Land Use Policy 119 (2022) 106170
Available online 29 April 2022
0264-8377/© 2022 Elsevier Ltd. All rights reserved.
Declining land for subsistence and small-scale farming in South Africa: A case study of Thulamela local municipality
Zwidofhelangani Lidzhegu
a,*,1, Tabaro Kabanda
baLimpopo Spatial Planning and Land Use Management Services; Department of Agriculture, Land Reform and Rural Development, Polokwane, South Africa
bDepartment of Geography, Sol Platjie University, Kimberly, South Africa
A R T I C L E I N F O Keywords:
Land cover change Land use management Land Tenure Rural livelihood Subsistence farming
A B S T R A C T
In Thulamela Local Municipality, South Africa, competing land use activities such as urbanisation and subsis- tence farming have accelerated rapid, widespread changes in land use and land cover (LULC) with potential negative impacts on subsistence and small-scale farming, food security, and sustainable rural livelihoods.
Therefore, the aim of the current study was to investigate the decline in land available for subsistence and small- scale farming in the Thulamela Local Municipality. A post-classification comparison approach was performed using three Landsat images from 2005, 2013 and 2020 in order to quantify the spatio-temporal dynamics of LULC in the study area. The land use management system and applicable land use policies were examined to gain an understanding of the factors driving LULC. The results showed a general decline in agricultural land with a general increase in built-up areas. Land under Agricultural Fallow shrank from 26% to 8% with a 69% decline in extent while the extent of Grass reduced from 22% to 16%. The study has shown that the decline in agricultural land and its conversion to built-up areas can be attributed to ineffective land use management system, which is less protective of land for subsistence and small-scale farming in rural areas characterised customary land tenure rights. The land use scheme’s generalisation of vacant and unsurveyed land as agricultural use zone makes it difficult to oppose development on productive agricultural land currently used for subsistence and small-scale farming in rural areas. Therefore, the study recommends that suitable agricultural land or land currently used for subsistence and small-scale farming should be clearly categorised as arable use zone from municipal land use schemes in order to ensure sustainable utilisation and protection of arable land for agricultural purposes.
Measures should also be taken to secure tenure rights for subsistence farmers in order to curb the widespread conversion of agricultural land into built-up areas.
1. Introduction
Globally, rural communities depends heavily on access to land and natural resources to sustain their livelihoods while agricultural use on communal lands is one of the major land uses that supports the liveli- hood of millions of people (Shackleton, 2020). The significant contri- bution of subsistence farming to food security, poverty alleviation, sustainable rural livelihoods as well as supplementing household food supply continues to be acknowledged (Viljoen, 2006; Baiphethi and Jacobs, 2009; Mngqawa et al., 2016). Yet, subsistence farmers in South Africa continue to maintain their livelihoods in adverse conditions such as inadequate access to production resources (Mpandeli and Maponya, 2014), climate change (Ubisi, 2015) and poor access to markets (Von
Loeper et al., 2016). Perhaps the most alarming challenge for subsis- tence farmers in South Africa’s rural communities is access to and ownership of arable land for subsistence farming (Mpandeli and Maponya, 2014; Von Loeper et al., 2016; Shackleton, 2020).
South Africa’s agricultural sector is comprised mainly of two types of farmers: the subsistence farmers largely farming in former homelands/
rural areas; and the large-scale commercial farmers (Kirsten and Van Zyl, 1998). Commercial farmers produce livestock and crops for the market in large quantities whereas subsistence farmers grow crops or raise livestock sufficient for household use while surplus produce are seldomly traded. The term subsistence farming is sometimes used interchangeably with small-scale farming (e.g. Aliber et al., 2005;
Moeletsi et al., 2013). However, Small-scale farmers are farmers who
* Correspondence to: Suit No. 6, Empire Place, 106 Hans van Rensburg Street, Polokwane, 0700.
E-mail address: [email protected] (Z. Lidzhegu).
