Geography

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An analysis of terracettes in a region of Giant's Castle Game Reserve, KwaZulu-Natal Drakensberg, South Africa.
(1998) Sinclair, Richard Roy.; Ahmed, Fethi B.
Terracettes are a widely occurring form of micro-relief found throughout regions displaying various climatic and environmental conditions. Much speculation surrounds the processes responsible for their formation and development. An investigation of these micro-forms, their associated soil physical properties, sustaining mechanisms, and their relationship to slope stability was undertaken in Giant's Castle Game Reserve, KwaZulu - Natal Drakensberg, South Africa. The study showed that relationships between terracette morphology and soil physical properties within the Reserve are few, and that current soil conditions cannot be used to infer process related to terracette formation. However dry bulk density data indicated that soil creep is the dominant formative mechanism within the Reserve. Throughflow at riser surfaces was the dominant sustaining mechanism, with needle ice growth, wind, surfacewash and animal disturbance contributing minor retreat at both treads and risers. Aspect played an important role in determining soil physical characteristics. It was inferred that terracettes imparted stability to the slopes on which they are found, and with continued retreat at both treads and risers the slope was again placed under conditions of instability.
Assessment of structural attributes of even-aged Eucalyptus grandis forest plantations using small-footprint discrete return lidar data.
(2009) Tesfamichael, Solomon Gebremariam.; van Aardt, Jan.; Ahmed, Fethi B.
Assessment of forest structural attributes has major implications in the management of forestry by providing information of ecological and economic importance. The traditional methods of assessment involve collecting data in the field and are regarded as labour-intensive and expensive. In plantation forestry, field campaigns are generally time consuming and costly, and may compromise profit maximisation. The introduction of lidar (light detection and ranging) remote sensing in forestry has shown promise to add value to the traditional field inventories mainly through large spatial coverages in a timely and cost-effective manner. Lidar remote sensing is an advanced system capable of acquiring information in both the vertical and horizontal dimensions at relatively high resolutions. Numerous studies have established that these qualities of lidar data are suited to estimating forest structural attributes at acceptably high accuracies. The generic approach in most studies is to use lidar data in combination with field data. Such an approach still warrants a high cost of inventory. It is therefore useful to explore alternative methods that rely primarily on lidar data by reducing the necessity for field-derived information. The aim of this study was to derive structural attributes of even-aged Eucalyptus grandis forest plantations using lidar data. The attributes are of significance to timber resource assessments and include plot-level tree height attributes, stems per hectare (SPHA), and volume. The surveyed field data included tree counting and measurement of tree height and diameter at breast height for sample plots. Volume was then calculated using standard allometric models. Small-footprint lidar data of the plantations were also acquired coincident with the field inventories. Mean tree height and dominant height were estimated at a range of simulated lidar point densities between 0.25 points/m2–6 points/m2. Various plot-level distributional metrics were extracted from height values of lidar non-ground points and related with field mean and dominant height values using stepwise regression analysis. The results showed that both attributes could be estimated at high accuracies with no significant differences arising from variations in lidar point density. Estimation of SPHA relied on the exploration of semi-variogram range as a mean window size for applying local maxima filtering to the lidar canopy height surface. A comparative approach of window size determination used pre-determined within-row tree spacing, based on planting information. Two secondary objectives were addressed: comparing spatial resolutions of canopy height surfaces interpolated from non-ground height values and comparison of lidar point densities simulated at three levels. Comparison of spatial resolutions of canopy height surfaces were performed at 0.2 m, 0.5 m, and 1 m using a lidar point density of 5 points/m2. The results indicated that 0.2 m is the most appropriate resolution for locating trees and consequently deriving SPHA. Canopy height surfaces of 0.2 m resolution were created at simulated densities of 1 point/m2, 3 points/m2, and 5 points/m2. While all estimates were negatively biased relative to field-observed SPHA, lidar densities of 3 points/m2 and 5 points/m2 returned similar accuracies, which were both superior to 1 point/m2. It was concluded that 3 points/m2 was sufficient to achieve the accuracy level obtained from higher lidar point densities. Plot-level mean height, dominant height, and volume of trees were estimated for trees located using local maxima filtering approaches at the three lidar point densities. Mean height and dominant height were both estimated at high accuracies for all local maxima filtering techniques and lidar point densities. The results were also comparable to the approach that employed regression analysis that related lidar-derived distributional metrics and field measurements. Estimated dominant height and SPHA, as well as age of trees, were used as independent variables in a function to estimate plot-level basal area. The basal area was then used to compute diameter of the tree with mean basal area, referred to as quadratic mean diameter at breast height (QDBH). Mean tree height and QDBH were used as independent variables in a standard equation to calculate mean tree volume, which was then scaled up to the plot-level. All estimates for the local maxima filtering approaches and lidar point densities returned negatively biased volume, when compared to field observations. This was due to the underestimation of SPHA, which was used as a conversion factor in scaling up from tree-level to plot-level. Volume estimates across lidar point densities exhibited similarities. This suggests that low lidar point densities (e.g., 1 point/m2) have potential for accurate volume estimation. It was concluded that multiple forest structural attributes can be assessed using lidar data only. The accuracy of height derivation meets the standards set by field inventories. The underestimation of SPHA may be comparable to other studies that applied different methods. However, improved estimation accuracy is needed in order to apply the approaches to commercial forestry scenarios. The significance of improving SPHA estimation extends to improved volume estimation. In addition, the potential improvement should also take into consideration the density of lidar points, as this will impact on the cost of acquisition. This research has taken a significant step towards determining if lidar data can be used as a stand-alone remote sensing data source for assessment of structural plantation parameters. Not only does such an approach seem viable, but the lower required point densities will help to reduce acquisition costs significantly.
