Academic literature on the topic 'Remote sensing – South Africa – Eastern Cape'
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Journal articles on the topic "Remote sensing – South Africa – Eastern Cape"
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Graw, Valerie, Gohar Ghazaryan, Karen Dall, Andoni Delgado Gómez, Ayman Abdel-Hamid, Andries Jordaan, Ruben Piroska, et al. "Drought Dynamics and Vegetation Productivity in Different Land Management Systems of Eastern Cape, South Africa—A Remote Sensing Perspective." Sustainability 9, no. 10 (September 26, 2017): 1728. http://dx.doi.org/10.3390/su9101728.
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Mpofu, Mthulisi, Kakaba Madi, and Oswald Gwavava. "Remote sensing, geological, and geophysical investigation in the area of Ndlambe Municipality, Eastern Cape Province, South Africa: Implications for groundwater potential." Groundwater for Sustainable Development 11 (October 2020): 100431. http://dx.doi.org/10.1016/j.gsd.2020.100431.
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Achieng, Therezah, Kristine Maciejewski, Michelle Dyer, and Reinette Biggs. "Using a Social-ecological Regime Shift Approach to Understand the Transition from Livestock to Game Farming in the Eastern Cape, South Africa." Land 9, no. 4 (March 26, 2020): 97. http://dx.doi.org/10.3390/land9040097.
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This study explored the shift in land use from livestock farming to game farming in the Eastern Cape, South Africa, from a social-ecological regime shift perspective. A regime shift can be defined as a large, persistent change in the structure and function of the intertwined social and ecological components of a landscape. This research focused on the Amakhala game reserve as a case study to understand how the shift affected the provision of ecosystem services and human wellbeing. We used remote sensing techniques to quantify changes in vegetation and found evidence of vegetation recovery following the shift. We then conducted interviews with both landowners and farmworkers and used participatory mapping to understand their perceptions of the main drivers and social-ecological impacts of the shift in land use. Social narratives revealed stark differences in different stakeholders’ perceptions, highlighting that the change in land use had varied implications for, and were perceived differently by, different stakeholders. Farmworkers emphasized changes in social structures that weakened community bonds and erased valued connections to the land. At the same time, they increased employment of women, skills development, and increased wages as benefits of the new game farming regime. Landowners, on the other hand, indicated financial gains from the land use change. The transition therefore resulted in trade-offs that surfaced as social, economic, and cultural losses and gains. These changes, especially in social relationships and community structures, have implications for resilience and possible future pathways of development in the region.
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Münch, Zahn, and Julian Conrad. "Remote sensing and GIS based determination of groundwater dependent ecosystems in the Western Cape, South Africa." Hydrogeology Journal 15, no. 1 (December 8, 2006): 19–28. http://dx.doi.org/10.1007/s10040-006-0125-1.
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Ngie, A. "THERMAL REMOTE SENSING OF URBAN CLIMATES IN SOUTH AFRICA THROUGH THE MONO-WINDOW ALGORITHM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W11 (February 14, 2020): 117–23. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w11-117-2020.
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Abstract. Urban Heat Island (UHI) is among some of the challenges plaguing urban environments. There is increase human population within urban environments especially in the developing world, which is a need to understand the climates for their wellbeing. The use of multispectral satellite remote sensing to investigate the climatic conditions through radiation measurement is applied across the two major South African cities. The thermal remote sensing technique applied for this study is the direct determination of land surface temperatures (LST) using multispectral thermal imagery (ETM+). In addition, meteorological data which included air temperature and relative humidity for the same satellite image dates were used. The LST values obtained showed Johannesburg has many micro heat islands scattered across the metro than in Cape Town. These areas of heat islands corresponded to areas of human settlement and more so the unplanned as opposed to the planned ones. The estimated LST values and observed air temperature values with an R2 of 0.9. It could be concluded that expansion of urban areas in South Africa has led to increased thermal radiation of land surface in densely populated areas.
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Stark, R., G. Pillay, C. Haskins, and N. Margalit. "The use of airborne hyper-spectral remote sensing for mapping water bodies in the Cape Flats area of Cape Town, South Africa." Israel Journal of Plant Sciences 60, no. 1 (December 1, 2012): 161–67. http://dx.doi.org/10.1560/ijps.60.1-2.161.
