Invasive Prosopis trees pose significant threats to biodiversity and ecosystem services in
the Northern Cape Province of South Africa. Several estimates have been made of the
spatial extent of alien plant invasion in South Africa. The South African Plant Invaders
Atlas (SAPIA) suggested that about 10 million hectares of South Africa has been
invaded. However, the rate and spatial extent of Prosopis invasion has never been
accurately quantified. The objective of the study is to use Remote Sensing and
Geographic Information System (GIS) techniques to: (i) reveal areas susceptible to
future invasion, (ii) describe the current extent and densities of Prosopis, (iii) to reveal
the spatial dynamics and (iv) establish the extent of fragmentation of the natural
vegetation in the Northern Cape Province.
Image classification products were generated using spectral analysis of seasonal
profiles, various resolution image inputs, spectral indices and ancillary data.
Classification approaches varied by scene and spatial resolution as well as application of
the data. Coarse resolution imagery and field data were used to create a probability
map estimating the area vulnerable to Prosopis invasion using relationships between
actual Prosopis occurrence, spectral response, soils and terrain unit. Multi-temporal
Landsat images and a 500m x 500m point grid enabled vector analysis and statistical
data to quantify the change in distribution and density as well as the spatial dynamics of
Prosopis since 1974. Fragmentation and change of natural vegetation was quantified
using a combined cover density class, calculating patch density per unit (ha) for each
biome
The extent of Prosopis cover in the Northern Cape Province reached 1.473 million
hectare or 4% of the total land area during 2007. The ability of the above mentioned
Remote Sensing and GIS techniques to map the extent and densities of Prosopis in the
Northern Cape Province of South Africa demonstrated a high degree of accuracy (72%).
While neither the image classification nor the probability map can be considered as
100% accurate representations of Prosopis density and distribution, the products provide
use full information on Prosopis distribution and are a first step towards generating more
accurate products. For primary invasion management, these products and the
association of a small area on a map with Prosopis plants and patches, mean that the
management effort and resources are efficiently focused.
Further studies using hyper-spectral image analysis are recommended to improve the classification accuracy of the spatial extent and density classes obtained in this study. / Thesis (M. Environmental Science)--North-West University, Potchefstroom Campus, 2010.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:nwu/oai:dspace.nwu.ac.za:10394/4377 |
| Date | January 2010 |
| Creators | Van den Berg, Elzie Catharina |
| Publisher | North-West University |
| Source Sets | South African National ETD Portal |
| Detected Language | English |
| Type | Thesis |
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