Global Positioning System (GPS) satellites and receivers are used to derive total electron content (TEC) from the time delay and phase advance of the radiowaves as they travels through the ionosphere. TEC is defined as the integralof the electron density along the satellite-receiver signal path. Electron densityprofiles can be determined from these TEC values using ionospheric tomographic inversion techniques such as Multi-Instrument Data Analysis System (MIDAS).This thesis reports on a study aimed at evaluating the suitability of ionospheric tomography as a tool to derive one-dimensional electron density profiles, using the MIDAS inversion algorithm over Grahamstown, South Africa (33.30◦S, 26.50◦E). The evaluation was done by using ionosonde data from the Louisvale (28.50◦S, 21.20◦E) and Madimbo (22.40◦S, 30.90◦E) stations to create empirical orthonormal functions (EOFs). These EOFs were used by MIDAS in the inversion process to describe the vertical variation of the electron density. Profiles derived from the MIDAS algorithm were compared with profiles obtained from the international Reference Ionosphere (IRI) 2001 model and with ionosonde profiles from the Grahamstown ionosonde station. The optimised MIDAS profiles show a good agreement with the Grahamstown ionosonde profiles. The South African Bottomside Ionospheric Model (SABIM) was used to set the limits within which MIDAS was producing accurate peak electron density (NmF2) values and to define accuracy in this project, with the understanding that the national model (SABIM) is currently the best model for the Grahamstown region. Analysis show that MIDAS produces accurate results during the winter season, which had the lowest root mean square (rms) error of 0.37×1011[e/m3] and an approximately 86% chance of producing NmF2 closer to the actual NmF2 value than the national model SABIM. MIDAS was found to also produce accurate NmF2 values at 12h00 UT, where an approximately 88% chance of producing an accurate NmF2 value, which may deviate from the measured value by 0.72×1011[e/m3], was determined. In conclusion, ionospheric tomographic inversion techniques show promise in the reconstruction of electron density profiles over South Africa, and are worth pursuing further in the future.

Please read the abstract in the section 00front of this document / Dissertation (MSc (Botany))--University of Pretoria, 2006. / Plant Science / unrestricted

Land degradation is a global problem affecting many countries including South Africa. This study was conducted in order to assess and monitor the nature and extent of land degradation within Qoqodala in the Eastern Cape Province, of South Africa. The study used GIS and Remote Sensing techniques together with household interviews in determining extent, spatial characteristics and nature of land degradation within the study area. Vegetation cover and bare-ground change were the land degradation indicators assessed and monitored by this study. Through RGB band combination, Tasselled Cap Analysis and Unsupervised ISODATA classification techniques, Landsat images over the past eighteen years (1984, 1993, 1996, 2000 and 2002) have been analysed. The results showed that there is vegetation cover and bare-ground increase in the study area. The vegetation increase has been seen as a sign of land degradation increase due to the encroachment of indigenous vegetation by Euryops species (also known as Lapesi by the local community). The bare-ground land degradation indicator has also increased. The analyses of slope showed the spatial characteristics of bare-ground occurring on moderate to flat slopes while vegetation cover occurs on steep to very steep slopes. Furthermore the photographs captured during field visits show rills and gullies or dongas occurring on bare-ground. The interviewed respondents indicated that decline in food production, increase in dongas and vast increase in Euryops and a decline in grassland are the indicators of degradation that are observed in the study area. The occurrence of erosion features (rills and dongas) on bare-ground and the increase of vegetation shown by GIS and Remote Sensing techniques showed a positive correlation with field and household survey towards establishing the nature of land degradation. In this study Landsat images together with interviews proved to be a very useful tool for land degradation research. However the suggestion of a higher spatial resolution satellite image on small catchment studies is recommended

Wetlands in South Africa are increasingly coming under threat from agriculture and urban development and rapidly disappearing, especially small, ephemeral wetlands. In response to the many threats to wetlands, South Africa has seen an increased interest in wetland research, which has introduced many methods to help standardize the approach to research, management and conservation of wetlands. Remote sensing can be a powerful tool to monitor changes in wetland vegetation and degradation leading to losses in wetlands. However, research into wetland ecosystems has focused on large systems (> 8 ha). Small wetlands (< 2 ha), by contrast, are often overlooked and unprotected due to the lack of detailed inventories at a scale that is appropriate for their inclusion. The main aim of this study was to determine if remote sensing (RS) and Geographical Information System (GIS) techniques could detect changes in small, ephemeral wetlands within areas under different management regimes in the Nelson Mandela Bay Metropole (NMBM) at different time intervals. Further, to explore the potential of hyperspectral remote sensing for the discrimination between plant species and to see if differences could be detected in the same species within two areas different management regimes. Four SPOT satellite images taken within a 6-year period (2006-2012) were analysed to detect land cover land changes. Supervised classification to classify land cover classes and post-classification change detection was used. Proportions of dense vegetation were higher in the conservation area and bare surface was higher outside that conservation area in the metropolitan open space area. Statistical tests were performed to compare the spectral responses of the four individual wetland sites using Normalized Difference Vegetation Index (NDVI) and red edge position (REP) .REP results for conserved sites showed significant differences (P < 0.05), as opposed to non-conserved ones. By implication, wetland vegetation that is in less degraded condition can be spectrally discriminated, than the one that is most degraded. Field spectroscopy and multi-temporal imagery can be useful in studying small wetlands.

