa-Teemane Large increase Local or Niche Town Christiana 15 421 16 727 20 475 5 054 Increase Schweizer- Mamusa Service Town Reneke ST 27 018 34 434 39 221 12 203 Large increase Local or Niche Town Stella 1 546 1 391 4 542 2 996 Naledi Increase Service Town Vryburg 40 942 44 911 10 297 Large increase
Local or Niche Town Dibeng John Taolo Gaetsewe 4 020 4 141 6 608 2 588 Increase Gamagara Local or Niche Town Olifantshoek 7 260 7 124 10 039 2 779 Increase Service Town Kathu ST 9 308 11 490 19 864 10 556 Large increase Ga-Segonyana Service Town Kuruman ST 44 300 48 877 64 639 20 339 Large increase Local or Niche Town Hotazel 383 1 232 1 237 854 Small increase Local or Niche Town Santoy Joe Morolong 1 289 1 016 990 (299) Stable Local or Niche Town Van Zylsrus 503 1 100 1 406 903 Small increase Local or Niche Town Biesiesvlei Ngaka Modiri Molema 2 533 5 598 5 473 2 940 Increase Local or Niche Town Coligny 9 785 17 181 18 703 8 918 Large increase Ditsobotla Local or Niche Town Sheila 911 1 078 982 71 Stable Lichtenburg Regional Centre 3 RSC 41 794 14 635 Large increase Service Town Itsoseng ST 28 999 53 641 49 144 20 145 Large increase
B78 CLUSTER 1: Summary of population in Regional Service Centres and Towns POPULATION LOCAL Functional area - CHANGE DISTRICT MUNICIPALITY Town Type 1996 2001 2011 GROWTH STATUS MUNICIPALITY Town Name 1996 - 2011
Local or Niche Town Ottoshoop 679 1 194 1 191 512 Small increase Local or Niche Town Rooigrond 128 1 839 2 780 2 652 Increase Mahikeng Local or Niche Town Slurry 326 1 032 953 627 Small increase Significant Regional Centre 2 Mahikeng RSC 167 887 187 504 212 553 44 666 increase Local or Niche Town Dinokana 22 786 24 198 22 711 (75) Stable Ramotshere Local or Niche Town Moshana 9 381 8 830 10 387 1 006 Increase Moiloa Local or Niche Town Motswedi 9 871 9 145 9 468 (403) Stable Local or Niche Town Zeerust 9 356 13 591 15 981 6 625 Increase Local or Niche Town Madibogo 26 243 24 113 22 044 (4 199) Ratlou Decline Local or Niche Town Setlagole 12 479 11 073 14 035 1 556 Increase Local or Niche Town Atamelang 5 514 5 977 6 247 733 Small increase Local or Niche Town Delareyville 2 168 5 017 8 161 5 993 Tswaing Increase Local or Niche Town Ottosdal 11 942 18 766 15 901 3 959 Increase Local or Niche Town Sannieshof 6 235 7 613 7 051 816 Small increase
B79 In addition to the distinct settlement pattern and dynamics that this patterns holds for development and service delivery, a key feature identified in the priority districts is that a large part of the economy is actually generated within Regional Service Centres, some of the mining towns and the network of service towns rather than in the extensive hinterlands of these places. Furthermore, it is important to note that other than the Community and Government Service sector, the resource economy as well as income generated from Tourism and Trade in the sparsely populated areas is vital to this region as they provide a measure of diversity and independence from government income sources. The data clearly highlights the crucial role that a few service centres play as population centroids and thus economic and service anchors within the region (see Figure 7.2). There are limited areas of population concentration/higher density outside 30 km of the main towns and this clearly shows where infrastructure support can have the biggest impact for the largest number of people within the smallest spatial extent.
The areas in Figure 7.2 marked in yellow are concentrations of population – this indicates the wide reach of the network of service towns and regional service centres. This figure thus clearly illustrates why the approach to economic development in rural South Africa has to be intrinsically linked to, and needs to consider, the realities of economic anchors and networks of settlements, and the importance in maintaining and investing in services in these areas. The importance of both settlement quality, service delivery, access to education and health services and the creation of linkages between urban areas and their rural hinterland and vice versa are important and the role of this network of towns cannot be underestimated in the attainment of a better social and economic future for these districts.