1 ORCID ID 0000–0002-1219–4389
Contents lists available at ScienceDirect
Land Use Policy
journal homepage: www.elsevier.com/locate/landusepol
https://doi.org/10.1016/j.landusepol.2022.106170
Received 14 September 2021; Received in revised form 17 March 2022; Accepted 23 April 2022
grow subsistence crops on small plots of land and one or more two cash crops relying almost exclusively on family labour (Department of Agri- culture, Forestry and Fisheries, 2012). There are about 39 982 com- mercial farm units in South Africa generating about 95% of the agricultural production while occupying 87% of the total agricultural land with subsistence and small-scale farmers in communal areas pro- ducing on the remaining 13% (Aliber and Hart, 2009). Communal land areas comprise the former homelands and Coloured reserves where land is used for housing, agriculture, and common property resources (Clark and Luwaya, 2017). With about 2.5 million people from 4 million households involved in subsistence farming as a means to supplement household food supply (Gebrehiwet, 2011) farming contributes immensely to rural livelihoods (Tibesigwa and Visser, 2015; Olofsson, 2019) despite the inequitable distribution of the country’s agricultural land resource. The issue of limited access to communal land for subsis- tence farming is further exacerbated by the continued loss of agricultural land through changes in land use. This was evident from a 2012 study conducted by Limpopo Department of Agriculture that reported a decline in agricultural land use because of conversion to urban, mining, and industrial land uses (Limpopo Department of Agriculture, 2012). In South Africa, land use and land cover have been altered considerably since the Native Land Act of 1913, in response to a broad variety of political, social, cultural, and environmental factors (Hoffman, 2014).
Yet, the loss of agricultural land for subsistence and small-scale farming and the links between land use and land cover change, land use man- agement system, land tenure, and food security in rural areas of South Africa continues to be overlooked.
The land use management system in South Africa is governed by national and provincial governments but its policies are effectively implemented at the level of local governments (Nel, 2009). However, land use management policies such as the Township Ordinance of 1986 and the Development Facilitation Act (DFA) of 1996 enforced through town planning schemes (van Wyk, 2010) were only applicable in formally proclaimed municipal areas while land use in rural or communal areas remained poorly regulated through the Subdivision of Agricultural Land Act of 1970, Proclamation No.188 of 1969 (R188), Proclamation No. 293 of 1962 (R 293) and customary laws. Customary law is the written and unwritten rules which have developed from the customs and traditions of communities (Mujuzi, 2020). Most set- tlements/villages in rural areas are informal/unproclaimed and are established in terms of the R188 while formal townships in rural areas (South African Cities Network, 2011) or settlements in land under communal titleship were established in terms of the R293 (Motloung, 2015). With regard to informal settlements/villages established through R188, a system of land tenure which is characterised by the customary laws and the principle of Permission-to-Occupy is enforced (Motloung, 2015) while vacant land is protected by the Subdivision of Agricultural Land Act of 1970. The Subdivision of Agricultural Land Act of 1970 defines and protects agricultural land as any land except formally pro- claimed land or land zoned for any particular use under a town planning scheme. In short, this is the vacant land that hasn’t been subdivided but is available for subdivision if consent is obtained from the Minister of Agriculture thus ensuring the protection of vacant/agricultural land.
However, in terms of R188 and customary laws in rural land, permission to occupy is granted by the traditional authority to an individual to use a particular plot of vacant land but without ownership of the plot (Mpandeli and Maponya, 2014; Israel and Wynberg, 2019). Currently, the Spatial Planning and Land Use Management Act (SPLUMA) of 2013 has abolished the DFA, which aims, among other things, to establish a standard, effective and complete system of spatial planning and land use management in South Africa. Under SPLUMA Chapter 5, Section 24, a single land use scheme shall be adopted for the entire area and land management and regulations shall be introduced in areas which have traditional leaders and rural communities, informal settlements, slums and areas not previously covered by the land-use scheme. SPLUMA places city councils in the Local Government centre, with traditional
authorities as consulted participants in the planning and land use and development management decision making (Mkhize, 2019).
