Thesis (MNutr (Human Nutrition))--University of Stellenbosch, 2006. / INTRODUCTION: The study investigated dietary intake, physical activity and risk for chronic diseases of lifestyle (CDL) among employees at a South African open-cast diamond mine. OBJECTIVES: The aim of the study was to determine the habits and barriers to a healthy lifestyle in order to determine the need for workplace interventions at De Beers Venetia Mine (DB-VM) to decrease the risk for CDL and optimise employee wellness. DESIGN: An analytical, cross-sectional, observational study. SAMPLING: A representative proportional stratified sample of 88 permanent employees at DB-VM was randomly selected to participate in the study. The sample was stratified according to work-shift configuration and occupational category. Permanent employees were limited to subjects with at least six months employment at DB-VM. Temporary employees and contractors were excluded from the sample. METHODS: Subjects were required to complete a validated self-administered sociodemographic-, meal frequency- and physical activity questionnaire. A validated quantified food frequency questionnaire was administered by the investigator. Anthropometric measurements including weight, height and waist circumference were performed by the investigator. RESULTS: The study documented a high prevalence of obesity among female (45%) and male (32%) employees. A total energy intake above the Estimated Energy Requirement (EER) was found in 38% of males and 64% of female subjects. Fourty eight percent of males and 64% of female subjects exceeded the Acceptable Macronutrient Distribution Rate (AMDR) for total fat intake, while the mean saturated fatty acid (SFA) intake was above the recommendation of less than 10% of total energy intake. An inadequate fibre intake was observed for 87% of males and 55% of female subjects. Folate intakes below the Estimated Average Requirement (EAR) were found in 62% male and 82% of female subjects. A “low active” physical activity level (PAL) was found in 91% of females and 67% of professionals. Significantly more females (p=0.01) and professionals (p=0.00005) demonstrated a “low active” PAL compared to males and other occupational categories. Work-related barriers to a healthy lifestyle such as long working hours, work demands, a long commute and working shifts contributed to skipping of meals and prevention of physical activity participation among employees. CONCLUSION: The study demonstrated a high prevalence of overweight and obesity among employees characterised by high fat and inadequate fibre intakes, increasing the risk for CDL. Work-related barriers contributed to an unhealthy lifestyle and specific interventions at the workplace would appear necessary to decrease the high prevalence of obesity and risk for CDL. RECOMMENDATIONS: Wellness interventions should be introduced at DB-VM to improve the health and well-being of employees.

There is a growing concern from government, communities, civil society and mining companies on the sustained development of the impact of mining on communities and the benefits of mineral development. Communities are more vocal in expressing their expectations for benefits and on the other hand mines are concerned about profits and maintaining a social licence to operate. This study critically evaluates the impact mining has on socio-economic development in mining communities. The focus area of the study is the West Rand District Municipality in Gauteng Province, South Africa. The ‘impact’ refers to the mine’s contribution to infrastructure development and poverty reduction projects in areas where the mine is operating and sourcing labour from. Forecasts for better performance in the future will be assessed. Issues such as community consultation, identification of projects, development forums, the Integrated Development Plan (IDP) and partnerships are addressed. The literature was reviewed from existing national and international research on the topic. The study starts from two assumptions. The first is that minerals are potentially a great resource of wealth for poor countries. The second assumption is that minerals have the potential to benefit the local population through the creation of indirect employment, skills transfer, enhancing the capacity of health and education services, improved infrastructure and small and medium business opportunities. Poverty levels are viewed on a national and international scale. The study reveals problems, with existing approaches, on mine community development. It concludes that the impact of mining on infrastructure development and poverty reduction projects can be huge, but only if a variety of demanding preconditions are met. The study concludes that the reality of mineral led development in mine communities has not lived up to a roaring promise.