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Adams, Luther A., Gavin W. Maneveldt, Andrew Green, Natasha Karenyi, Denham Parker, Toufiek Samaai, and Sven Kerwath. "Rhodolith Bed Discovered off the South African Coast." Diversity 12, no. 4 (March 27, 2020): 125. http://dx.doi.org/10.3390/d12040125.
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Rhodolith beds have not previously been recorded in South Africa. A multidisciplinary research effort used remote sampling tools to survey the historically unexplored continental shelf off the Eastern Cape coast of South Africa. A rhodolith bed, bearing both living and dead non-geniculate coralline red algae, was discovered in the 30–65 m depth range off the Kei River mouth in the newly proclaimed Amathole Offshore Marine Protected Area. Some of the rhodolith forming coralline algal specimens were identified as belonging to at least three genera based on their morphology and anatomy, namely, Lithophyllum, Lithothamnion and a non-descript genus. Rhodolith mean mass and diameter were 44.85 g ± 34.22 g and 41.28 mm ± 10.67 mm (N = 13), respectively. Remotely operated vehicle (ROV) imagery revealed a suite of epibenthic red macroalgae associated with the rhodolith bed. Taxonomy, vertical structure and distribution of rhodoliths in South Africa require further investigation.
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Twala, M., R. J. Roberts, and C. Munghemezulu. "Detection of magnetite in the Roossenekal area of the Eastern Bushveld Complex, South Africa, using multispectral remote sensing data." South African Journal of Geology 123, no. 4 (November 16, 2020): 573–86. http://dx.doi.org/10.25131/sajg.123.0041.
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Abstract Multispectral sensors, along with common and advanced algorithms, have become efficient tools for routine lithological discrimination and mineral potential mapping. It is with this paradigm in mind that this paper sought to evaluate and discuss the detection and mapping of magnetite on the Eastern Limb of the Bushveld Complex, using high spectral resolution multispectral remote sensing imagery and GIS techniques. Despite the wide distribution of magnetite, its economic importance, and its potential as an indicator of many important geological processes, not many studies had looked at the detection and exploration of magnetite using remote sensing in this region. The Maximum Likelihood and Support Vector Machine classification algorithms were assessed for their respective ability to detect and map magnetite using the PlanetScope Analytic data. A K-fold cross-validation analysis was used to measure the performance of the training as well as the test data. For each classification algorithm, a thematic landcover map was created and an error matrix, depicting the user’s and producer’s accuracies as well as kappa statistics, was derived. A pairwise comparison test of the image classification algorithms was conducted to determine whether the two classification algorithms were significantly different from each other. The Maximum Likelihood Classifier significantly outperformed the Support Vector Machine algorithm, achieving an overall classification accuracy of 84.58% and an overall kappa value of 0.79. Magnetite was accurately discriminated from the other thematic landcover classes with a user’s accuracy of 76.41% and a producer’s accuracy of 88.66%. The overall results of this study illustrated that remote sensing techniques are effective instruments for geological mapping and mineral investigation, especially iron oxide mineralization in the Eastern Limb of the Bushveld Complex.
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Elhebiry, Mohamed S., Mohamed Sultan, Ibrahim Abu El-Leil, Alan E. Kehew, Mahmoud H. Bekiet, Islam Abdel Shahid, Nehal M. A. Soliman, Abotalib Z. Abotalib, and Mustafa Emil. "Paleozoic glaciation in NE Africa: field and remote sensing-based evidence from the South Eastern Desert of Egypt." International Geology Review 62, no. 9 (July 12, 2019): 1187–204. http://dx.doi.org/10.1080/00206814.2019.1636416.
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Seutloali, Khoboso Elizabeth, Heinz Reinhard Beckedahl, Timothy Dube, and Mbulisi Sibanda. "An assessment of gully erosion along major armoured roads in south-eastern region of South Africa: a remote sensing and GIS approach." Geocarto International 31, no. 2 (May 29, 2015): 225–39. http://dx.doi.org/10.1080/10106049.2015.1047412.