Through land use and land cover (LULC) mapping and analysis, the current study seeks to examine the decline in land available for subsis- tence farming in Thulamela Local Municipality. Conversely, the exam- ination of land use schemes and appropriate legislations will provide an insight into the nature and level of protection for agricultural land for subsistence farming. Globally, rapid increase in population has resulted in rapid alteration in LULC leading to deforestation and transformation of fertile land to built-up environment (Alawamy et al., 2020). There- fore, evaluating LULC change is vitally important for environmental conservation, resource management, land use planning, and sustainable development (Alam et al., 2020; Gudmann et al., 2020). Remote sensing through the analysis of satellite imagery provide an excellent cost-effective and timeously tool for studying LULC change since im- agery are freely available, cover large geographic area, and have high temporal resolution (Fonji and Gregory, 2014; Alam et al., 2020).
2. Material and methods 2.1. Study area
Thulamela Local Municipality in Limpopo Province is one of the four municipalities comprising the Vhembe District Municipality (Fig. 1).
The municipality is predominantly rural with a few numbers of formal towns and large numbers of villages with major concentration of people and economic activities centred around Thohoyandou town. Thulamela Municipality is characterised by high levels of poverty (Musyoki et al., 2016) with its agricultural sector (i.e. commercial and subsistence agriculture) insignificantly contributing about 1% towards formal economy as it generates about 4% of formal employment (Thulamela Local Municipality, 2019). Although elderly women who mostly rely on government old age pension dominate farming in the district (Mngqawa et al., 2016), subsistence farming play an important role in household food supply (Thulamela Local Municipality, 2019). The municipal landscape is dominated by an extensive mountain range called the Soutpansberg which extends across its northern and central parts from west to east (Fig. 1). The Soutpansberg Mountain greatly influences the range of agricultural activities and settlement patterns as it limits access to and between various parts of the municipal area (Thulamela Local Municipality, 2009).
2.2. Material
Table 1 displays characteristics of the Level 1 Landsat Collection utilized in the study and retrieved from the USGS (https://earthexplorer.
usgs.gov/) website. Photos for the study region were picked for the early wet season (November and December) to ensure that images corre- sponded to farming activities such as soil tilting, planting, and germi- nation within the study area. From November to March, the Municipalities of Thulamela receive a large proportion of its precipita- tion while the Inter-Tropical Convergence Zone (ITCZ) moves south (Kabanda, 2004) while planting commonly takes place between November to January (de Janvry and Sadoulet, 2011), with the pre-farming activities of slashing and burning taking place in September/October.
2.3. Methods
2.3.1. Image classification
Raster calculator in ArcMap was used to convert the Landsat level 1 Digital Number (DN) bands to top-of-atmosphere (TOA) reflectance with correction for solar angle using Eq. (1) as detailed by the United States Geological Survey (https://landsat.usgs.gov).
ρλ= (MρQcal+Aρ) ÷sin(θSE) (1)
where ρλis TOA reflectance, Mρ is band-specific multiplicative rescaling factor, Qcal is quantised and calibrated standard product pixel values (DN), Aρis band-specific additive rescaling factor, and θSE is local sun angle.
ArcGIS Pro was used to independently classify the Landsat images using a supervised object-based classification and a maximum likelihood algorithm. Pixel is fused into objects in an object-based image catego- rization, and ’grouping’ is performed according to the sophisticated criteria including form, texture, shade, size, mutual relationships and not just a pixel value. The object-oriented function extraction method is thus a workflow supported by tools encompassing three main fields of functionality: image segments, analytical segmentation, and classifica- tion information. One tool’s data output is an input to the following tools where the purpose is to produce a thematically classified raster dataset with the classes identified in the attribute table, coloured according to the scheme of the training process.
2.3.2. Accuracy assessment
Accuracy evaluation is a crucial aspect of any classification effort so that the resultant data is relevant in the study of change detection. It compares the categorized image to another source of data that is regarded accurate or ground truth data. The ground truth data were derived from Google’s historically high-resolution imagery taken from Google Earth Pro for the accuracy validation of the 2005, 2013 and 2020 LULC map correspondingly The accuracy of the classified images was tested with a classification error matrix which compares ground refer- ence data and the classification results (Lillesand and Kiefer, 2000).