Designing and implementing a GIS-based cadastral database for land administration in the city of Asmara, Eritrea.
(2004) Gebreslasie, Michael Teweldemedhin.; Ahmed, Fethi B.
The knowledge and application of land information and GIS in Eritrea are very limited and as a result there is a shortage of sufficient, reliable, up-to-date and modem land information for decision-making. This study aimed to develop and design a GIS-based cadastral database for land administration in the city of Asmara, Eritrea. The two components of the cadastral data, the spatial and non-spatial were collected and processed in a GIS environment. GIS-based cadastral data was created to store the data. A recently acquired IKONOS image and existing Auto CAD data were the main sources of data for the study. Geo-rectification, conversion, ,building of topology, spatial adjustment, and digitizing were used' for creating the parcels and roads of Asmara city. A key of relation was created to link both the spatial and non-spatial components of the cadastre. The study used illustrated practical examples to show how GIS-based cadastral data could support land administration as practiced by the different divisions of the Municipal Office of Asmara city. The importance and usage of the cadastral database for urban planners and property valuators were detailed. Spatial and network analysis were used to develop bands for creating a banded property appraisal system for assessing the service catchment area~ of hospitals and the only fire station. Further, a location allocation model was <,I:lso developed to recommend suitable sites for new fire stations in the city of Asmara. It is recommended that the Municipal Office of Asmara adopts the designed GIS-based database. It is also recommended there the major cities in Eritrea follow similar methodology to design and implement cadastre database for their administration.
Estimating foliar and wood lignin concentrations, and leaf area index (LAI) of Eucalyptus clones in Zululand using hyperspectral imagery.
(2006) Mthembu, Ingrid Bongiwe.; Ahmed, Fethi B.
To produce high quality paper, lignin should be removed from the pulp. Quantification of lignin concentrations using standard wet chemistry is accurate but time consuming and costly, thus not appropriate for a large number of samples. The ability of hyperspectral remote sensing to predict foliar lignin concentrations could be utilized to estimate wood lignin concentrations if meaningful relationships between wood and foliar chemistry are established. LAI (leaf area index) is a useful parameter that is incorporated into physiological models in forest assessment. Measuring LAI over vast areas is labour intensive and expensive; therefore, LAI has been correlated to vegetation indices using remote sensing. Broadband indices use average spectral information over broad bandwidths; therefore details on the characteristics of the forest canopy are compromised and averaged. Moreover, the broadband indices are known to be highly affected by soil background at low vegetation cover. The aim of this study is to determine foliar and wood lignin concentrations of Eucalyptus clones using hyperspectral lignin indices, and to estimate LAI of Eucalyptus clones from narrowband vegetation indices in Zululand, South Africa Twelve Eucalyptus compartments of ages between 6 and 9 years were selected and 5 trees were randomly sampled from each compartment. A Hyperion image was acquired within ten days of field sampling, SI and LAI measurements. Leaf samples were analyzed in the laboratory using the Klason method as per Tappi standards (Tappi, 1996-1997). Wood samples were analyzed for lignin concentrations using a NIRS (Near Infrared Spectroscopy) instrument. The results showed that there is no general model for predicting wood lignin concentrations from foliar lignin concentrations in Eucalyptus clones of ages between 6 and 9 years. Regression analysis performed for individual compartments and on compartments grouped according to age and SI showed that the relationship between wood and foliar lignin concentration is site and age specific. A Hyperion image was georeferenced and atmospherically corrected using ENVI FLAASH 4.2. The equation to calculate lignin indices for this study was: L1R= ~n5il: A'''''y . 