Full textDissertations / Theses on the topic "Remote sensing – South Africa – Eastern Cape"
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Mhangara, Paidamwoyo. "Land use/cover change modelling and land degradation assessment in the Keiskamma catchment using remote sensing and GIS." Thesis, Nelson Mandela Metropolitan University, 2011. http://hdl.handle.net/10948/1467.
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Land degradation in most communal parts of the Keiskamma catchment has reached alarming proportions. The Keiskamma catchment is particularly predisposed to severe land degradation associated with soil erosion, thicket degradation and deteriorating riparian vegetation. There is a close coupling between land use/cover dynamics and degradation trends witnessed in the catchment. Soil erosion is prevalent in most of the communal areas in the catchment. The principal aim of this study was to investigate land use/cover trends, model the spatial patterns of soil loss and predict future land use/cover scenarios as a means of assessing land degradation in the Keiskamma catchment. Multi-temporal Landsat satellite imagery from 1972 to 2006 was used for land use/cover change analyses using object-oriented post-classification comparison. Fragmentation analysis was performed by computing and analyzing landscape metrics in the riparian and adjacent hillslope areas to determine the land cover structural changes that have occurred since 1972. The landscape function analysis was used to validate the current rangeland conditions in the communal areas and the former commercial farms. The current condition of the riparian zones and proximal hillslopes was assessed using the Rapid Appraisal of Riparian Condition and future land use/cover scenarios were simulated using the Markovcellular automata model. Spatial patterns of soil loss in the Keiskamma catchment were determined using the Sediment Assessment Tool for Effective Erosion Control (SATEEC), which is a GIS based RUSLE model that integrates sediment delivery ratios. Object oriented classification was used to map soil erosion surfaces and valley infill in ephemeral stream channels as a means of demonstrating the major sediment transfer processes operating in the Keiskamma catchment. The Mahalanobis distance method was used to compute the topographic thresholds for gully erosion. To understand the effect of soil characteristics in severe forms of erosion, laboratory analyses were undertaken to determine the physico-chemical soil properties. iv The temporal land use/cover analysis done using the post-classification change detection indicated that intact vegetation has undergone a significant decline from 1972 to 2006. The temporal changes within the intermediate years are characterized by cyclic transitions of decline and recovery of intact vegetation. An overall decline in intact vegetation cover, an increase in degraded vegetation and bare eroded soil was noted. Fragmentation analyses done in the communal villages of the central Keiskamma catchment indicated increasing vegetation fragmentation manifested by an increase in smaller and less connected vegetation patches, and a subsequent increase of bare and degraded soil patches which are much bigger and more connected. The Landscape Organisation Index revealed very low vegetation connectivity in the communal rangelands that have weak local traditional institutions. Fragmentation analyses in the riparian and proximal hillslopes revealed evidence of increasing vegetation fragmentation from 1972 to 2006. The Markov Cellular Automata simulation predicted a decline in intact vegetation and an increase in bare and degraded soil in 2019. The Keiskamma catchment was noted as experiencing high rates of soil loss that are above provincial and national averages. The classification of erosion features and valley infill showcased the vegetation enrichment in the ephemeral streams which is occurring at the expense of high soil losses from severe gully erosion on the hillslopes. This in turn has led to an inversion of grazing patterns within the catchment, such that grazing is now concentrated within the ephemeral stream channels. Soil chemical analyses revealed a high sodium content and low soluble salt concentration, which promote soil dispersion, piping and gully erosion. The presence of high amounts of illite-smectite in the catchment also accounts for the highly dispersive nature of the soil even at low SAR values. Significant amounts of swelling 2:1 silicate clays such as smectites cause cracking and contribute to the development of piping and gullying in the catchment. Given the worsening degradation trends in the communal areas, a systematic re-allocation of state land in sections of the catchment that belonged to the former commercial farms is recommended to alleviate anthropogenic pressure. Strengthening local institutions that effectively monitor and manage natural resources will be required in order to maintain v optimum flow regimes in rivers and curb thicket degradation. Measures to curb environmental degradation in the Keiskamma catchment should encompass suitable ecological interventions that are sensitive to the socio-economic challenges facing the people in communal areas.
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Fundisi, Emmanuel. "Spatio-temporal analyses of woody vegetation cover using remote sensing techniques: the case of Alice - King Williams Town route, Eastern Cape, South Africa." Thesis, University of Fort Hare, 2016. http://hdl.handle.net/10353/1830.