Stratified points were developed and selected for use as reference data in the confusion matrix for the seven land cover classes, resulting in a total of over 250 reference points (Salem et al., 2017; Andualem et al., 2018).
Stratified random technique generates a number of accuracy assessment points proportional to each class region. The ArcGIS "Compute Confu- sion Matrix" tool calculates a confusion matrix including omission er- rors, commission errors and generates a kappa agreement index and overall accuracy between the map and the reference data. These preci- sion rates vary from 0 to 1, where 1 is 100% accurate. The kappa factor is given by:
kappa(K) =Po− Pe 1− Pe
where Po – is the proportion of correctly classified classes; Pe – is the proportion of correctly classified values expected by chance.
The precision of the producer’s accuracy is when the total number of correct pixels inside the category that divide by the number of reference pixels in that category. The accuracy or dependability of the user’s Fig. 1. The location of Thulamela Local Municipality in Limpopo province, South Africa.
Table 1
Landsat data used in the current study.
Imagery Acquisition
Date Path/
Row Bands (µm) Landsat 8
collection 2 level 1
2020–12–11 169/
76 Red (Band 4), near infrared (Band 5), and shortwave infrared 1 (Band 6)
2013–11–06 169/
Landsat 5 TM 76 collection 2 level 1
2005–11–16 169/
76 Red (Band 3), near infrared (Band 4), and shortwave infrared 1 (Band 5)
accuracy is when a pixel classified on a map is likely to represent that class on the ground. Precision of the user’s accuracy is when the total number of accurate pixels in a category are divided by the total number of pixels actually categorized into a category; results in a commission error measurement (Congalton, 1991).
2.3.3. Land cover change matrix
Due to the development of society and the evolution of nature, various land cover types are commonly converted. Change detection on various raster data sets is carried out to further analyse the land type change, often taken in one area at different times, to establish the type, magnitude and position of change (Hardin et al., 2007). The geo- processing capabilities in the ArcGIS Pro 2.7 Change Detection Toolkit enable the detection of the change between raster datasets. The output from change detection is a thematic layer containing information about the type of change that occurred and magnitude. Using the Microsoft Excel Pivot Table function, a land cover transition matrix was created from the attribute table of the thematic layer, which reflected the amount of conversion between various types of land and the intensity of land changes.
3. Results
3.1. Land cover classification
The 2005, 2013 and 2020 satellite images were analysed for land- cover by creating a land-cover map of the area. The classified LULC map of the study area is given in Fig. 2 having seven classes i.e.
Agricultural Fallow, Agricultural Crops, Built-up, Forestry, Grass, Vegetation and Water.
Classification accuracies were assessed from the confusion matrix tables that showed a good classification accuracy with overall accuracy and kappa coefficient value of 88% and 0.85 respectively for the 2005 image, 86% and 0.81 for the 2013 image (Table 2), and 87% and 0.82 for the 2020 image. Despite the overall high classification accuracies across all images, Built-up class showed a significant spectral confusion with Agricultural Crops, Agricultural Fallow, Grass, and Vegetation classes across all images. Agricultural Fallow is simply ground or soil which has been left unplanted for some time while Agricultural Crop land, includes irrigated and rainfed agricultural areas used to produce crops.
