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...

Full description

Bibliographic Details
Main Author: Fox, Sarah-Jane Caroline
Other Authors: Hoffmann, Timm
Format: Others
Language:English
Published: University of Cape Town 2017
Subjects:
Online Access:http://hdl.handle.net/11427/25784
id ndltd-netd.ac.za-oai-union.ndltd.org-uct-oai-localhost-11427-25784
record_format oai_dc
spelling ndltd-netd.ac.za-oai-union.ndltd.org-uct-oai-localhost-11427-257842020-07-22T05:07:50Z 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 University of Cape Town Faculty of Science Department of Biological Sciences
collection NDLTD
language English
format Others
sources NDLTD
topic Conservation Biology
Climate Change
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
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.
author2 Hoffmann, Timm
author_facet Hoffmann, Timm
Fox, Sarah-Jane Caroline
author Fox, Sarah-Jane Caroline
author_sort Fox, Sarah-Jane Caroline
title 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_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_sort analysis of vegetation pattern and its relationship to ndvi data in the namaqualand area, south africa
publisher University of Cape Town
publishDate 2017
url http://hdl.handle.net/11427/25784
work_keys_str_mv AT foxsarahjanecaroline ananalysisofvegetationpatternanditsrelationshiptondvidatainthenamaqualandareasouthafrica
AT foxsarahjanecaroline analysisofvegetationpatternanditsrelationshiptondvidatainthenamaqualandareasouthafrica
_version_ 1719331064740052992