1750 AI680 The relationship between the lignin index and laboratory-measured foliar lignin was significant with R2 = 0.79. This relationship was used to calculate imagepredicted foliar lignin concentrations. Firstly, the compartment specific equations were used to calculate predicted wood lignin concentrations from predicted foliar lignin concentrations. The relationship between the laboratorymeasured wood lignin concentrations and predicted wood lignin concentrations was significant with R2 = 0.91. Secondly, the age and site-specific equations were used to convert foliar lignin concentration to wood lignin concentrations. The wood lignin concentrations predicted from these equations were then compared to the laboratory-measured wood lignin concentrations using linear regression and the R2 was 0.79 with a p-value lower than 0.001. Two bands were used to calculate nine vegetation indices; one band from the near infrared (NIR) region and the other from the short wave infrared (SWIR). Correlations between the Vis and the LAI measurements were generated and . then evaluated to determine the most effective VI for estimating LAI of Eucalyptus plantations. All the results obtained were significant but the NU and MNU showed possible problems of saturation. The MNDVI*SR and SAVI*SR produced the most significant relationships with LAI with R2 values of 0.899 and 0.897 respectively. The standard error for both correlations was very low, at 0.080, and the p-value of 0.001. It was concluded that the Eucalyptus wood lignin concentrations can be predicted using hyperspectral remote sensing, hence wood and foliar lignin concentrations can be fairly accurately mapped across compartments. LAI significantly correlated to eight of the nine selected vegetation indices. Seven Vis are more suitable for LAI estimations in the Eucalyptus plantations in Zululand. The NU and MNU can only be used for LAI estimations in arid or semi-arid areas.
Estimating leaf area index (LAI) of black wattle (Acacia mearnsii) using Landsat ETM+ satellite imagery.
(2003) Ghebremicael, Selamawit T.; Ahmed, Fethi B.
Leaf area index (LAI) is an important variable in models that attempt to simulate carbon, nutrient, water and energy fluxes for forest ecosystems. LAI can be measured either directly (destructive sampling) or by using indirect techniques that involve estimation of LAI from light penetration through canopies. Destructive sampling techniques are laborious, expensive and can only be carried out for small plots. Although indirect techniques are non-destructive and less time consuming, they assume a random foliage distribution that rarely occurs in nature. Thus a technique is required that would allow for rapid estimation of LAI at the stand level. A means of getting this information is via remotely sensed measurements of reflected energy with an airborne or satellite-based sensor. Such information on an important plant species such as Acacia mearnsii (Black Wattle) is vital as it provides an insight into its water use. Landsat ETM+ images covering four study sites In KwaZulu-Natal midlands encompassing pure stands of Acacia mearnsii were processed to obtain four types of vegetation indices (VIs). The indices included: normalized difference vegetation index (NDVI), ratio vegetation index (RVI), transformed vegetation index (TVI) and vegetation index 3 (VB). Ground based measurements of LAI were made using destructive sampling (actual LAI) and LAI-2000 optical instrument, (plant area index, PAl). Specific leafarea (SLA) and leaf area (LA) were measured in the field for the entire sample stands to estimate their LAI values. The relationships between the various VIs and SLA, actual LAI and PAl values measured by LAI-2000 were evaluated using correlation and regression statistical analyses. Results showed that the overall mean SLA value of Acacia mearnsii was 8.28 m2kg-1 SLA showed strong correlations with NDVI (r=0.71, p
The estimation of Eucalyptus plantation forest structural attributes using medium and high spatial resolution satellite imagery.
(2008) Gebreslasie, Michael Teweldemedhin.; Ahmed, Fethi B.; van Aardt, Jan.