3.2. Change detection
Post classification analysis shows significant land use and land cover change between different imagery dates (Table 3). The change in the distribution of land cover types between 2005 and 2013 shows that Built-up land cover class increased from 14% of the total area coverage to 18%, Vegetation increased from 34% to 47% and Agricultural Crops increased from 3% to 6%. Forestry class on the other hand showed the highest increment from 0.9% to 3%, an increase of 233% while the area covered by water increased slightly and Grass land cover showed a slight decline in area coverage between 2005 and 2013. Land cover change between 2013 and 2020 showed a continued trend in an increase in area covered by Built-up land cover class. Built-up class increased by 33%
between 2013 and 2020 even though the highest percentage increase during this period was water class at 80% as seen in Table 3. Area
Fig. 2.Classified maps showing different land use within the study area (2005, 2013 and 2020 Landsat images).
covered by Agricultural Crops increased from 6% in 2013 to 8% in 2020, showing a 33% percent increment while Agricultural Fallow land cover class showed a decrease in area coverage from 10% to 8%. Forestry and Vegetation classes showed a slight decrease from 3% to 1% and 47–43%
respectively between 2013 and 2020. However, much notable changes can be observed between 2005 and 2020. Between 2005 and 2020, major decline with respect to land cover class extent was observed for Agricultural Fallow and Grass, whereas the area covered by Built-up, Vegetation, Agricultural Crops, Forestry and Water classes showed a general increase. Land under Agricultural Fallow shrank from 26% to 8% with a 69% decline in extent while the extent of Grass reduced from 22% to 16%. Built-up area showed a 71% increase in extent from covering 14% of the total municipal area in 2005 to covering 24% in 2020. Vegetation class increased from a share of 34% of the total municipal area in 2005–43% in 2020 while area covered by water increased from 0.3% to 0.9% and area covered by Agricultural Crops increased from 3% to 8% of the total municipal area between 2005 and 2020.
4. Discussion
4.1. Image classification and classification accuracies
The classification results showed a high overall classification accu- racy and kappa coefficient, and this indicate that the classification and ground truthing methods were successful in categorising and quanti- fying land cover classes within the study area. This is because the ac- curacy of at least 85% is required for satisfactory classification results (Soriano et al., 2019) and a kappa coefficient approaching 1 represent a perfect agreement with reference data while a kappa coefficient approaching 0 represent complete randomness (Lillesand et al., 2014).
Despite the overall satisfactory classification results, several Built-up pixels were misclassified mainly due to resemblances in spectral infor- mation with Agricultural Crops, Agricultural Fallow, Grass, and Vege- tation land cover classes. This spectral can be attributed to the similarities in the physical characteristics of land cover types in the study area. The study area is predominately rural with very few towns, townships and roads that are predominately of asphalt material. Roads, streets, driveways, and front yards surfaces in rural settlements within
the study are predominately gravel/dirt while backyards could either be vegetated or used for subsistence farming. As a result, there is high similarity between Built-up class and other land cover classes. There- fore, the misclassification is due to their high complexity and similarity of spectral response patterns, especially in a mixture of pixels with heterogeneous objects (Zha et al., 2003; Sukristiyanti et al., 2007).
4.2. Land use and land cover change
The land use and land cover change trends in the study area can be summed as an overall decline in land under Agricultural Fallow and Grass land cover types, and an increase in land under Built-up, Water, Vegetation, Forestry, and Agricultural Crops classes. The increase in area covered by water in the study area can be attributed to the con- struction and operation of dams, most noticeable the 163 million m3 storage capacity Nandoni Dam which was completed during the 2005/
2006 financial year (South African Government, 2014). The increase in Forestry can be attributed to the thriving timber plantation which is a major land use activity in the south western part of the study area (OABS Development, 2017). The decrease in area covered by Grass and the increase in area covered by dense vegetation can be attributed to plant succession typical of ecosystems. Ecological succession, or plant suc- cession, is the orderly process of one plant community transitioning or
"advancing" to another over time (Pierce et al., 2012). As plant succes- sion progresses, dense vegetation become established. This process that results in an increase in trees and tall shrubs at the expense of grasses has also been observed as the most obvious change in the vegetation of the savanna by Hoffman (2014). However, according to Hoffman (2014) this phenomenon is referred to as bush encroachment in much of the world’s literature and it occurs as result of densification of tall shrubs and trees in areas where they already exist or colonisation of new environment where woody vegetation have not previously occurred.