MEnv.Sc / Department of Geography and Geo-Information Sciences

MEVNSC / Department of Geography and Geo-Information Sciences / Vegetation is one of the most important renewable natural resources to play a role in the preservation of the environment and biodiversity. Various land use activities such as urbanization, population growth and other anthropogenic activities, as well as climate change have been some of the major drivers which alter vegetation cover and contribute to biodiversity loss. This research study uses remote sensing and Geographical Information System to quantify vegetation and land cover change in Makhado over a five-year period (2007 - 2012). This study used multi-temporal satellite image data to identify the dynamic pattern of vegetation change and the negative impacts it has on the environment. The research uses remote sensing techniques and GIS software to analyse data. In addition, satellite imageries were used to study the spatial and temporal distribution of vegetation. The results of the study show that settlement areas have been on a stable positive and mostly uncontrolled expansion from 17.73% of the study area in 2007 to 30.52% in 2012. Vegetation on the other hand, has been on a steady decline, from 10.65% in 2007 to 5.92% in 2012, as well as the ecosystems quality on which biodiversity depends for their existence and to a greater extent the climate conditions, with an increase in temperature, methane, nitrous oxide and carbon dioxide. The monitoring of vegetation change can play a vital role in knowledge generation, best practices and as well as Environmental Monitoring and Evaluation which can be abated in the near future. This study recommends that the South Africa Government and public agencies concerned develop policies and strategies to bring about balanced, coordinated and sustainable development in the municipality and its district.

MESMEG / Department of Mining and Environmental Geology / Many recent studies have shown that some of the greatest water needs occur in areas underlain by crystalline rocks with complex hydrogeology. Crystalline basement rocks underlie over 60% of the South African surface, and the Limpopo Province of South Africa is no exception. Previous attempts to develop the lithologies of Limpopo for groundwater abstraction without the use of sound scientific methodologies resulted in low yielding boreholes and a higher rate of borehole failure. The complexity of the lithologies in the region necessitates the use of sound scientific methodologies for the delineation of promising groundwater potential zones. Therefore, the principal objective of the present study was to delineate groundwater potential zones through an integrated approach of remote sensing, geophysics, as well as the use of ancillary datasets. The area of focus is located in the northeastern section of Limpopo province, covering an area of about 16 800km2. Geologically, it is underlain by three Lithostratigraphic domains comprised of Archean-aged basement rocks, Soutpansberg volcano-sedimentary succession and subsidiary basins of the main Karoo young sedimentary cover. In general, the groundwater potential of a region is a function of factors such as lithology, lineaments, slope, climate and land use/ land cover. Thus, the present study used parameters such as lineaments, lithologies, slope, and land use/ land cover to produce a groundwater potential zone map. The thematic layers were prepared from raw datasets, which include; LANDSAT 8 OLI, ASTER-DEM, aeromagnetic data, geological maps, and land use/land cover data, which were overlaid in a GIS environment. The resultant groundwater map revealed the presence of five distinct classes of groundwater potential zones, which were categorised into excellent, good, moderate, low and very low. Interpretation of the results shows that the study area is dominated by areas that may be regarded as moderate water potential zones, covering about 52% of the total area. On the other hand, low and good groundwater potential zones occur in almost equal proportions of 19.52 % and 24 % respectively. The results obtained were validated using GRIP borehole dataset, and a number of follow-up geophysical surveys. iii Overlaying of the boreholes dataset on the map showed positive correlation between borehole yields groundwater potential zones. On the other hand, follow-up Vertical Electrical Sounding surveys revealed the presence of conductive layers in some selected target areas. The groundwater potential zone map and validation results provided a meaningful regional assessment of groundwater distribution in the study area. Thus, the results of this study can be used as a guideline for future groundwater exploration projects. / NRF

