Land degradation in the Limpopo Province, South Africa
Date
2007-02-26T13:25:10Z
Authors
Gibson, Donald J. D.
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Abstract
An estimated 91 % of South Africa’s total land area is considered dryland and susceptible to
desertification. In response, South Africa has prepared a National Action Programme to
combat land degradation, and this requires assessment and monitoring to be conducted in a
systematic, cost effective, objective, timely and geographically-accurate way. Despite a
perception-based assessment of land degradation conducted in 1999, and a land-cover
mapping exercise conducted for 2000/2001, there are few national scientifically rigorous
degradation monitoring activities being undertaken, due largely to a lack of objective,
quantitative methods for use in large-scale assessments. This study therefore tests a satellitederived
index of degradation for the Limpopo Province in South Africa, which is perceived to
be one of the most degraded provinces in the country. The long-term average maximum
normalized difference vegetation index (NDVI), calculated from a time series (1985-2004) of
NOAA AVHRR satellite images, as a proxy for vegetation productivity, was related to water
balance datasets of mean annual precipitation (MAP) and growth days index (GDI), using both
linear and non-linear functions. Although the linear regressions were highly significant
(p<0.005), a non-linear four parameter Gompertz curve was shown to fit the data more
accurately. The curve explained only a little of the variance in the data in the relationship
between NDVI and GDI, and so GDI was excluded from further analysis. All pixels that fell
below a range of threshold standard deviations less than the fitted curve were deemed to
represent degraded areas, where productivity was less than the predicted value. The results
were compared qualitatively to existing spatial datasets. A large proportion of the degraded
areas that were mapped using the approach outlined above occurred on areas of untransformed
savanna and dryland cultivation. However the optical properties of dark igneous derived soils
with high proportions of smectitic minerals and therefore low reflectance, were shown to
lower NDVI values substantially. Overall, there was an acceptable agreement between the
mapped degradation and the validation datasets. While further refinement of the methodology
is necessary, including a rigorous field-based resource condition assessment for validation purposes, and research into the biophysical effects on the NDVI values, the methodology
shows promise for regional assessment in South Africa.
Description
Student Number : 9511039F -
MSc Dissertation -
School of Animal, Plant and Environmental Sciences -
Faculty of Science
Keywords
Land degradation, Desertification, Rain-use efficiency, Remote Sensing, NDVI, Limpopo Province