Although marginal, there is an observed increase in land under Agri- cultural Crops despite the general decline in area under Agricultural Fallow. This can be attributed to the difference in imagery dates be- tween the 2005 and 2020 images such that the images correspond to different farming activities within the study area. The 2005 image was taken in November, a month earlier than the 2020 image that was taken in December. Planting commonly occurs from November to January (de Janvry and Sadoulet, 2011) such that around December, seedlings would have already germinated in some areas and those areas would be classified as Agricultural Crops rather than Agricultural Fallow. Another possible reason for the observed increase in Agricultural Crops could be changing farming practices as an adaptation strategy to climate change/variability (Mpandeli et al., 2015) wherein planting occurs early in the season just after the first rain of the rainy season (Rankoana, 2016).
Table 2
Confusion matrix showing classification accuracy for the 2013 image.
Class Water Built-up Vegetation Grass Agricultural Crops Agricultural Fallow Forestry Total Users Accuracy
Water 10 0 0 0 0 0 0 10 1,00
Built-up 0 30 4 10 0 1 0 45 0,67
Vegetation 0 2 111 1 2 0 0 116 0,96
Grass 0 2 2 37 0 0 0 41 0,90
Agricultural Crops 0 5 0 0 10 0 0 15 0,67
Agricultural Fallow 0 2 0 2 1 19 0 24 0,79
Forestry 0 0 1 0 0 0 9 10 0,90
Total 10 41 118 50 13 20 9 261
Producers
Accuracy 1,00 0,73 0,94 0,74 0,77 0,95 1,00
Kappa statistics 0,82 and overall accuracy 86%
Table 3
Land cover/land use classes and areas in square kilometres (km2).
Land Cover Classes 2005 Statistics 2013 Statistics 2020 Statistics Agricultural Fallow 699,10 (26,44%) 254,97 (9,64%) 206,00 (7,79%) Agricultural Crops 70,81 (2,68%) 155,05 (5,86%) 207,39 (7,84%) Built-up 365,14 (13,81%) 478,75 (18,11%) 625,77 (23,67%) Forestry 24,62 (0,93%) 79,86 (3,02%) 32,49 (1,23%) Grass 582,71 (22,04%) 430,11 (16,27%) 416,06 (15,74%) Vegetation 894,15 (33,82%) 1231,19 (46,57%) 1132,72 (42,85%)
Water 7,18 (0,27%) 13,79 (0,52%) 23,28 (0,88%)
Total 2643,71 2643,71 2643,71
4.3. Decline in land under agricultural fallow and an increase in built-up areas
One factor that can be easily attributed to the decline in agricultural land use is agricultural land abandonment which is pervasive globally and in developing countries (Blair et al., 2018). According to Njwaxu and Shackleton (2019) there has been a global increase in agricultural land abandonment of over 150 million hectors from the 1940′s to 1990′s as increasing number of small-scale farming households are disengaging from arable production. Unfavourable climatic conditions and more modernised youth disinclined to living a marginal agrarian lifestyle (Blair et al., 2018) as well as a general shift of rural livelihoods from being mostly agrarian to increasing contributions from non-agrarian incomes (Njwaxu and Shackleton, 2019) are some of the factors attrib- uted to cropland abandonment. However, despite this global phenom- enon of crop abandonment, OABS Development (2017) found in survey conducted within the study area that none of the interviewed re- spondents reported any abandonment of previously productive lands.
OABS Development (2017) then arrived at an affirmation that produc- tive land in Thulamela Local Municipality is at a premium and is opti- mally utilised by small-scale farmers to a large extent. A recent land cover change study conducted in Dedza District in Malawi found that about 2.7% of what used to be agricultural land in 1991 was converted to built-up environment in 2015 (Munthali et al., 2019). This conversion of agricultural land into built environment was also observed in Lim- popo province by Limpopo Department of Agriculture (2012). Fig. 3 shows that land that was previously used for subsistence farming north
of Tshivhulani (Figure 3a1) and Tshikhudini (Figure 3b1) villages in 2006 were converted to built-up area in 2020 (Figure 3a2 and 3b2). This shows that similar to Munthali et al. (2019) and Limpopo Department of Agriculture (2012), the observed general decline in agricultural land from 2005 to 2020 in Thulamela Local Municipality is as a result of conversion to built-up areas rather than crop abandonment. Regarding crop abandonment, former agricultural land become colonised with dense vegetation through plant succession/bush encroachment over- time (Hoffman, 2014) and this is clearly not the case in Thulamela Local Municipality were former agricultural lands are now residential areas.