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Expansion of woody vegetation results in the transformation of a grass-dominated ecosystem to a tree-dominated ecosystem causing land degradation in most semi-arid areas. The imbalance in the natural ecosystem between herbaceous plants and woody vegetation poses a threat to the natural environment. Such changes alter the flow, availability and quality of nutrient resources in the biogeochemical cycle. Most of the dominating woody plants are often unpalatable to domestic livestock. Therefore, the objective is to assess the spatial extent of woody vegetation over time. Knowledge of the spatial and temporal characteristics of woody vegetation dynamics will enable the development of management plans. These characteristics can be derived using remote sensing techniques which have become efficient in such studies. This study aimed to characterize woody vegetation dynamics along the route between Alice and King Williams’s town in Eastern Cape Province South Africa using Landsat data. This aim was achieved by focussing on three specific objectives. The first objective was to compare the performance of multispectral data and Normalized Difference Vegetation Index (NDVI) data of Landsat imagery in mapping woody vegetation cover. The second objective was to investigate the effect of the spatial resolution of remotely-sensed data on discrimination of woody vegetation from other land cover types. The third objective characterised woody vegetation dynamics between 1986 and 2013/2014 using the results from the first objective. The study used Landsat imagery acquired in November or February of 1986, 1994/1995, 2002/2003 and 2013/2014. Due to lack of data which covered the study area two separate dates (November and February) where used for the study resulting in naming the study area western and eastern parts. Unsupervised classification was performed on the multispectral, NDVI and pan-sharpened images to generate four generic land cover classes, namely water, bare land, grassland and woodland. Accuracy assessments of the classified images was done using error matrix. The results showed that the classification based on NDVI images yielded a better overall accuracy than the classification based on multispectral images for the western (83 percent and 75 percent, respectively) and eastern (82 percent and 76 percent, respectively) parts of the study area. Similarly, pan-sharpening resulted in better overall classification accuracy than multispectral, but comparable to the classification of the NDVI images for both the western (82 percent) and eastern (83 percent) parts of the study area. Remote sensing is an effective tool in assessing changes in the physical environment. Landsat imagery is suitable in assessing land cover dynamics given the long-term and free availability of the image. In addition, the large spatial coverage it provides, enables Landsat data to be used on studies that have wide spatial coverage. Classification for the purpose of time-series analysis was then performed on the NDVI images of each date (1986, 1994/1995, 2002/2003 and 2013/2014). Both woody vegetation and grassland experienced changes from 1986 to 2013/2014 with grassland occupying (75 percent) compared to woodland (17 percent) in 1986. In the year 2013/14 grassland occupied 32 percent and woodland occupied 51 percent of the study area. The increase in woody vegetation in the study area can be attributed to livestock rearing and migration of people from the rural to urban areas post-Apartheid. The study output will aid in the development of a database on land cover distribution of the area between King William’s town and Alice town, providing useful information to decision-making and further studies on woody vegetation.
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Haindongo, Priscilla Nauwanga. "An investigation of the factors influencing vegetation stress in a part of the Keiskamma catchment, Eastern Cape : a remote sensing and GIS approach." Thesis, Nelson Mandela Metropolitan University, 2009. http://hdl.handle.net/10948/975.
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Vegetation stress as a form of degradation is a widespread problem in many catchments in the Eastern Cape province. The Keiskamma is one of the catchments where considerable parts of the thicket biome are stressed. This necessitates an assessment of the status of the thicket biome by way of detecting vegetation stress in the area. The underpinnings of vegetation stress are investigated in this study. As a basic method to evaluate the thicket condition, remotely sensed data were acquired. High resolution ASTER imagery for the Keiskamma area at two different dates (2001 and 2005) was used to compute SVI and NDVI as indicators of vegetation stress conditions. A Digital Elevation Model (DEM) was used to derive slope angle and aspect. By way of digitizing from ortho-photo maps, various land-use types were mapped using Arc View GIS. The relationship between land use, terrain, soil erosion and vegetation stress was established. Field based techniques comprising stomatal conductance measurements were used and compared to remotely sensed data. The SVI and NDVI resultant images expressed similarities in areas depicting vegetation stress conditions at both epochs. A strong linear regression between NDVI and stomatal conductance measurements (mmol/m²) serve to confirm that the NDVI is a reliable indicator of vegetation stress condition. Slope angle and aspect were found to have a significant influence on vegetation stress conditions. Similarly variations in soil moisture and soil surface condition have strong implications for vegetation stress. Amongst other land-use types, abandoned lands were found to have the lowest NDVI values implying an association with the worst vegetation stress scenarios. It was concluded that an element of persistent stress conditions exists amongst the thicket vegetation of the Keiskamma catchment. This was mainly due to land use activities in the area.