Mining industry has been identified as the main sustenance of the South African economy, however the negative impacts of the industry on the ecological systems cannot be over emphasized due to the released waste which is mostly heavy metals into the environment. The study evaluated six heavy metal (A1, Cu, Fe, Ni, Pb and Cr) contents in a tailings dam from a specific mine site. Two sets of samples for the investigation were measured, that is, one in year 2012 and the other in year 2013. In the year 2012, the sample set was only taken at a distance profile of 500 meters from the foot of the dam, whereas the sample set taken in the year 2013 was for the 500 and 1500 meter distance profiles from the foot of the dam. The year 2012 and 2013 sample sets for the 500m distance profile were sampled very similarly to each other. A kilogram of each sample was taken as per grid format. The samples at varied depths were taken at 0-cm depth for the top layer, 20cm depth for the second layer, and 30cm depth for the third layer. The samples for the surface varied distance were taken at 1 m, 2m, 3m, and 4m away from each 500m and 1500 sampling points. The 2012 samples were analysed using characterization methods namely ICP MS and The 2013 samples were analysed using the ICP OES. The comparison of the field results for the six heavy metals studied (A1, Fe, Pb, Cu, Ni and Cr) was performed using statistical analytical methods, namely ANOVA. The statistical analysis results for heavy metals (A1, Fe, Pb, Cu, Ni and Cr) from sample and 2013 revealed that the group means are not significantly different from each other which means that there is no significant difference in (A1, Fe, Pb, Cu, Ni and Cr) concentrations with respect to both depth and distance. The observations from both 2012 and 2013 indicate the results of the samples are in agreement. In addition, the comparative average concentrations of the three results obtained reach the same conclusion that the tailing dam probably does not introduce considerable or significant amounts of these metals (A1, Fe, Pb, Cu, Ni and Cr) into the surrounding soils. / Chemical Engineering / M. Tech. (Chemical Engineering)

Thesis (MAud)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: In developing countries, like Namibia, there is limited data pertaining to the number of individuals with hearing loss and its associated factors. This study aimed to determine the prevalence of potential hearing loss in Namibian Class A mines and to describe the extrinsic and intrinsic factors associated with hearing loss. A cross-sectional design was utilised and data were collected from 132 respondents (mining employees) from five different Class A mines throughout the country. A questionnaire and a retrospective review of respondents’ medical records were utilised to determine the risk factors. The most recent audiogram found in the respondents’ records was used to determine the presence of potential hearing loss. Three definitions of potential hearing loss were used in this study and included all major frequency hearing loss (AFHL), high frequency hearing loss (HFHL) and low frequency hearing loss (LFHL). Potential hearing loss was identified when the pure tone average (PTA) of 0.5, 1, 2, & 4kHz, 0.5, 1 & 2kHz and 4 & 8kHz respectively was greater than 25dBHL in either one or both ears. Chi-square measurements or, where necessary, Fisher’s exact tests, as well as Odds Ratios were used for the analysis of data. In general a significance level of 5% was applied for all analyses. Results indicated the prevalence of potential hearing loss in Namibian mining employees to be 27% and that both extrinsic and intrinsic factors were associated with hearing loss. The extrinsic factors significantly associated with potential hearing loss were both occupational and medical. The occupational factors found to be significant were the number of years employed in whole life >10 years (p=0.012; OR=3.1, 95% CI=1.3-7.9), the number of years employed in current job > 10 years (p=0.01; OR=3.9, 95% CI1.7-8.8) and the non-availability of formal training in prevention of hearing loss (p=0.022; OR=0.3, 95% CI (0.1-0.9). Diabetes was the sole significant extrinsic medical factor (p=0.035, OR=5, 95% CI 1.1-22.1). The only intrinsic factor which was found to be significantly associated with hearing