4.4. Land use change and land use management practices
The conversion of agricultural land to built-up areas observed in the Thulamela Municipality can be attributed to ineffective land use man- agement practices and policies in South Africa’s rural landscapes. In rural landscapes land is under the custodianship of traditional author- ities and the customary land tenure system is characterised by the principle of permission to occupy. The permission to occupy that is granted by the traditional authority can be given legal status through a Permission-to-Occupy (PTO) certificate issued by the Department of Cooperative Governance, Human Settlement and Traditional Affairs (CoGHSTA) in collaboration with the local municipality. Yet, Spatial Planning and Land Use Management Act of 2013 (SPLUMA) places municipalities at the centre of spatial planning and land use manage- ment within their entire municipal area (Mkhize, 2019) including land under the custodianship of traditional authorities. Municipalities are
Fig. 3. Google Earth maps showing land cover around Tshivhulani village in 2006 (a1) and 2020 (a2) and around Tshikhudi/Dumasi/Tshififi villages in 2006 (b1) and 2020 (b2).
required to develop and adopt a single land use scheme for managing land use within its entire municipal area. However, the Thulamela Local Municipality (2019) land use scheme appears to be less protective of land for subsistence and small-scale farming in rural areas. This is because in rural areas such as Guyuni and Tshiombo villages there is no clear categorisation of land uses (Fig. 4). Any land that is not formally surveyed either as part of a township establishment or rural settlement is regarded as agricultural use zone regardless of the land use activities.
For example the vacant land around Guyuni village (Figure 4a1) is classified under agricultural use zone in terms of the land use scheme (Figure 4a2) while the irrigated agricultural schemes around Tshiombo village (Figure 4b1) are also categorised into agricultural use zone in terms of the land use scheme (Figure 4b2). The agricultural use zone as used in the land use scheme appears to be aligned to agricultural land as defined from the Subdivision of Agricultural Land Act of 1970. This is because according to Thulamela Local Municipality (2019) the protec- tion of productive agricultural land is administered through the Subdi- vision of Agricultural Land Act of 1970. Therefore, any vacant land and land that is not formally surveyed or officially proclaimed within the municipal area is categorised under agricultural use zone and is there- fore available for subdivision provided that consent is obtained from the minister of the department of agriculture. This lack of clear catego- risation of land use zones and the generalisation of vacant and unsur- veyed land in agricultural use zone makes it difficult to oppose development on productive agricultural land. Therefore, the current land use management system makes high potential arable land vulner- able for exploitation and loss through conversion into other land use
types such as built-up areas.
4.5. Access to and protection of agricultural land as means for supporting and uplifting agrarian rural livelihoods
There are several government initiatives that are aimed at addressing some of the challenges that subsistence and small-scale farmers are faced with in South Africa. The Comprehensive Agricultural Support Pro- gramme (CASP) is one of such initiatives that offers a wide range of support services including financial support, purchase of agricultural inputs, infrastructure development, training, and capacity building (Mpandeli et al., 2014). Another interesting initiative for addressing such challenges is the Agri-park programme (OABS Development, 2017). An Agri-park is a networked innovation system of agro-production, processing, logistics, marketing, training, and exten- sion services, located in a District Municipality (Heimann, 2017).