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Ngcofe, Luncedo Dalithemba Sanelisiwe. "Assessment and monitoring of land degradation using remote sensing and geographic information systems (GIS): a case study of Qoqodala within the Wit-Kei catchment in the Eastern Cape, South Africa." Thesis, Rhodes University, 2009. http://hdl.handle.net/10962/d1005492.
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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
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Nyamugama, Adolph. "Monitoring carbon stocks in the sub-tropical thicket biome using remote sensing and GIS techniques : the case of the Great Fish River Nature Reserve and its environs, Eastern Cape province, South Africa." Thesis, Nelson Mandela Metropolitan University, 2013. http://hdl.handle.net/10948/d1020303.
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The subtropical thicket biome in the Eastern Cape Province of South Africa has been heavily degraded and transformed due overutilization during the last century. The highly degraded and transformed areas exhibit a significant loss of above ground carbon stocks (AGC) and loss of SOC content. Information about land use /cover change and fragmentation dynamics is a prerequisite for measuring carbon stock changes. The main aim of this study is to assess the trends of land use/cover change, fragmentation dynamics, model the temporal changes of AGC stocks in the Great Fish River Nature Reserve and its environs from 1972 to 2010, quantify and map the spatial distribution of SOC concentrations in the partial subtropical thicket cover in the Great Fish River Nature Reserve and environs (communal rangelands). Multi-temporal analyses based on 1972 Landsat MSS, 1982 and 1992 Landsat TM, 2002 Landsat ETM and 2010 SPOT 5 High Resolution images were used for land use/cover change detection and fragmentation analysis. Object oriented post-classification comparison was applied for land use/cover change detection analysis. Fragmentation dynamics analysis was carried out by computing and analyzing landscape metrics in land use/cover classes. Landscape fragmentation analyses revealed that thicket vegetation has increasingly become fragmented, characterized by smaller less linked patches of intact thicket cover. Landscape metrics for intact thicket and degraded thicket classes reflected fragmentation, as illustrated by the increase in the Number of Patches (NP), Patch Density (PD), Landscape Shape Index (LSI), and a decrease in Mean Patch Size (MPS). The use of remote sensing techniques and landscape metrics was vital for the understanding of the dynamics of land use/cover change and fragmentation. Baseline land use/cover maps produced for 1972, 1982, 1992 2002 and 2010 and fragmentation analyses were then used for analyzing carbon stock changes in the study area. To model the temporal changes of AGC stocks in the Great Fish River Nature Reserve and its environs from 1972 to 2010, a method based on the integration of RS and GIS was employed for the estimation of AGC stocks in a time series. A non-linear regression model was developed using NDVI values generated from SPOT 5 HRG satellite imagery of 2010 as the independent variable and AGC stock estimates from field plots as the dependent variable. The regression model was used to estimate AGC stocks for the entire study area on the 2010 SPOT 5 HRG and also extrapolated to the 1972 Landsat MSS, 1982 and 1992 Landsat TM, and 2002 Landsat ETM. The AGC stocks for the period 1972 -1982, 1982-1992, 1992-200) and 2002-2010 were compared by means of change detection analysis. The comparison of AGC stocks was carried out at subtropical thicket class level. The results showed a decline of AGC stocks in all the classes from 1972 to 2010. Degraded and transformed thicket classes had the highest AGC stock losses. The decline of AGC stocks was attributed to thicket transformation and degradation which were caused by anthropogenic activities. To map and quantify SOC concentration in partial (fractional) thicket vegetation cover, the spectral reflectance of both thicket vegetation and bare-soils was measured in situ. Soil samples were collected from the sampling sites and transported to the laboratory for spectral reflectance and SOC measurements. Thicket vegetation and bare soil reflectance were measured using spectroscopy both in situ and under laboratory conditions. Their respective endmembers were extracted from ASTER imagery using the Pixel Purity Index (PPI). The endmembers were validated with in situ and laboratory thicket and bare-soil reflectance signatures. The spectral unmixing technique was applied to ASTER imagery to discriminate pure pixels of thicket vegetation and bare-soils; a residual spectral image was produced. The Residual Spectral Unmixing (RSU) procedure was applied to the residual