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Data-driven methods for the extraction, grouping and application of terroir units
Thesis (MSc)--Stellenbosch University, 2026.
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| Format: | Thesis |
| Language: | English |
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Stellenbosch : Stellenbosch University
2026
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| _version_ | 1867613911352606720 |
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| access_status_str | Open Access |
| author | West, Jonathan Robert |
| author2 | Van Niekerk, Adriaan |
| author_browse | Van Niekerk, Adriaan West, Jonathan Robert |
| author_facet | Van Niekerk, Adriaan West, Jonathan Robert |
| author_sort | West, Jonathan Robert |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MSc)--Stellenbosch University, 2026. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/135558 |
| institution | Stellenbosch University (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:43:40.048Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/135558 Data-driven methods for the extraction, grouping and application of terroir units West, Jonathan Robert Van Niekerk, Adriaan Southey, Tara Stellenbosch University. Faculty of Science. Dept. of Computer Science. Thesis (MSc)--Stellenbosch University, 2026. West, J. R. 2026. Data-driven methods for the extraction, grouping and application of terroir units. Unpublished masters thesis. Stellenbosch: Stellenbosch University [online]. Available: https://scholar.sun.ac.za/items/6c262a4e-51ab-47ac-8bc5-324647be1d76 Data-driven methods for the delineation of viticultural zones have become increasingly relevant, necessitated by the transition from subjective, expert-based methods to objective and transparent methods. The use of subjective expert knowledge to inform zone boundaries can lack empirical evidence, making the justification of zone boundaries challenging. Modern methods derive zone boundaries based on the analysis of factors of the natural environment (climate, terrain, and soil) that constitute terroir. The first experiment aimed to develop a method for the delineation of basic terroir units. A stepwise method was developed in which the multiresolution segmentation (MRS) and spectral difference segmentation (SDS) algorithms were used to segment slope and height above nearest drainage (HAND) into terroir representative minimum mapping units. These units were used as the foundation for the following set of experiments. The second set of experiments aimed to identify the most effective method for grouping the basic terroir units derived from the first experiment. Overall MRS outperformed SDS and both the k-means and hierarchical clustering. MRS produced the most spatially uniform and practical zones. Between the two clustering algorithms, hierarchical clustering produced less fragmented results than k-means, and higher Moran’s Index scores. Data-driven zoning can reduce expert subjectivity, providing empirical evidence to support decision-making for legislators and producers regarding geographic indication (GI) boundaries. The data-driven methods presented in this research provide new approaches to zoning by demonstrating the value of object-based image analysis (OBIA), finding it to be a highly effective alternative to pixel-based or vector overlay zoning methods. Further development of these methods could support viticultural zoning in South Africa, ensuring the sustainability of the Wine of Origin scheme in the context of a changing climate. Masters 2026-04-01T12:33:31Z 2026-04-01T12:33:31Z 2026-03 Thesis https://scholar.sun.ac.za/handle/10019.1/135558 en Stellenbosch University 173 pages application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | West, Jonathan Robert Data-driven methods for the extraction, grouping and application of terroir units |
| title | Data-driven methods for the extraction, grouping and application of terroir units |
| title_full | Data-driven methods for the extraction, grouping and application of terroir units |
| title_fullStr | Data-driven methods for the extraction, grouping and application of terroir units |
| title_full_unstemmed | Data-driven methods for the extraction, grouping and application of terroir units |
| title_short | Data-driven methods for the extraction, grouping and application of terroir units |
| title_sort | data driven methods for the extraction grouping and application of terroir units |
| url | https://scholar.sun.ac.za/handle/10019.1/135558 |
| work_keys_str_mv | AT westjonathanrobert datadrivenmethodsfortheextractiongroupingandapplicationofterroirunits |