Sustaining the socioeconomic and ecological benefits of South African plantation forests is challenging. A more systematic and rapid forest inventory system is required by forest managers. This study investigates the utility of medium (ASTER 15 m) and high (IKONOS 1-4 m) spatial resolution satellite imageries in an effort to improve the remote capture of structural attributes of even-aged Eucalyptus plantations grown in the warm temperate climatic zone of southern KwaZulu-Natal, South Africa. The conversion of image data to surface reflectance is a pre-requisite for the establishment of relationships between satellite remote sensing data and ground collected forest structural data. In this study image-based atmospheric correction methods applied on ASTER and IKONOS imagery were evaluated for the purpose of retrieving surface reflectance of plantation forests. Multiple linear regression and canonical correlation analyses were used to develop models for the prediction of plantation forest structural attributes from ASTER data. Artificial neural networks and multiple linear regression were also used to develop models for the assessment of plantation forests structural attributes from IKONOS data. The plantation forest structural attributes considered in this study included: stems per hectare, diameter at breast height, mean tree height, basal area, and volume. In addition, location based stems per hectare were determined using high spatial resolution panchromatic IKONOS data where variable and fixed window sizes of local maxima were employed. The image-based dark object subtraction (DOS) model was better suited for atmospheric correction of ASTER and IKONOS imagery of the study area. The medium spatial resolution data were not amenable to estimating even-aged Eucalyptus forest structural attributes. It is still encouraging that up to 64 % of variation could be explained by using medium spatial resolution data. The results from high spatial resolution data showed a promising result where the ARMSE% values obtained for stems per hectare, diameter at breast height, tree height, basal area and volume are 7.9, 5.1, 5.8, 8.7 and 8.7, respectively. Results such as these bode well for the application of high spatial resolution imagery to forest structural assessment. The results from the location based estimation of stems per hectare illustrated that a variable window size approach developed in this study is highly accurate. The overall accuracy using a variable window size was 85% (RMSE of 189 trees per hectare). The overall findings presented in this study are encouraging and show that high spatial resolution imagery was successful in predicting even-aged Eucalyptus forest structural attributes in the warm temperate climates of South Africa, with acceptable accuracy.
An evaluation of the periglacial morphology in the high Drakensberg and associated environmental implications.
(1997) Grab, Stefan Walter.; Hall, Kevin John.; Ahmed, Fethi B.
Although periglacial research in the high Drakensberg and Lesotho mountains has received growing interest amongst southern African geomorphologists, little detailed, quantitative information was available prior to this study. In an attempt to help overcome this deficit, a quantitative assessment on cryogenic landforms and processes operative in the high Drakensberg was undertaken. Morphological and sedimentological assessments of sorted patterned ground, non-sorted steps, thufur, blockstreams, stone-banked lobes, debris deposits and turf exfoliation landforms were undertaken. In addition, geomorphic process assessments in the field included the measurement of turf retreat at turf exfoliation sites, the determination of frost-heave mechanisms within wetlands and sediment mobilization along the Mashai Stream. Ground temperatures were recorded for thufur from 1993 to 1996. The environmental implications of some of the findings are discussed. Seasonal frost-induced sorted patterned ground emerges annually within a few weeks, demonstrating the effect of regular, diurnal freeze-thaw cycles during the winter months. It is found that the present climate is not conducive to maintaining or preserving miniature periglacial landforms below 3200m a.s.l. during the summer months. Large relict sorted circles, stone-banked lobes and blockstreams are the most conspicuous periglacial landforms in the high Drakensberg and are products of at least seasonally-frozen ground. It is suggested that debris deposits found within high Drakensberg cutbacks are possible indicators for marginal niche and cirque glaciation during the Late Pleistocene. It is demonstrated that in climatically marginal periglacial regions, the microtopographically controlled freezing processes may be of paramount importance in maintaining and modifying the cryogenic landforms that occur. Pronounced temperature differentials are found during the winter months, when thufur are frozen for several weeks and depressions remain predominantly unfrozen. It is suggested that such contemporary temperature differentials induce thermodynamic forces and ultimately ground heave at sites in the high Drakensberg. The pronounced seasonal weather patterns in the high Drakensberg have promoted a cycle of geomorphic process events that operate synergistically and initiate particular erosion landforms. However, cryogenic activity during the colder period is overwhelmed by water induced erosion processes during the summer months in the high Drakensberg. It is concluded that the high Drakensberg is currently a marginal periglacial region, but that periglacial conditions prevailed during both the Pleistocene and some Late Holocene Neoglacial events.
An investigation into estimating productivity, above ground biomass and leaf area index of Eucalyptus grandis using remotely sensed data and a process-based model.
(2007) Mzinyane, Thamsanqa Donges.; Ahmed, Fethi B.; Esprey, Luke John.
South Africa depends largely on afforestation programs for its timber supplies due to the great demands for fiber and wood products. This has brought discomfort to other water users who have advocated that the effects of afforestation on water resources are detrimental to the country as a whole since South Africa is known as a water scarce country. This study has undertaken to integrate a process-based model and remote sensing data to estimate water use and productivity of Eucalyptus grandis in the Zululand areas of South Africa. The remote sensing techniques and recently developed "process based model" that is 3PG-S were used to estimate water use and productivity of Eucalyptus grandis, an economically important plantation species grown in the summer rainfall areas of South Africa. The study utilized monthly Landsat Thematic Mapper datasets and climatic data as inputs into the 3PG-S model, determined the Leaf Area Index (LAI) and Specific Leaf Area (SLA) through direct (destructive sampling) and indirect measurements (LiCor- 2000) and assessed the relationships between various vegetation indices (VI's) using correlation and regression analyses. The results suggest that all the indices, except the ratio VI, correlated significantly with LiCor-determined and destructively measured LAI values with both normalized difference vegetation index (NDVI) and Ratio Vegetation Index (RVI) (r=0.86, p
An investigation into land capability classification in Eritrea : the case study of Asmara city environs.
