DSpace Collection:

Mitigating health problems associated with AMD in South Africa

Thu, 01 Mar 2012 00:00:00 GMT

Title: Mitigating health problems associated with AMD in South Africa Authors: Schachtschneider, K Abstract: Acid mine drainage (AMD) is a serious threat to water quality in South Africa. Questions are being asked to South African government leaders as to what they are doing to mitigate the effects that South Africa’s mining industry is having on communities’ water supply and the water table. The CSIR has developed a novel process to reclaim high-quality precipitated calcium carbonate (PCC) from calcium-rich industrial solid waste. Calcium carbonate can be used to prevent AMD from becoming too acidic, as it has the effect of lowering water's pH level. Description: Copyright: 2012 Malnor Publications. This is an ABSTRACT ONLY. The definitive version is published in Government Digest, Vol. 31 (9,)pp 28-29

Relevance of new multispectral imagery for assessing tropical forest disturbance: RapidEye and WorldView-2

Thu, 01 Nov 2012 00:00:00 GMT

Title: Relevance of new multispectral imagery for assessing tropical forest disturbance: RapidEye and WorldView-2 Authors: Cho, MA; Ramoelo, AI; Mutanga, O; Van Deventer, H; Debba, P; Mathieu, R Abstract: The aims of this study were to assess utility of RapidEye imagery for predicting leaf nitrogen concentration and evaluate the effects of forest fragmentation on leaf nitrogen distribution in the Dukuduku forest, KwaZulu Natal, South Africa. RapidEye and WorldView-2 images were acquired for the study area. Leaf nitrogen concentration was accurately (R2 = 0.52, p < 0.05) estimated using the MERIS terrestrial vegetation index (MTCI) derived from the RapidEye image. Land cover types were accurately classified (overall accuracy = 85%) using WorldView-2 imagery. Differences in leaf nitrogen concentration between land cover types were then analysed. Remnant forest patches showed higher leaf nitrogen than grassland patches in the degraded landscape. In conclusion, foliar nitrogen can be mapped at peak productivity using RapidEye sensor. Forest fragmentation significantly affects leaf nitrogen concentration. Description: 9th International Conference of the African Association of Remote Sensing and the Environment, El Jadida, Morocco, 29 October-2 November 2012

The relationship between fog, floods, groundwater and tree growth along the lower Kuiseb River in the hyperarid Namib

Wed, 01 Dec 2010 00:00:00 GMT

Title: The relationship between fog, floods, groundwater and tree growth along the lower Kuiseb River in the hyperarid Namib Authors: Schachtschneider, K; February, EC Abstract: There is a growing demand for increased water abstraction from ephemeral rivers such as the Kuiseb in western Namibia. Studies in the 1980.s recorded mortality rates of the most common riparian tree species in a prolonged drought from 1979 to 1984. These results show that mortality for the three species differed considerably with 16 % mortality for Acacia erioloba, 39 % for Faidherbia albida and 75 % for Tamarix usnoides. Here we determine the water sources and rooting strategy of three age groups of the three most common riparian tree species growing along the Kuiseb River using stable hydrogen and oxygen isotope analysis. We do this to better understand the relationship between germination and establishment of trees along river courses in hyperarid western Namibia. A secondary objective is to determine whether the mortality rates recorded in the drought in the 1980.s may be related to rooting strategy. We use a linear mixing model approach (IsoSource) to quantify probable contributions of multiple water sources to tree water uptake. Our results show that none of the tree species in this study use fog water. Rather, all of the trees are reliant on a seasonally fluctuating combination of groundwater, shallow soil water and deep soil water. All of these water sources are directly reliant on regular recharge from annual flood events. Our results also show that the mortality rates recorded in the early 1980.s need not necessarily relate to rooting depth or water source but that there may be a combination of possible causes including root growth and structure. If predictions for increased water abstraction and global climate change are realized then the vegetation structure along ephemeral river courses in Namibia will be seriously threatened. Description: Copyright: 2010 Elsevier. This is an ABSTRACT ONLY. The definitive version is published in Journal of Arid Environments, vol. 74(12), 1632-1637

Comparing parametric and non-parametric classifiers for remote sensing of tree species across a land use gradient in a Savanna landscape

Thu, 01 Nov 2012 00:00:00 GMT

Title: Comparing parametric and non-parametric classifiers for remote sensing of tree species across a land use gradient in a Savanna landscape Authors: Cho, MA; Naidoo, L; Mathieu, R; Asner, GP; Ramoelo, A Abstract: Several classification techniques have been used to map vegetation communities or land cover types using remote sensing data including maximum likelihood (ML), discriminant analysis and spectral angle mapper classifiers. ML classifier is a commonly used supervised classification method with conventional multispectral data that considers both first order variations (e.g. mean values) and second order variations (e.g. covariance matrices). However, there is a limitation with the application of the ML classifier in situations of high within-species variability. The objective of this study is to ascertain which classification techniques are suitable for classification of savanna tree species across a land-use gradient. Eight savanna tree species were classified for two sites in the vicinity of the Kruger National Park, South Africa using two parametric (ML and Mahalanobis distance classifiers) and three non-parametric classifiers (spectral angle mapper (SAM), artificial neural networks (ANN) and Random Forest (RF)). The spectral data used consisted of 8 WorldView-2 multispectral bands simulated from 72 VNIR bands image acquired over the study areas using the Carnegie Airborne Observatory (CAO) system. With the exception of SAM, the nonparametric classifiers provided higher classification accuracies (RF = 78%, ANN = 75%, SAM = 36%) when compared to the parametric classifiers (ML = 65%, Mahalanobis distance = 68). This study moves remote sensing closer towards classification of savanna tree species over large areas. Description: 9th International Conference of the African Association of Remote Sensing and the Environment, El Jadida Morocco, October 29 to November 2, 2012