Land degradation in the Limpopo Province, South Africa
Gibson, Donald J. D.
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.
Student Number : 9511039F - MSc Dissertation - School of Animal, Plant and Environmental Sciences - Faculty of Science
Land degradation , Desertification , Rain-use efficiency , Remote Sensing , NDVI , Limpopo Province