(2004) Tesfagiorgis, Girmai Berhe.; Ahmed, Fethi B.
The problems of land resources degradation as a result of misuse of arable land for non agricultural development and lack of appropriate methods and guidelines for land resources assessment are currently evident in Eritrea. These problems, have called for an urgent need for an appropriate land resources assessment in Eritrea. In response to this, a land capability classification in the areas around Asmara city that covers about 11742.7 ha was conducted. The intended aim was to properly assess the potential of the land resources in the study area and classify the capability of the land so as to designate the land according to its capability and foster appropriate land use. All the available natural resources in the study area were carefully assessed. A detailed soil survey was conducted and soil units were examined, described, classified and mapped out. Several criteria for the limitations were selected from the reviewed literature mainly USDA and RSA Land Capability Classification systems and in consultation with the soil survey and natural resources experts of the Ministry of Agriculture in Eritrea. In formation on land and soil characteristics, and the specified limitations and criteria were captured in a spatial digital format and then analysed within a GIS. Based on the specified parameters, different land capability units, subclasses, classes and orders were identified and mapped out. Finally, the sub classes were grouped to create,land capability classes ranging from Class I to Class VII and consequently the capability classes were grouped and mapped out at the level of land capability orders. The results revealed seven land capability classes (Class I to VII). Class III land in the study area covers 4149.43 ha (36.9 percent of the total area). The largest portion of this class is found in the central, southern and south eastern parts of the study area. However, classes I and II are very limited and cover 1562.95 ha (13.9 percent) of the study area. These classes are found mainly in the southern and central parts of the study area. Most of the gentle and steep sloping lands in the north and north eastern parts of the study area are classified as classes IV and VI. These classes have an area of 2652.08 ha (23.6 percent) and 2594.87 ha (23.1 percent) of the study area, respectively. Classes V and VII are very limited. These classes cover 221.53 ha (2 percent) and 57.55 ha (0.5 percent), respectively. The largest portion of class V land is found in the central part of the study area. Class VII land is mainly confined to the north eastern, western and southern corners of the study area. Four land capability orders were arrived at ranging from (high to moderate potential to non-arable land). The high to moderate potential arable lands are largely found in the southern and central parts of the study area. These lands cover 5715.39 ha (50.8 percent) of the study area. However, low potential arable (marginal productive) and non-arable lands have a considerable area of 2652.08 ha (23.6 percent) and 2652.42 ha (23.1 percent) of the study area, respectively. The largest portion of these lands is found in the north, north eastern and eastern parts of the study area. A small portion of the lands in the study area is classified as seasonally wetland. This land has an are~\ of 221.53 h~{2 percent) of the study area and is mainly found in the central part of the study area. It was concluded that nearly 50 percent of the land in the study area is classified as of moderately to high agricultural potential whereas the rest of the land is classified as marginal to non-arable land. However, the steady growth of demand for land for nonagricultural development due to the increasing population that depend on farm production in the study area, renders the prime arable lands as too limited to support the current population in the study area. Hence, protecting the prime arable lands and properly using such lands based on their sustained capacity can only secure the livelihood of the community.
An investigation into using textural analysis and change detection techniques on medium and high spatial resolution imagery for monitoring plantation forestry operations.
(2006) Norris-Rogers, Mark.; Van Aardt, Jan.; Ahmed, Fethi B.; Coppin, P. R.