loss was Age, specifically being older than 40 years (p=0.002; OR=3.5, 95% CI 1.6-7.8) and 50 years (p=0.001, OR=5.5, 95% CI1.9-15.8). A multiple logistic regression model of all significant factors found that only no formal training of prevention of hearing loss was found to be significant in the presence of all other factors (p=0.036, OR=0.036, 95% 0.1-0.92). Findings from this study suggest that multiple factors may be associated with potential hearing loss and not just the exposure to hazardous occupational conditions. Recommendations for future research and clinical practice should, therefore, include thorough investigations into the aetiology of hearing loss. As this study focused on Class A mines, it is recommended that future research be conducted in other mines that are not categorised as Class A mines. Keywords: prevalence, extrinsic factors, intrinsic factors, extrinsic occupational factors, extrinsic social factors, extrinsic medical factors, potential hearing loss, mining industry, Class A mine, Namibia. / AFRIKAANSE OPSOMMING: In ontwikkelende lande, soos Namibië, is daar beperkte data met betrekking tot die aantal individue met gehoorverlies en sy verwante faktore. Hierdie studie het gepoog om die voorkoms van gehoorverlies in Namibiese Klas A myne te bepaal en die ekstrinsieke en intrinsieke faktore wat verband hou met potensiale gehoorverlies te beskryf. 'n Deursnee-ontwerp is gebruik en data is ingesamel uit 132 respondente (mynbou werknemers), uit vyf verskillende Klas A myne regdeur die land. 'n Vraelys en 'n retrospektiewe oorsig van die respondente se mediese rekords is gebruik om die risiko faktore te bepaal. Die mees onlangse oudiogram wat in die respondente se rekords gevind is, is gebruik om die teenwoordigheid van potensiale gehoorverlies te bepaal. Drie definisies van potensiale gehoorverlies is gebruik in hierdie studie, ingesluit al die groot frekwensie gehoorverliese (AFHL), hoë frekwensie gehoorverlies (HFHL) en 'n lae frekwensie gehoorverlies (LFHL). ‘n Gehoorverlies was teenwoordig wanneer die suiwer toon gemiddelde (PTA van 0.5 , 1 , 2, & 4kHz , 0.5, 1 & 2kHz en 4 & 8kHz onderskeidelik , groter was as 25dBHL in een of albei ore. Chi -square metings of, waar nodig, Fisher se presiese toetse, asook kans verhoudings is gebruik vir die ontleding van data. In die algemeen is 'n beduidendeidsvlak van 5% gebruik en toegepas vir al die ontledings. Resultate het aangedui die voorkoms van gehoorverlies in Namibiese mynbouwerknemers tot 27 % was en dat beide ekstrinsieke en intrinsieke faktore ‘n verband toon met potensiaal gehoorverlies. Die ekstrinsieke faktore wat ‘n beduidende verband getoon het met gehoorverlies was albei beroeps- en mediese faktore. Die beroepsfaktore wat betekenisvol was, was die aantal jare diens in hele lewe > 10 jaar ( p = 0,012 ; OR = 3.1 , 95 % CI = 1.3-7.9) , die aantal jare in huidige pos> 10 jaar diens (p = 0,01 ; OF = 3.9 , 95 % CI1.7-8.8 ) en die onbeskikbaarheid van formele opleiding in die voorkoming van potensiaal gehoorverlies (p = 0,022 ; OF = 0,3 , 95 % CI ( 0,1-0,9 ). Diabetes was die enigste beduidende ekstrinsieke mediese faktor (p = 0,035 , OR = 5 , 95 % CI 1,1-22,1 ). Die enigste intrinsieke faktor watbeduidend was en verband hou met gehoorverlies was ouderdom, spesifiek om ouer as 40 jaar ( p = 0,002 ; OF = 3.5 , 95 % CI 1,6-7,8 ) en 50 jaar ( p = 0.001 , OR = 5.5 , 95 % CI1.9-15.8 ) te wees. 'n Veelvuldige regressie model van alle beduidende faktore het bevind dat slegs geen formele opleiding in die voorkoming van gerhoor verlies beduidende was in die teenwoordigheid van al die ander faktore ( p = 0,036 , OR = 0,036 , 95 % 0,1-0,92 ) . Bevindinge van hierdie studie dui daarop dat verskeie faktore geassosieer kan word met gehoorverlies en nie net die blootstelling aan gevaarlike beroepstoestande nie. Aanbevelings vir toekomstige navorsing en kliniese praktyk moet dus 'n grondige ondersoek na die etiologie van gehoorverlies uitvoer. Aangesien hierdie studie gefokus het op die Klas A- myne , word dit aanbeveel dat toekomstige navorsing gedoen word in ander myne wat nie gekategoriseer is as Klas A myne nie. Sleutelwoorde: Voorkoms, ekstrinsieke faktore, instrinsieke faktore, ekstrinsieke beroepsfaktore, ekstrinsieke sosiale faktore, ekstrinsieke mediese faktore, potensiale gehoorverlies, Klas A myn, Namibië.

