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An analysis of vegetation pattern and its relationship to NDVI data in the Namaqualand area, South Africa
The Namaqualand area in the North Western Cape, South Africa is unique in comparison to other similar semi-arid areas of the world. It has a high biodiversity and endemism and is consequently an area of interest for a growing number of conservation initiatives. Climate plays an important role in inf...
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| Format: | Thesis |
| Language: | English |
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Department of Biological Sciences
2017
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| _version_ | 1867613302421454848 |
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| access_status_str | Open Access |
| author | Fox, Sarah-Jane Caroline |
| author2 | Hoffmann, Timm |
| author_browse | Fox, Sarah-Jane Caroline Hoffmann, Timm |
| author_facet | Hoffmann, Timm Fox, Sarah-Jane Caroline |
| author_sort | Fox, Sarah-Jane Caroline |
| collection | Thesis |
| description | The Namaqualand area in the North Western Cape, South Africa is unique in comparison to other similar semi-arid areas of the world. It has a high biodiversity and endemism and is consequently an area of interest for a growing number of conservation initiatives. Climate plays an important role in influencing the phenology and growth of the vegetation in the area. Remote sensing techniques were used to reveal the vegetation patterns in the greater Namaqualand area and to relate them to climatic variables. To do this we used the normalised difference vegetation index (NDVI) to relate biomass to altitude, rainfall and vegetation type. Each vegetation type in the area had a unique temporal signature and the climatic variables influencing the summer rainfall and winter rainfall vegetation types differed significantly from each other. Mean annual NDVI was significantly correlated to precipitation and potential evapotranspiration (PET) (r = 0.60, -0.63 respectively). A multiple regression model explained 52% of the variance when Mean Annual NDVI was related to climatic variables. Mean NDVI in August (the month of maximum NDVI in most of Namaqualand) was significantly related to PET and the current plus two previous months of precipitation (r = -0.72 and 0.74 respectively). A multiple regression model for mean NDVI in August and climatic variables explained almost 58% of the variance. The results suggest that NDVI can be used successfully as a measure of growth and phenology in the Namaqualand area and that NDVI could be used in climate models, drought prediction, desertification predictions and a number of other applications in the future. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/25784 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:33:59.204Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| publisher | Department of Biological Sciences |
| publisherStr | Department of Biological Sciences |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/25784 An analysis of vegetation pattern and its relationship to NDVI data in the Namaqualand area, South Africa Fox, Sarah-Jane Caroline Hoffmann, Timm Hoare, David Conservation Biology Climate Change The Namaqualand area in the North Western Cape, South Africa is unique in comparison to other similar semi-arid areas of the world. It has a high biodiversity and endemism and is consequently an area of interest for a growing number of conservation initiatives. Climate plays an important role in influencing the phenology and growth of the vegetation in the area. Remote sensing techniques were used to reveal the vegetation patterns in the greater Namaqualand area and to relate them to climatic variables. To do this we used the normalised difference vegetation index (NDVI) to relate biomass to altitude, rainfall and vegetation type. Each vegetation type in the area had a unique temporal signature and the climatic variables influencing the summer rainfall and winter rainfall vegetation types differed significantly from each other. Mean annual NDVI was significantly correlated to precipitation and potential evapotranspiration (PET) (r = 0.60, -0.63 respectively). A multiple regression model explained 52% of the variance when Mean Annual NDVI was related to climatic variables. Mean NDVI in August (the month of maximum NDVI in most of Namaqualand) was significantly related to PET and the current plus two previous months of precipitation (r = -0.72 and 0.74 respectively). A multiple regression model for mean NDVI in August and climatic variables explained almost 58% of the variance. The results suggest that NDVI can be used successfully as a measure of growth and phenology in the Namaqualand area and that NDVI could be used in climate models, drought prediction, desertification predictions and a number of other applications in the future. 2017-10-25T08:28:51Z 2017-10-25T08:28:51Z 2003 2017-02-23T07:23:05Z Bachelor Thesis Honours BSc (Hons) http://hdl.handle.net/11427/25784 eng application/pdf Department of Biological Sciences Faculty of Science University of Cape Town |
| spellingShingle | Conservation Biology Climate Change Fox, Sarah-Jane Caroline An analysis of vegetation pattern and its relationship to NDVI data in the Namaqualand area, South Africa |
| thesis_degree_str | Bachelor's / Honours |
| title | An analysis of vegetation pattern and its relationship to NDVI data in the Namaqualand area, South Africa |
| title_full | An analysis of vegetation pattern and its relationship to NDVI data in the Namaqualand area, South Africa |
| title_fullStr | An analysis of vegetation pattern and its relationship to NDVI data in the Namaqualand area, South Africa |
| title_full_unstemmed | An analysis of vegetation pattern and its relationship to NDVI data in the Namaqualand area, South Africa |
| title_short | An analysis of vegetation pattern and its relationship to NDVI data in the Namaqualand area, South Africa |
| title_sort | analysis of vegetation pattern and its relationship to ndvi data in the namaqualand area south africa |
| topic | Conservation Biology Climate Change |
| url | http://hdl.handle.net/11427/25784 |
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