In the same vein, the importance of a focus on the high density settlement areas, largely located on tribal land and within the borders of former homeland areas, are also evident. Figure 7.3 shows the results of a very broad stroke analysis that was undertaken to identify high density rural settlements that are further than 30 km from higher order service centres (regional service centres and small service centres; these being towns with at least some significant level of economic and government services).
As further evidence of functional linkages and to provide an indication of the strength and reach of functional interactions within a regional context, the number of trips made for the purpose of education and for work is often used as a key indicator. Unfortunately, existing data of these travel trip linkages for South Africa is extremely outdated; however, an analysis of this older data confirms the high levels of regional interaction that exist for education purposes and the importance that government services play. In a context where unemployment is rife, the distances that people are prepared to travel and commute on a daily, weekly, monthly or seasonal basis must not be underestimated and this further emphasises the importance of the network of service centres (Figure 7.3) in the regional development of this area.
B80
Figure 7.2: Functional areas playing a significant economic and service centre role in priority district
B81
Figure 7.3: High density settlements beyond 30 km access of significant service centres
B82
It is, however, important to note that beyond the spatial influence of the extent of the service centres and towns, the outlying hinterland area is still faced with the on-going influence of apartheid legacies. Many of the remote former homeland areas have developed largely as very highly densely settled areas without any economic base or the required range of social services necessary to support the extensive populations which are provided in urban settlements of such extent. Figure 7.3 specifically highlights both the Dense Rural and High Density Rural areas that are outside a 30 km travel range of any town where a full range of government and social services (including the required health, education services) are likely to be provided. From this it is evident that Atamelang, Madibogo and Sannieshof as well as Zeerust, to the north, are largely the high density settlement areas that are further than 30 km away from a regional service centre, and these would require better access to services than are currently likely to be provided to these extensive groups of population. These services include the core services citizens require to transact their lives including Home Affairs offices, SASSA, SAPS and financial services.
7.2 Identification of Potential Rural Nodes
A regional scale analysis of the densely settled rural areas outside of the 30 minute catchment of the towns was undertaken in order to extend the network of towns and urban service delivery points more widely and thus identify potential alternative markets in addition to the identified towns. This was supported by an analysis of places in relation to levels of household income. This analysis showed that the Swartruggens area was the only area close to this cluster that could be identified as having the potential for serving as a rural node (Figure 7.4) and that as such could provide an ideal opportunity for synergy between industrial and government service activities in the region.
The remaining areas beyond 30 km of a service centre or town have such low population densities and access to household income that it is not viable to identify any additional rural nodes within these three districts. However, support is required for existing centres such as Vryburg, Kuruman, Schweizer-Reneke, Taung and Kathu to effectively provide services to smaller settlements and dispersed populations in their hinterland, as well as using settlements such as Van Zylsrus, Gaynesa, Morokweng, Piet Plessis, Stella, Bray, Sannieshof, Reivelo, Setlagole, Madibogo, Broedersput and other such settlements in their catchments to provide local and national level government services on a periodic or part-time basis in order to meet the needs of these smaller points of population concentration and where there is insufficient evidence of the need to develop and support a specific “rural node”.
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Figure 7.4: Potential focus for extending rural node role
B84 As a further step to seeking nodes of significant economic activity outside of the identified towns, a further analysis was undertaken focusing on the non-primary sectors. This analysis was undertaken for any high density mesozones outside of towns. The results suggest that there are areas that have significantly more clustering of service and economic activity than other areas. The three sectors that were specifically analysed were SIC 6 – wholesale and retail (incorporates tourism), SIC 7 – transport, storage and communication, and SIC 9&10 – community and government services. As can be seen in Figure 7.5, there are several clusters of activity outside the nodes. The green points show points of wholesale and retail clustering and can most likely be considered to be points of tourism activity. The purple and blue points are areas of clustering of government services. There are no points of clustered transport economy outside the towns. The identified points have significantly more economic activity of the specified type than the surrounding areas and as such may have potential for consolidation as nodes and the clustering of government and economic services.