Thesis (MBA)--Stellenbosch University, 2001. / Some digitised pages may appear illegible due to the condition of the original hard copy / ENGLISH ABSTRACT: The decision to make equipment replacements has a major influence on the competitiveness of any business. A company like Iscor recently spent approximately one billion Rand to modernise its fleet of equipment at various centres. This report presents a holistic approach to the issue of equipment replacement decision-making. It contends that equipment replacement decisions are not isolated incidents that occur by chance. In fact, the whole process is an integral part of the various processes in the business. This ranges from the influence on the strategy, through to issues such as production planning, maintenance, staffing, financial planning and so on. The role of the replacement decision in each of these elements are discussed and elaborated on. The report goes on to review the various models available in the industry and discusses their advantages and disadvantages. Thus ensuring a clear understanding of the differences in the approaches. The report attempted to propose a method that is relatively straight forward and in terms of application lends itself to the practical mining man. The proposed models are then used to complete a relatively simple example. The example was primarily aimed at showing the elements of the application and certainly not the full extent of the model. / AFRIKAANSE OPSOMMING: Die uitvoer van toerusting vervanging_sbesluite kan 'n dramatiese invloed op die mededingendheid van enige besigheid hê. 'n Maatskappy soos Iscor het onlangs 'n bedrag van ongeveer een biljoen Rand gespandeer om hul vloot van toerusting op verskeie sentrums te vervang. Die verslag stel 'n alles omvattende benadering tot die kwessie van toerusting vervangingsbesluitneming voor. Die verslag gaan voort om voor te stel dat die vervangingsbesluit nie iets is wat toevallig geneem moet word nie. Inteendeel dit is 'n integrale deel van al die verskeidenheid besigheidsprosesse. Die verslag bespreek die verskeidenheid modelle beskikbaar en brei uit oor die voor - en- nadele van elk. Die bespreking verseker dat die leser 'n duidelike beeld kry oor die toepaslikheid van die verskeie modelle. Dit gaan voort om 'n praktiese model voor te stel wat redelik maklik is om aan te wend. Die model word dan toegepas op 'n eenvoudige voorbeeld.

Thesis (MBA)--Stellenbosch University, 2007. / ENGLISH ABSTRACT: Purchasing strategies impact on the value added to operations by the items included in the specific purchasing strategy. In mechanised mining operations the mining equipment plays a significant role in the production process as it is the primary production tools. This study reviews literature on the application of buyer-supplier collaboration to purchasing strategies in order to improve the value added to operations and focus on mining equipment purchasing. Most authors agree that the origin of this type of relationship is the adoption of the production management concept of Just-in-Time. Models for buyer supplier collaboration include one dimensional models such as the Traditional and Advanced Supply Management model, Models on the automotive industry, and Supplier partnerships. The one dimensional models mainly compare traditional market type supplier relationships to advanced partnership or relational type relationships. The models reviewed also include multi-dimensional models such as the portfolio management models and the strategic supplier segmentation model. These multidimensional models propose the adoption of a variety of supplier management models based on certain contextual parameters relating to the purchase and expands on the one dimensional models. The benefits of buyer-supplier collaboration include reduced inventory, increased inventory turnover, reduced scrap, increased quality, reduced costs, improved delivery reliability, design and productivity, reductions in lead time, and additional effort from suppliers. The risks associated with buyer-supplier collaboration include significant resource requirements, lack of support from suppliers, shifting of inventory, industry type exclusivity, higher switching costs, and increase in supplier's power. Buyer-supplier collaboration has certain requirements to be successful. These include a fundamental change in the purchasing strategy relating to supplier selection criteria, number of sources and time horizon, multi-dimensional evaluations, a move to single-sourcing and long term relationships. The development of buyer-supplier collaboration is dependant on similarity in industry and technology, prior experiences change, effective communication and information sharing, and experiential learning. Other success factors include two-way information sharing, top management support, shared goals, early communication to suppliers of specification changes or new products, suppliers adding distinctive value, total quality management initiatives and Just-in-time initiatives. The models for buyer-supplier collaboration form the basis of most