Agri-park is comprised of the Farmer Production Support Unit (FPSU) which is a rural subsistence farmer outreach and capacity building unit that links farmers with markets, and the Agri-hub (AH). The Agri-hub is a production, equipment hire, processing, packaging, logistics, innova- tion and training unit. One of the strategic proposals for supporting and uplifting agrarian rural livelihoods in Thulamela Municipality is to improve integration between agricultural activities and the identified Agri-hub and FPSU through the upgrading and maintenance of linkage of several district routes (Thulamela Local Municipality, 2019). This shows that many efforts have been geared towards addressing some of the challenges facing subsistence and small-scale farmers in order to
Fig. 4.Land use maps for Guyuni and Tshiombo villages with (a) showing the location of the villages within the study area, (a1) showing an aerial image while (a2) shows land use map for Guyuni village, and (b1) showing areal image while (b2) shows land use map around Tshiombo village (Modified from the 2019 Thulamela Local Municipality Land Use Scheme).
support and uplift agrarian rural livelihoods. Yet, little efforts have been geared towards the protection and conservation of agricultural land for subsistence and small-scale farming through land tenure security.
Therefore, the South African government is investing a lot of funds and constructing permanent infrastructure to support agrarian activities that are being practiced on land characterised by insecure tenure in a sense that the majority of subsistence and small-scale farmers in rural areas do not have ownership or legal protection of their farming plots. Currently, the protection of agricultural land is administered through the Subdi- vision of Agricultural Land Act of 1970 (Thulamela Local Municipality, 2019) and this legislation leaves land with high potential for farming vulnerable to conversion into built-up environment. Therefore, in order to protect land for subsistence and small-scale farming and to ensure the successful implementation of programmes or initiative designed to mitigate challenges facing subsistence and small-scale farmers, tenure of land for subsistence and small-scale farming should be formally secured.
Furthermore, agricultural land used or land suitable for subsistence and small-scale farming should be clearly categorised as arable use zone from municipal land use schemes.
5. Conclusion
The current study clearly demonstrated that remote sensing can be an efficient tool for mapping and managing regional natural and agri- cultural resources, and for informing spatial planing and land use management. The findings of this study emphasise the necessity of sat- ellite digital image processing combined with GIS technology for map- ping and identifying LULC changes as well as drivers of change. The study showed a large decrease in agricultural fallow land and a com- parable increase in built-up areas. Ineffective land use management system and policies in South Africa’s rural landscapes can be attributed to the observed widespread conversion of agricultural land to built-up areas in Thulamela Local Municipality. Infrastructure development and urbanisation have undoubtedly cost precious agricultural land resource for economic expansion and may continue to drive agricultural land to the edges of other uses. However, land tenure security and careful management of land for subsistence farming is required to guarantee that this limited agricultural land resource is sustanably uti- lised to the benefits of rural communities. Land tenure security, raising agricultural productivity through support from governement initiatives, as well as better land policies and management system in the face of competing priorities, can help safeguard food security, support, and uplift agrarian rural communities. Policy measures should be taken to secure tenure rights for subsistence farmers in rural areas as to reduce the incidences of conversion of agricultural land for urban purposes.
Although a PTO certificate can have legal status, community members in rural areas rarely apply for PTO certificates and court battles over a plot for subsistence farming may be too costly for a subsistence farmer.
Perhaps priority in terms of securing land tenure for subsistence farming should be given to subsistence and small-scale farming plots targeted for support by government initiatives or in proximity to the Agri-park programme (i.e. Agri-hubs or FPSUs) for example. The Agri-park pro- gramme is one of the example of government initiatives aimed at enhencing agricultural productivity. Securing tenure rights for farming plots targeted by government initiatives such as the Agri-park pro- gramme can ensure the sustainability of subsistence farming through continued support from such initiatives. Conversely, failing to secure land tenure for subsistence and small-scale farming plots targeted by government initiatives such as the Agri-park programme may results in continued conversion of agricultural land to urban areas with potential dire consequences for subsitence farming communities and the Agri- park initiative.
Acknowledgements
The authors are grateful to colleagues from Limpopo Spatial
Planning and Land Use Management Services; Department of Agricul- ture, Land Reform and Rural Development (Malose Kola and Lawulani Baloyi) as well as a colleague from Limpopo Department of Agriculture and Rural Development (Thifhelimbilu Virginia Nemalili) for their valuable comments and inputs.
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