Savannahs regulate an agro-ecosystem crucial for the production of domestic livestock, one of the main sources of income worldwide as well as in South African rural communities. Nevertheless, globally these ecosystem functions are threatened by intense human exploitation, inappropriate land use and environmental changes. Leaf area index (LAI) defined as one half the total green leaf area per unit ground surface area, is an inventory of the plant green leaves that defines the actual size of the interface between the vegetation and the atmosphere. Thus, LAI spatial data could serve as an indicator of rangeland productivity. Consequently, the accurate and rapid estimation of LAI is a key requirement for farmers and policy makers to devise sustainable management strategies for rangeland resources. In this study, the main focus was to assess the utility and the accuracy of the PROSAILH radiative transfer model (RTM) to estimate LAI in the South African rangeland on the recently launched Landsat 8 sensor data. The Landsat 8 sensor has been a promising sensor for estimating grassland LAI as compared to its predecessors Landsat 5 to 7 sensors because of its increased radiometric resolution. For this purpose, two PROSAIL inversion methods and semi- empirical methods such as Normalized difference vegetation index (NDVI) were utilized to estimate LAI. The results showed that physically based approaches surpassed empirical approach with highest accuracy yielded by artificial neural network (ANN) inversion approach (RMSE=0.138), in contrast to the Look-Up Table (LUT) approach (RMSE=0.265). In conclusion, the results of this study proved that PROSAIL RTM approach on Landsat 8 data could be utilized to accurately estimate LAI at regional scale which could aid in rapid assessment and monitoring of the rangeland resources. / Environmental Sciences / M. Sc. (Environmental Science)

Savannahs regulate an agro-ecosystem crucial for the production of domestic livestock, one of the main sources of income worldwide as well as in South African rural communities. Nevertheless, globally these ecosystem functions are threatened by intense human exploitation, inappropriate land use and environmental changes. Leaf area index (LAI) defined as one half the total green leaf area per unit ground surface area, is an inventory of the plant green leaves that defines the actual size of the interface between the vegetation and the atmosphere. Thus, LAI spatial data could serve as an indicator of rangeland productivity. Consequently, the accurate and rapid estimation of LAI is a key requirement for farmers and policy makers to devise sustainable management strategies for rangeland resources. In this study, the main focus was to assess the utility and the accuracy of the PROSAILH radiative transfer model (RTM) to estimate LAI in the South African rangeland on the recently launched Landsat 8 sensor data. The Landsat 8 sensor has been a promising sensor for estimating grassland LAI as compared to its predecessors Landsat 5 to 7 sensors because of its increased radiometric resolution. For this purpose, two PROSAIL inversion methods and semi- empirical methods such as Normalized difference vegetation index (NDVI) were utilized to estimate LAI. The results showed that physically based approaches surpassed empirical approach with highest accuracy yielded by artificial neural network (ANN) inversion approach (RMSE=0.138), in contrast to the Look-Up Table (LUT) approach (RMSE=0.265). In conclusion, the results of this study proved that PROSAIL RTM approach on Landsat 8 data could be utilized to accurately estimate LAI at regional scale which could aid in rapid assessment and monitoring of the rangeland resources. / Environmental Sciences / M. Sc. (Environmental Science)

MENVSC / Department of Geography and Geo-Information Sciences / This is a case study research that focuses on the assessment of the impacts of land use changes on the Duthuni wetland ecosystem in Limpopo Province using geospatial techniques and Social Survey. SPOT 4 satellite images which covered the time frame between 1999, 2005 to 2012, were used. The unit of analysis included different institutions such as the local municipality, farmers, the heads of the households and Chief of the Village. In this study, different methods of sampling were used in different context for selecting participants and for sample size determination. The different instruments for data collection included the questionnaires, interviews, focus group interviews and documents review. Socio-economic survey and review of documents were carried out to understand historical trends, collect ground truth and other secondary information required. Data collected from the survey were captured and analysed using the Statistical Package for Scientific Solutions (SPSS). For quantitative analysis, Chi-Square and cross tabulation were employed in SPSS. Analysis of satellite imagery was accomplished through integrated use of ERDAS Imagine (version 2015) and ArcGIS (version 10.1) software package. The themes were identified and analysed using the content analysis based on the main research topics. The results show that the land use/ cover changes have occurred at an unprecedented rate over the years 1999 to 2012. From the year 1999 to the year 2012, the total land use/ cover conversions equal to 299.984 ha of land. The trend and spatial extent of land use/ cover changes had undergone considerable changes over the years in the study period. The major contributing factors included population increase, expansion of agriculture and lack of space to settle. The residential area was found to be the major factor contributing to land use change over the years with an increase of (102.87ha.). People residing in Duthuni village especially along the wetland ecosystem consist of the majority of female-headed households. There is no proper facilitation and mentoring in the village by the government in order to resolve social problems when it comes to land use change. Water pollution and soil erosion were found to be the major concern by wetland users such as farmers and residents. Lack of knowledge has also been identified as one of the driving factors of environmental impacts of land use change in the area. Food was the most resources with 41% which the community gets from the wetland.