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Figure 7.5: Differentiation in existing rural concentration and anchor points
B86 8. Summary of Key Interventions
The range of analyses, findings and next steps are provided in an intervention summary table in the following section. An overview of the priority infrastructure investment for catalytic transformation is summarised and set out in the following tables. The guiding questions can be utilised with the more detailed accompanying information as evident from the analyses.
Table 8.1: Summary of investment priorities
CATALYTIC INFRASTRUCTURE INVESTMENT AREAS OF FOCUS TO HARNESS OPPORTUNITY AREA SPECIFIC COMMENTS PRIORITIES IDENTIFIED Basic service innovation as job creation catalyst Growing settlements, well located and with All regional service centres and service and local in high density settlements and growing towns good accessibility, high potential to make use of towns with growing populations. See Sections 3 – Utilise basic service provision and maintenance alternative energy solutions. and 4. as sustainable jobs and technology driver. Consolidate & protect prime rural production High potential agriculture production land, Potential agricultural land mainly located in zones – for income generation, regional food – areas within traditional authority ownership, eastern areas. Specific attention to be paid to tribal and ecosystem security. Investment and potential land reform sites, land owned by the and state land with high potential close to protection of high value agriculture land, market state, areas in close proximity to large markets Mmabatho/Mahikeng. All high potential lands are access zones, ecosystem resources, tourism asset for agro-production in diary/poultry/vegetables, sufficiently close to markets. See Sections 6 and 7. areas, mining areas. ecosystem resources, tourism asset areas. Create and formalise key service nodes (local) as Large number of people and high density No specific nodes of sufficient intensity identified catalyst in high density settlements – Identify formal and informal market access (proximity within cluster. See Figure 7.4. and prioritise selected, highly accessible rural to household income high), physical service nodes in areas with sprawling high consolidation of settlement structure, potential Support smaller concentrations beyond towns. See density rural settlements. Infrastructure and for consolidation of local level services access. Sections 3, 4, 5 and 7 (non-town economic economic agglomeration opportunity points in clusters). areas with high levels of household income proximity. Capitalise on centralisation through rural Well-connected and accessible, evidence of See Sections 3, 4, 5 and 7. Invest in and maintain centres (regional) of excellence – Government economic service hub formation, need for services and infrastructure in main RSCs and driven services, facilities and employment to higher order government facilities, potential for towns. stimulate and consolidate regional markets, rural consolidation of government facilities. nodes of excellence and economic opportunity. Place Specific Investments/Project priority areas Large scale SIP infrastructure projects, IDZs, – Major infrastructure, manufacturing areas. mining opportunities. B87 Table 8.2: Basic Services – Summary of investment priorities
Basic service innovation as job creation catalyst in high density settlements and growing towns
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Based on the analysis of service provision investment, the priority areas as seen on the maps below have been identified. Areas of both high growth and high backlog are to be prioritised for service investment and as such include Kuruman, Morokweng, Setlagole, Mmabatho/ Mahikeng, Itsoseng, Pudimoe and Van Zylsrus.
B89 Table 8.3: Rural Production Zones – Summary of investment priorities
Consolidate and protect prime rural production zones
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B92 Table 8.4: Key Service Nodes – Summary of investment priorities
Create and formalise key service nodes (local) as catalyst in high density settlements
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Support is required for existing centres such as Vryburg, Kuruman, Schweizer-Reneke, Taung and Kathu to effectively provide services to smaller settlements and dispersed populations in their hinterland as well as using settlements such as Van Zylsrus, Gaynesa, Morokweng, Piet Plessis, Stella, Bray, Sannieshof, Reivelo, Setlagole, Madibogo, Broedersput and other such settlements in their catchments to provide local and national level government services on a periodic or part-time basis in order to meet the needs of these smaller points of population concentration and where there is insufficient evidence of the need to develop and support a specific “rural node”. [Note: Income is shown here for a total area, i.e. all household income within a 20 min access distance]
B94 Table 8.5: Rural regional centres of excellence - Summary of investment priorities
Capitalise on centralisation through rural centres (regional) of excellence
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In addition to the RSC, the key areas to support would be to develop and strengthen the service towns such as Kuruman, Vryburg and Kathu along with some of the smaller places as identified on the Settlement Typology.
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