Plantation forestry involves the management of man-made industrial forests for the purpose of producing raw materials for the pulp and paper, saw milling and other related wood products industries. Management of these forests is based on the cycle of planting, tending and felling of forest stands such that a sustainable operation is maintained. The monitoring and reporting of these forestry operations is critical to the successful management of the forestry industry. The aim of this study was to test whether the forestry operations of clear-felling, re-establishment and weed control could be qualitatively and quantitatively monitored through the application of classification and change detection techniques to multi-temporal medium (15-30 m) and a combination of textural analysis and change detection techniques on high resolution (0.6-2.4 m) satellite imagery. For the medium resolution imagery, four Landsat 7 multi-spectral images covering the period from March 2002 to April 2003 were obtained over the midlands of KwaZulu-Natal, South Africa, and a supervised classification, based on the Maximum Likelihood classifier, as well as two unsupervised classification routines were applied to each of these images. The supervised classification routine used 12 classes identified from ground-truthing data, while the unsupervised classification was done using 10 and 4 classes. NDVI was also calculated and used to estimate vegetation status. Three change detection techniques were applied to the unsupervised classification images, in order to determine where clear-felling, planting and weed control operations had occurred. An Assisted "Classified" Image change detection technique was applied to the Ten-Class Unsupervised Classification images, while an Assisted "Quantified Classified" change detection technique was applied to the Four-Class Unsupervised Classification images. An Image differencing technique was applied to the NDVI images. For the high resolution imagery, a series of QuickBird images of a plantation forestry site were used and a combination of textural analysis and change detection techniques was tested to quantify weed development in replanted forest stands less than 24 months old. This was achieved by doing an unsupervised classification on the multi-spectral bands, and an edge-enhancement on the panchromatic band. Both the resultant datasets were then vectorised, unioned and a matrix derived to determine areas of high weed. It was found that clear-felling operations could be identified with accuracy in excess of 95%. However, using medium resolution imagery, newly planted areas and the weed status of forest stands were not definitively identified as the spatial resolution was too coarse to separate weed growth from tree stands. Planted stands younger than one year tended to be classified in the same class as bare ground or ground covered with dead branches and leaves, even if weeds were present. Stands older than one year tended to be classified together in the same class as weedy stands, even where weeds were not present. The NDVI results indicated that further research into this aspect could provide more useful information regarding the identification of weed status in forest stands. Using the multi-spectral bands of the high resolution imagery it was possible to identify areas of strong vegetation, while crop rows were identifiable on the panchromatic band. By combining these two attributes, areas of high weed growth could be identified. By applying a post-classification change detection technique on the high weed growth classes, it was possible to identify and quantify areas of weed increase or decrease between consecutive images. A theoretical canopy model was also derived to test whether it could identify thresholds from which weed infestations could be determined. The conclusions of this study indicated that medium resolution imagery was successful in accurately identifying clear-felled stands, but the high resolution imagery was required to identify replanted stands, and the weed status of those stands. However, in addition to identifying the status of these stands, it was also possible to quantify the level of weed infestation. Only wattle (Acacia mearnsii) stands were tested in this manner but it was recommended that in addition to applying these procedures to wattle stands, they also are tested in Eucalyptus and Pinus stands. The combination of textural analysis on the panchromatic band and classification of multi-spectral bands was found to be a suitable process to achieve the aims of this study, and as such were recommended as standard procedures that could be applied in an operational plantation forest monitoring environment.
A land suitability evaluation for improved subsistence agriculture using GIS : the case study of Nkwezela, KwaZulu-Natal, South Africa.
(2007) Ebrahim, Fazal.; Ahmed, Fethi B.
Rural farmers in the Nkwezela Area, with an average family size of 10 people, face a number of problems. The crops that are predominantly cultivated in the area, for subsistence (maize, dry beans, sorghum, potatoes, cabbages and turnips) have very low yields compared to the potential yield of the land. Natural resources in the area are increasingly deteriorating. In addition, arable land has shown remarkable signs of soil erosion that may lead to loss of soil fertility. This study evaluates the current land suitability for subsistence agriculture in Nkwezela based on climatic, soil, topographic and crop requirement data collected from different sources. The spatial parameters of the land resources were digitally encoded into a GIS database to create thematic layers of the land resources which was then compared to the crop requirement data of the selected crops grown in Nkwezela namely, maize, sorghum, dry beans, potatoes, cabbages and turnips. A GIS was used to overlay the thematic layers of the resources to select areas that satisfied the crop requirements of the selected crops. The results of the analysis of the land evaluation in the study area showed that the very hot summers, very cold winters together with the high clay content in the soils are the two limiting factors in Nkwezela. The land suitability maps indicate that sorghum is highly suitable in the area with dry beans and maize being relatively suitable. Cabbages are the least the least adapted crop with potatoes and turnips being not suitable due to the high temperatures during the growing season and the very cold winters. In conclusion Nkwezela is in a high rainfall area that is suitable for subsistence agriculture where warm season crops like dry beans, maize and sorghum are used for daily consumption by the community and can be cultivated in a sustainable manner. In addition the correct farming methods, procedures, liming and fertiliser requirements must be implemented, adhered to and maintained in order to improve crop yields in a sustainable manner and to encourage subsistence agriculture by the community.
Land suitability evaluation for rainfed agriculture using GIS : the case study of Weenen Nature Reserve, KwaZulu-Natal, South Africa.