spectral image to produce an RSU soil spectrum image. Partial Least Squares Regression (PSLR) model was developed using spectral signatures of a residual soil spectrum image as the independent variable and SOC concentration measured from soil samples as the dependent variable. The PSLR prediction model was used to predict SOC concentration on the RSU soil spectral image. The predicted SOC concentration was then validated with SOC concentration measured from the field plots. A Strong correlation (R2 = 0.82) was obtained between the predicted SOC concentration and the SOC concentration measured from field samples. The PSLR was then used to generate a map of SOC concentration for the Great Fish River Nature Reserve and its environs. Areas with very low SOC concentrations were found in the degraded communal villages, as opposed to the higher SOC values in the protected area. The results confirmed that RS techniques are key to estimating and mapping the spatial distribution of SOC concentration in partial subtropical thicket vegetation. Partial thicket vegetation has a huge influence on the soil spectra; it can influence the prediction of SOC concentration. The use of the RSU approach eliminates partial thicket vegetation cover from bare soil spectra. The residual soil spectrum image contains enough information for the mapping of SOC concentration. The technique has the potential to augment the applicability of airborne imaging spectroscopy for soil studies in the sub-tropical thicket biome and similar environments.
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Manjoro, Munyaradzi. "Soil erosion and sediment source dynamics of a catchment in the Eastern Cape province, South Africa: an approach using remote sensing and sediment source fingerprinting techniques." Thesis, Nelson Mandela Metropolitan University, 2012. http://hdl.handle.net/10948/d1015038.
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This study originated from an evaluation of the performance of a commercially available high concentration point focus concentrator PV system. The effect of module design flaws was studied by using current-voltage (I-V) curves obtained from each module in the array. The position of reverse bias steps revealed the severity of mismatch in a string of series-connected cells. By understanding the effects of the various types of mismatch, power losses and damage to the solar cells resulting from hot spot formation can be minimized and several recommendations for improving the basic performance of similar systems were made. Concern over the extent and type of defect failure of the concentrator photovoltaic (CPV) cells prompted an investigation into the use of a light beam induced current (LBIC) technique to investigate the spatial distribution of defects. An overview of current and developing LBIC techniques revealed that the original standard LBIC techniques have found widespread application, and that far-reaching and important developments of the technique have taken place over the years. These developments are driven by natural progression as well as the availability of newly developed advanced measurement equipment. Several techniques such as Lock-in Thermography and the use of infrared cameras have developed as complementary techniques to advanced LBIC techniques. As an accurate contactless evaluation tool that is able to image spatially distributed defects in cell material, the basis of this method seemed promising for the evaluation of concentrator cells.
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Mathe, Tumelo. "GIS and remote sensing as a potential tool to support digital soil mapping in the Eastern Cape province in South Africa." Thesis, University of Fort Hare, 2014. http://hdl.handle.net/10353/d1019858.
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This study is based on assessing the potential use of GIS and Remote Sensing in trying to fill the various soil maps of selected regions at different scales with spatial soil data. A variety of processes are available for use. These include band ratios, principal component analysis as well as use of a digital elevation model (DEM). With the advent of GIS and Remote Sensing, these principles in the new niche of study are investigated to check if they can be used to augment the current processes available in soil mapping techniques. Such processes as band ratioing, principal component analysis and use of Digital Elevation Models (DEMs) are investigated to check if they can be used in soil mapping techniques. From the results produced it is evident that these processes have the potential to be used in the Digital Soil Mapping process. Despite the limitation of remote sensing to a few centimetres of the topsoil these processes can be used together with the soil mapping techniques currently being used to come up with soil maps.