discussions on implementation. The main implementation guidelines reviewed include the implementation of operational links relating to design, logistics and quality. The more complete implementation models include the model for Five phases in the development and evolution of purchasing partnerships. The most complete models are the portfolio management models to supplier relationship management which includes contextual analysis as well as relationship analysis and implementation. Portfolio management models were found to be the most applicable to application in industries other than manufacturing. The final part of this study applies the theory to mining equipment purchases. The theory and application of buyer-supplier collaboration were developed for the manufacturing industry and therefore several issues arise in the application of these approaches in the mining industry. No significant literature was found relating to the application of buyer-supplier collaboration to mining equipment purchasing strategies. Applying the portfolio management approach to the mining equipment purchase and suppliers, reveals that mining equipment purchases are strategic in nature and buyer-supplier collaboration is the applicable management approach. Several areas of possible value add were identified and include acquisitions costs, replacement parts, efficiency and productivity of mining equipment. The initial review of the implementation of buyer-supplier collaboration at a mining operation reveals early performance improvements in terms of service levels. The review also indicates the existence of some of the risks associated with this type of relationship, mainly the shifting of inventory to the supplier.

Mining industry has been identified as the main sustenance of the South African economy, however the negative impacts of the industry on the ecological systems cannot be over emphasized due to the released waste which is mostly heavy metals into the environment. The study evaluated six heavy metal (A1, Cu, Fe, Ni, Pb and Cr) contents in a tailings dam from a specific mine site. Two sets of samples for the investigation were measured, that is, one in year 2012 and the other in year 2013. In the year 2012, the sample set was only taken at a distance profile of 500 meters from the foot of the dam, whereas the sample set taken in the year 2013 was for the 500 and 1500 meter distance profiles from the foot of the dam. The year 2012 and 2013 sample sets for the 500m distance profile were sampled very similarly to each other. A kilogram of each sample was taken as per grid format. The samples at varied depths were taken at 0-cm depth for the top layer, 20cm depth for the second layer, and 30cm depth for the third layer. The samples for the surface varied distance were taken at 1 m, 2m, 3m, and 4m away from each 500m and 1500 sampling points. The 2012 samples were analysed using characterization methods namely ICP MS and The 2013 samples were analysed using the ICP OES. The comparison of the field results for the six heavy metals studied (A1, Fe, Pb, Cu, Ni and Cr) was performed using statistical analytical methods, namely ANOVA. The statistical analysis results for heavy metals (A1, Fe, Pb, Cu, Ni and Cr) from sample and 2013 revealed that the group means are not significantly different from each other which means that there is no significant difference in (A1, Fe, Pb, Cu, Ni and Cr) concentrations with respect to both depth and distance. The observations from both 2012 and 2013 indicate the results of the samples are in agreement. In addition, the comparative average concentrations of the three results obtained reach the same conclusion that the tailing dam probably does not introduce considerable or significant amounts of these metals (A1, Fe, Pb, Cu, Ni and Cr) into the surrounding soils. / Chemical Engineering / M. Tech. (Chemical Engineering)

Thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy. School of Animal, Plant and Environmental Science, University of the Witwatersrand, Johannesburg, South Africa. October 2016. / Mining has negative impacts on the environment in many different ways. One method developed to quantify some of these impacts is Landscape Function Analysis (LFA) and this has been accepted by some mining companies and regulators. In brief, LFA aims at quantifying the organization of vegetative and landscape components in a landscape into patches along a transect and quantifying, in a relative manner, three basic processes important to landscape functioning, namely: soil stability or susceptibility to erosion, infiltration or runoff, and nutrient cycling or organic matter decomposition. However, LFA is limited in large heterogeneous environments, such as those around mining operations, due to its localized nature, and the man hours required to collect a representative set of measurements for such large and complex environments. Remote sensing using satellite-acquired data can overcome these limitations by sampling the entire environment in a rapid and objective manner. What is required is a method of connecting these