(2003) Ghebremeskel, Legesse Abraham.; Ahmed, Fethi B.
Weenen Nature Reserve (WNR) has a long history of unwise land use that resulted in severe overgrazing and soil degradation. Since 1948 several soil conservation and reclamation programs have been undertaken to halt the degradation process and regain the agricultural potential of the area. This study evaluates the current agricultural potential of the reserve under rainfed cultivation primarily based on climatic, soil, topographic and crop requirement data collected from different sources. Spatial information on each of the land resources parameters was digitally encoded in a GIS database to create thematic layers of the land resources. Crop requirement information on seven different crops that were selected as representative crops under rainfed agriculture in the area namely, maize, Sorg):mm, cotton, dry bean, soya bean, potato and cabbage was compared with the land resources parameters. The thematic layers of the land resources were then overlyed using a GIS to select areas that satisfy the crop requirements. The results showed that WNR has two major limitations in relation to its use for rainfed agriculture, namely its shallow and rocky soils and its arid climate. Consequently, the resulting land suitability maps indicate that WNR has very low suitability for all of the crops considered. Dry beans are relatively well adapted to the area followed by sorghum. Maize and soya beans are preferred over cotton. Potatoes'and cabbages are least adapted to the area because of the high temperatures during thCl/growing season. It was concluded that generally the reserve is not suitable for rainfed agriculture. However, there is a small area of land in the northern part of the reserve that can be cultivated. The rugged area in the central part of the reserve can be used for grazing with careful managemeIit. The eastern and southern parts can only be used as habitats for wildlife owing to their steep topography and inaccessibility, whereas the highly degraded areas in the western parts of the reserve should be kept under soil conservation and reclamation.
Mapping potential soil erosion using rusle, remote sensing, and GIS : the case study of Weenen Game Reserve, KwaZulu-Natal.
(2004) Tesfamichael, Solomon Gebremariam.; Ahmed, Fethi B.; Abib, Essack.
Accelerated soil erosion is drawing a growing attention with the recognition that the rate of soil loss is too great to be met by soil formation rate. Weenen Game Reserve (WGR) is an area with an unfortunate history of prolonged soil erosion due to excessive overgrazing that led to severe land degradation with prominent visible scars. This problem triggered the general objective of estimating and mapping potential soil erosion in WGR. Assessing soil loss in the area objectively has important implications for the overall management plans as it is reserved for ecological recovery. The most important variables that affect soil erosion are considered as inputs in soil loss estimation models. In this study the RUSLE model, which uses rainfall, soil, topography, and cover management data, was employed. From the rainfall data, an erosivity factor was generated by using a regression equation developed by relating EI30 index and total monthly rainfall. The soil erodibility factor was calculated using the soil erodibility nomograph equation after generating the relevant data from laboratory analysis of soil samples gathered from the study area. Using exponential ordinary kriging, the point values of this factor were interpolated to fill in the non-sampled areas. The topographic effect, which is expressed as the combined impact of slope length and slope steepness, was extracted from the DEM of the study area using the flow accumulation method. For mapping of the land cover factor, in situ measurements of cover from selected sites were undertaken and assigned values from the USLE table before being related with MSAVI of Landsat 7 ETM+ image. These values were then multiplied to get the final annual soil loss map. The resulting potential soil loss values vary between 0 and 346 ton ha-1 year-l with an average of 5 ton ha-1 year-l. About 58% of the study area experiences less than 1 ton ha-1 year-1 indicating the influence of the highest values on the average value. High soil erosion rates are concentrated in the central part extending as far as the south and the north tips along the eastern escarpments and these areas are the ones with the steepest slopes. The results indicate a high variation of soil loss within the study area. Nevertheless, the majority of the area falling below the average might foresee that the soil erosion problem of the area can be minimized significantly depending largely on soil management. The most important areas for intervention are the medium and low erosion susceptible parts of WGR, which are mainly found in the flatter or gently sloping landscapes. The steepest areas are mostly covered with rocks and/or vegetation and hence less effort must be spent in managing them. Overall, the reported increasing density of the vegetation community in the area that reduces the exposure of soil from the impact of direct raindrops and surface-flowing water must be pursued further.
The potential for using remote sensing to quantify stress in and predict yield of sugarcane (Saccharun spp. hybrid)
(2010) Abdel-Rahman, Elfatih Mohamed.; Ahmed, Fethi B.; Van den Berg, Maurits.