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Lane, Karl. "The feasibility of using remote sensing and field-based checks to monitor the impact caused by collection of wood in the Eastern Cape/Ciskei forest and thicket formations." Master's thesis, University of Cape Town, 1989. http://hdl.handle.net/11427/21929.
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Bibliography: pages 71-83.A variety of studies have shown the problems of energy supply faced by low-income communities in southern Africa. Most of these communities are dependent upon indigenous fuelwood supplies. In addition, many of these communities use indigenous wood for construction. This largely uncontrolled utilisation imposes severe threats on woody vegetation communities. The Eastern Cape/Ciskei region is an area where energy supply problems are particularly severe and impacts on woody vegetation correspondingly severe. This study aimed to investigate the feasibility of using remote sensing techniques to monitor the the impact caused by collection of wood in the Eastern Cape/Ciskei forest and thicket communities. A variety of remote sensing techniques for landcover analysis were investigated. In all cases, visual interpretation was used because it is considerably cheaper and demands less technical expertise than would computer processing. In addition, many studies have shown visual interpretation to be superior. Maps were drawn from multitemporal aerial photograph sequences and from Landsat and SPOT satellite images. These maps showed that there has been relatively little change in area of woody vegetation in the study area since 1956. However, field studies showed that vegetation community structure had been degraded as a result of intense and sustained human impact. This qualitative decline also reflected a decline in usefulness of the woody vegetation of the area to local communities. This substantial degradation was not visible on any of the remote sensing imageries. This emphasises that field-based checks to monitor human impacts on forest and thicket formations are essential. Strategies for reducing the dependence of low-income communities on indigenous vegetation for energy supplies and constructional timber have been reviewed from the literature and these are descibed in Appendix 1. Most successful strategies in other parts of the world have been the result of a national commitment to tree planting, recognition of a multiplicity of constraints and the voluntary involvement of the communities the strategies are intended to assist.
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Chari, Martin Munashe. "Assessing the vulnerability of resource-poor households to disasters associated with climate variability using remote sensing and GIS techniques in the Nkonkobe Local Municipality, Eastern Cape Province, South Africa." Thesis, University of Fort Hare, 2016. http://hdl.handle.net/10353/2425.
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The main objective of the study was to assess the extent to which resource-poor households in selected villages of Nkonkobe Local Municipality in the Eastern Cape Province of South Africa are vulnerable to drought by using an improvised remote sensing and Geographic Information System (GIS)-based mapping approach. The research methodology was comprised of 1) assessment of vulnerability levels and 2) the calculation of established drought assessment indices comprising the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI) from wet-season Landsat images covering a period of 29 years from 1985 to 2014 in order to objectively determine the temporal recurrence of drought in Nkonkobe Local Municipality. Vulnerability of households to drought was determined by using a multi-step GIS-based mapping approach in which 3 components comprising exposure, sensitivity and adaptive capacity were simultaneously analysed and averaged to determine the magnitude of vulnerability. Thereafter, the Analytical Hierarchy Process (AHP) was used to establish weighted contributions of these components to vulnerability. The weights applied to the AHP were obtained from the 2012 - 2017 Nkonkobe Integrated Development Plan (IDP) and perceptions that were solicited from key informants who were judged to be knowledgeable about the subject. A Kruskal-Wallis H test on demographic data for water access revealed that the demographic results are independent of choice of data acquired from different data providers (χ2(2) = 1.26, p = 0.533, with a mean ranked population scores of 7.4 for ECSECC, 6.8 for Quantec and 9.8 for StatsSA). Simple linear regression analysis revealed strong positive correlations between NDWI and NDVI ((r = 0.99609375, R2 = 1, for 1985), 1995 (r = 0.99609375, R2 = 1 for 1995), (r = 0.99609375, R2 = 1 for 2005) and (r = 0.99609375, R2 = 1 for 2014). The regression analysis proved that vegetation condition depends on surface water arising from rainfall. The results indicate that the whole of Nkonkobe Local Municipality is susceptible to drought with villages in south eastern part being most vulnerable to droughts due to high sensitivity and low adaptive capacity.