satellite-based measurements to LFA measurements and then being able to extrapolate these measurements across the entire mine surface. The aim of this research was to develop a method to use satellite-based hyperspectral imagery to predict landscape function analysis (LFA) using partial least squares regression (PLSR). This was broken down into three objectives: (1) Collection of the LFA data in the field and validation of the LFA indices against other environmental variables collected at the same time, (2) validation of PLSR models predicting LFA indices and various environmental variables from ground-based spectra, and (3) production of risk maps based on predicting LFA indices and above-ground biomass using PLSR models and Hyperion satellite-based hyperspectral imagery. Although the study was based in grasslands at two mining regions, West Wits and Vaal River, a suitable Hyperion image was only available for Vaal River. A minimum of 374 points were sampled for LFA indices, ground-based spectra, above-ground biomass and soil cores along 2880 m of LFA transect from both mine sites. Soil cores were weighed fresh before sieving with a 2 mm sieve to separate root and stone fractions. The sieved soil fraction was tested for pH, EC, SOM, and for the West Wits samples, organic nitrogen and total extractable inorganic nitrogen. There was one modification to the LFA method where grass patches were collapsed into homogenous units as it was deemed not feasible to sample 180 m transects at grass tuft scales of 10 – 30 cm, but other patch definitions followed the LFA manual (Tongway and Hindley, 2004). Evidence suggested that some of the different patch types, in particular the bare/biological soil crust – bare grass – sparse grass patch types, represented successional stages in a continuum although this was not conclusive. There also was evidence that the presence or absence of cattle play a role in some processes active in these grasslands and erosion is mainly through deflation, rain splash and sheet wash. Generally the environmental variables supported the LFA indices although the nutrient cycling index was representative of above-ground nutrient cycling but not below-ground nutrient cycling. Models derived with PLSR to predict the LFA indices from ground-based spectral measurements were strong at both mine sites (West Wits: LFA stability r2 = 0.63, P < 0.0001; LFA infiltration r2 = 0.75, P < 0.0001; LFA nutrient cycling r2 = 0.73, P < 0.0001; Vaal River: LFA stability r2 = 0.39, P < 0.0001, LFA infiltration r2 = 0.72, P < 0.0001, LFA nutrient cycling r2 = 0.54, P < 0.0001), as were PLSR models predicting above-ground biomass (West Wits above-ground biomass r2 = 0.55, P = 0.0003; Vaal River above-ground biomass r2 = 0.79, P < 0.0001) and soil moisture (West Wits soil moisture r2 = 0.45, P = 0.0017; Vaal River soil moisture r2 = 0.68, P < 0.0001). However, for soil organic matter (r2 = 0.50, P < 0.0001) and EC (r2 = 0.63, P < 0.0001), Vaal River had strong prediction models while West Wits had weak models for these variables (r2 = 0.31, P = 0.019 and r2 = 0.10 and P < 0.18, respectively). For EC, the wide range of soil values at Vaal River in association with gypsum crusts, and low values throughout West Wits explained these model results but for soil organic matter, no clear explanation for these site differences was identified. Patch-based models could accurately discriminate between spectrally well-defined patch types such S. plumosum patches but were less successful with patch types that were spectrally similar such as the bare/biological soil crust – bare grass – sparse grass patch continuum. Clustering similar patch types together before PLSR modelling did improve these patch-based spectral models. To test the method proposed to predict LFA indices from satellite-based hyperspectral imagery, a Hyperion image matching 6 transects at Vaal River was acquired by NASA’s EO-1 satellite and downloaded from the USGS Glovis website. LFA transects were partitioned to match and extract pixel spectra from the Hyperion data cube. Thirty-one spectra were separated into calibration (20) and validation (11) data. PLSR models were derived from the calibration data, tested with validation data to select the optimum model, and then applied to the entire Hyperion data cube to produce prediction maps for five LFA indices and above-ground biomass. The patch area index (PAI) produced particularly strong models (r2 = 0.79, P = 0.0003, n =11) with validation data, whereas the landscape organization index (LOI) produced weak models. It is argued that this difference between these two essentially similar indices is related to the fact that the PAI is a 2-dimensional index and the LOI is a 1-dimensional index. This difference in these two indices allowed the PAI to compensate for some burned pixels on the transects by “seeing” the density pattern of grass tufts and patches whereas the linear nature of the LOI was more susceptible to the changing dimensions of patch structure due to the effects of fire. Although validation models for the three LFA indices of soil