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Identifying land suitable for agricultural land reform using GIS-MCDA in South Africa

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Abstract

Land reform is identified as a key tool in fostering development in South Africa. Twenty years after the advent of democracy in South Africa, the land question remains a critical issue for policy makers. Several frameworks have been put in place by the government to identify land that is strategically located for land reform. However, many of these frameworks are not well aligned and not objective in defining strategically located land for land reform and often lead to unsustainable land use management practices. This has hampered the government’s land reform initiative in promoting agricultural land reform and food security. Accordingly, there is a need to develop a decision support tool that facilitates the identification of strategically located land for land reform. This study proposes the use of geographic information systems (GIS) and multi-criteria decision analysis (MCDA) to develop a strategically located land index (SLLI) to identify land suitable for agricultural land reform. Participatory workshops and the group analytical hierarchy process were utilised to identify and weigh criteria used in computing the SLLI. The results indicate that land that is suitable for agricultural land reform is scarce, and there are also competing needs on the highly suitable land for agriculture. The study demonstrates that GIS and MCDA are invaluable tools in facilitating evidence-based decision-making for land reform and sustainable land use management practices. The SLLI is not the panacea to land identification; there is also need to appreciate the contested nature of land in South Africa.

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Notes

  1. Academic experts in GIS; professionals such as agronomists, development economists, crop specialists, livestock specialists, town planners, GIS professionals, environmentalists, agricultural experts, economists from various government departments together with civil society.

  2. Aggregating using an automated algorithm was utilised because it avoids using a moderator or judge who may be biased (Dong and Cooper 2016). Moreover, reaching consensus is almost impossible in the real world; hence, utilising the algorithm by Goepel (2014) ensures consistency and avoids biases.

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Acknowledgements

Sincere thanks goes to Matheri Kangethe, Rebone Tshesane, Eric Makoni, Lerato Segooa and the DRDLR for their input and guidance. This paper was also made possible from funding from University of Johannesburg, Faculty of Engineering and the Built Environment.

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  1. Department of Town and Regional Planning, University of Johannesburg, Johannesburg, South Africa

    Walter Musakwa

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Musakwa, W. Identifying land suitable for agricultural land reform using GIS-MCDA in South Africa. Environ Dev Sustain 20, 2281–2299 (2018). https://doi.org/10.1007/s10668-017-9989-6

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