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Tanser, Frank Courteney. "The application of a landscape diversity index using remote sensing and geographical information systems to identify degradation patterns in the Great Fish River Valley, Eastern Cape Province, South Africa." Thesis, Rhodes University, 1997. http://hdl.handle.net/10962/d1005488.
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Using a range of satellite-derived indices I describe. monitor and predict vegetation conditions that exist in the Great Fish River Valley, Eastern Cape. The heterogeneous nature of the area necessitates that the mapping of vegetation classes be accomplished using a combination of a supervised approach, an unsupervised approach and the use of a Moving Standard Deviation Index (MSDI). Nine vegetation classes are identified and mapped at an accuracy of 84%. The vegetation classes are strongly related to land-use and the communal areas demonstrate a reduction in palatable species and a shift towards dominance by a single species. Nature reserves and commercial rangeland are by contrast dominated by good condition vegetation types. The Modified Soil Adjusted Vegetation Index (MSA VI) is used to map the vegetation production in the study area. The influence of soil reflectance is reduced using this index. The MSA VI proves to be a good predictor of vegetation condition in the higher rainfall areas but not in the more semi-arid regions. The MSA VI has a significant relationship to rainfall but no absolute relationship to biomass. However, a stratification approach (on the basis of vegetation type) reveals that the MSA VI exhibits relationships to biomass in vegetation types occurring in the higher rainfall areas and consisting of a large cover of shrubs. A technique based on an index which describes landscape spatial variability is presented to assist in the interpretation of landscape condition. The research outlines a method for degradation assessment which overcomes many of the problems associated with cost and repeatability. Indices that attempt to provide a correlation with net primary productivity, e.g. NDVI, do not consider changes in the quality of net primary productivity. Landscape variability represents a measure of ecosystem change in the landscape that underlies the degradation process. The hypothesis is that healthy/undisturbed/stable landscapes tend to be less variable and homogenous than their degraded heterogenous counterparts. The Moving Standard Deviation Index (MSDI) is calculated by performing a 3 x 3 moving standard deviation window across Landsat Thematic Mapper (TM) band 3. The result is a sensitive indicator of landscape condition which is not affected by moisture availability and vegetation type. The MSDI shows a significant negative relationship to NDVI confirming its relationship to condition. The cross-classification of MSDI with NDVI allows the identification of invasive woody weeds which exhibit strong photosynthetic signals and would therefore be categorised as good condition using NDVI. Other ecosystems are investigated to determine the relationship between NDVI and MSDI. Where increase in NDVI is disturbance-induced (such as the Kalahari Desert) the relationship is positive. Where high NDVI values are indicative of good condition rangeland (such as the Fish River Valley) the relationship is negative. The MSDI therefore always exhibits a significant positive relationship to degradation irrespective of the relationship of NDVI to condition in the ecosystem.
Conference papers on the topic "Remote sensing – South Africa – Eastern Cape"
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Gwate, O., Sukhmani K. Mantel, Anthony R. Palmer, and Lesley A. Gibson. "Measuring evapotranspiration using an eddy covariance system over the Albany Thicket of the Eastern Cape, South Africa." In SPIE Remote Sensing, edited by Christopher M. U. Neale and Antonino Maltese. SPIE, 2016. http://dx.doi.org/10.1117/12.2245426.
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Hayden, Linda, Ambrose Jearld, Je'aime Powell, Kuchumbi Hayden, and Nina L. Jackson. "Hands-on GPS and remote sensing training for high school learners during IGARSS 2009 in Cape Town, South Africa." In IGARSS 2010 - 2010 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2010. http://dx.doi.org/10.1109/igarss.2010.5651320.
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Elhebiry, Mohamed Samy, Mohamed Sultan, Mohamed Sultan, A. E. Kehew, A. E. Kehew, Ibrahim Abu El-Leil, Ibrahim Abu El-Leil, et al. "ORDOVICIAN GLACIATION IN NE AFRICA: FIELD AND REMOTE SENSING-BASED EVIDENCES FROM THE SOUTH EASTERN DESERT OF EGYPT." In GSA Annual Meeting in Indianapolis, Indiana, USA - 2018. Geological Society of America, 2018. http://dx.doi.org/10.1130/abs/2018am-320677.
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