stability, infiltration and nutrient cycling were strong (r2 = 0.72, P = 0.004; r2 = 0.66, P = 0.008; r2 = 0.70, P = 0.005, n = 9 respectively), prediction maps were confounded by the presence of fire on some transects. The poor quality of the Hyperion imagery also meant great care had to be taken in the selection of models to avoid poor quality prediction maps. The 31 bands from the VNIR (478 – 885 nm) portion of the Hyperion spectra were generally the best for PLSR modelling and prediction maps, presumably because of better signal-to-noise ratios due to higher energy in the shorter wavelengths. With two satellite-based hyperspectral sensors already operational, namely the US Hyperion and the Chinese HJ-1A HSI, and a number expected to be launched by various space agencies in the next few years, this research presents a method to use the strengths of LFA and hyperspectral imagery to model and predict LFA index values and thereby produce risk maps of large, heterogeneous landscapes such as mining environments. As this research documents a method of partitioning the landscape rather than the pixel spectra into pure endmembers, it makes a valuable contribution to the fields of landscape ecology and hyperspectral remote sensing. / LG2017

A research report presented to the Department of Social Work School of Human and Community Development, Faculty of Humanities University of the Witwatersrand, July 2017 / Women have previously been discouraged from pursuing careers in the mining industry given the nature of the work in the field and the physical strength needed to do the work. However, literature has reported an increase in the number of women penetrating the field in recent years (Benya, 2009; Singer, 2002). New legislative frameworks in South Africa, such as the Mining Charter of 2002 (amended 2010) and the Mineral Petroleum Resources Development Act have made provisions for females to be absorbed into the field of mining, but this has not gone without challenges. This study thus sought to gain in-depth understanding of the experiences of underground female mine workers and demystify gender barriers that affect the functioning of women within the mining sector. The study was qualitative in nature and adopted a case study design to richly understand the phenomenon. The study used semi-structured interviews to collect data. Ten participants and two key informants were selected using purposive sampling technique. Data collected from participants was analysed using thematic analysis, in conjunction with the literature reviewed. The study addressed the social and human needs of female mine workers. It was found that, the mining industry has not been progressive in adequately addressing the unique needs of women who work underground. The study was essential in unravelling the experiences of female mine workers and thus made recommendations that can be used to introduce workplace appropriate interventions to be implemented to ensure that underground women mine workers are well accommodated within the industry. / XL2018

Thesis (M.Com. (Development Theory and Policy))--University of the Witwatersrand, Faculty of Commerce, Law and Management, School of Economic and Business Sciences. / South Africa has been referred to as a country of “geological superlatives” because of its rich and diverse mineral resource base. Despite its unique endowment of precious metals and mineral resources, the country has fallen short of translating these resources into the required economic linkages that will lead to sustainable employment creation and economic emancipation for the majority of its people. Whilst the country has established, successful critical upstream industries based on its natural resource advantage, it has not managed to develop successful downstream value additions in most of its strategic value chains, most notably the chromium mineral value chain. This paper explores the significance of the chromium mineral value chain in the context of South Africa’s economic development trajectory, the dynamics between the mining and manufacturing sectors, the ongoing structural constraints, and the implications all these have on stainless steel fabrication. South Africa is a dominant player in chrome, consuming approximately 80% of the world’s chromite ore reserves and is undeniably one of the major producers of ferrochromium globally, with production accounting for approximately 34% of total world production. Despite a mature ferrochromium industry that boasts world-class ferrochromium manufacturing facilities and contributes massively to the domestic and global economies, a declining market share to China threatens the sector. The availability (or lack thereof) of power supply, high energy costs, uncompetitive domestic prices amongst other structural issues are contributing to this decline. The challenge remains in government, the mining industry, labour and all other affected stakeholders to engage robustly in order to preserve a value chain that possesses enough potential to enhance the development of the country, both socially and economically.