South Africa is the leading producer of sugarcane in Africa and one of the largest sugarcane producers in the world. Sugarcane is grown under a wide range of climatic, agronomic, and socio-economic conditions in the country. Stress factors such as water and nutrient deficiencies, and insect pests and diseases are among the most important factors affecting sugarcane production in the country. Monitoring of stress in sugarcane is therefore essential for assessing the consequences on yield and for taking action of their mitigation. The prediction of sugarcane yield, on the other hand is also a significant practice for making informed decisions for effective and sound crop planning and management efforts regarding e.g., milling schedules, marketing, pricing, and cash flows. In South Africa, the detection of stress factors such as nitrogen (N) deficiency and sugarcane thrips (Fulmekiola serrata Kobus) damage and infestation are made using traditional direct methods whereby leaf samples are collected from sugarcane fields and the appropriate laboratory analysis is then performed. These methods are regarded as being time-consuming, labour-intensive, costly, and can be biased as often they are not uniformly applied across sugarcane growing areas in the country. In this regard, the development of systematically organised geo-and time-referenced accurate methods that can detect sugarcane stress factors and predict yields are required. Remote sensing offers near-real-time, potentially inexpensive, quick and repetitive data that could be used for sugarcane monitoring. Processing techniques of such data have recently witnessed more development leading to more effective extraction of information. In this study the aim was to explore the potential use of remote sensing to quantify stress in and predict yield of sugarcane in South Africa. In the first part of this study, the potential use of hyperspectral remote sensing (i.e. with information on many, very fine, contiguous spectral bands) in estimating sugarcane leaf N concentration was examined. The results showed that sugarcane leaf N can be predicted at high accuracy using spectral data collected using a handheld spectroradiometer (ASD) under controlled laboratory and natural field conditions. These positive results prompted the need to test the use of canopy level hyperspectral data in predicting sugarcane leaf N concentration. Using narrow NDVI-based vegetation indices calculated from Hyperion data, sugarcane leaf N concentration could reliably be estimated. In the second part of this study, the focus was on whether leaf level hyperspectral data could detect sugarcane thrips damage and predict the incidence of the insect. The results indicated that specific wavelengths located in the visible region of the electromagnetic spectrum have the highest possibility of detecting sugarcane thrips damage. Thrips counts could also adequately be predicted for younger sugarcane crops (4–5 months). In the final part of this study, the ability of vegetation indices derived from multispectral data (Landsat TM and ETM+) in predicting sugarcane yield was investigated. The results demonstrated that sugarcane yield can be modelled with relatively small error, using a non-linear random forest regression algorithm. Overall, the study has demonstrated the potential of remote sensing techniques to quantify stress in and predict yield of sugarcane. However, it was found that models for detecting a stress factor or predicting yield in sugarcane vary depending on age group, variety, season of sampling, conditions at which spectral data are collected (controlled laboratory or natural field conditions), level at which remotely-sensed data are captured (leaf or canopy levels), and irrigation conditions. The study was conducted in only one study area (the Umfolozi mill supply area) and very few varieties (N12, N19, and NCo 376) were tested. For practical and operational use of remote sensing in sugarcane monitoring, the development of an optimum universal model for detecting factors of stress and predicting yield of sugarcane, therefore, still remains a challenging task. It is recommended that models developed in this study should be tested – or further elaborated – in other South African sugarcane producing areas with growing conditions similar to those under which the predictive models have been developed. Monitoring of sugarcane thrips should also be evaluated using remotely-sensed data at canopy level; and the ability of multispectral sensors other than Landsat TM and ETM+ should be tested for sugarcane yield prediction.
Unemployment in South Africa : in search of a spatial model.
(2015) Weir-Smith, Gina.; Ahmed, Fethi B.; Maharaj, Bridgemohan.
Consistent high unemployment perpetuates inequalities in the South African society. The 2014 growth expectation for the South African economy is 1.5 per cent and this will most certainly not be enough to reduce unemployment. This research aimed to create an understanding of the spatial intricacies related to unemployment and to create a longitudinal dataset since 1991. The challenge with such a dataset is that boundaries of the enumeration and administrative areas have changed continually in the past and makes it difficult to compare unemployment spatially over time. These particular problems were addressed by aggregating data for 1991 and 1996 census from magisterial districts to the 2005 municipal boundaries. Area based weighted areal interpolation was used and it assumes that data is distributed homogeneously across the area of each source unit. The 2001 census and 2007 community survey data was available at the 2005 municipal level, and therefore a longitudinal socio-economic dataset of four time points could be created. The results showed that unemployment has been spatially persistent in a number of areas. Furthermore, a spatial grouping of unemployment by municipality showed that metropolitan municipalities had unique unemployment characteristics whereas the remainder of the country could be clustered into five distinct groups. A spatial comparison between unemployment and poverty at municipality level revealed that people can be poor and unemployed, but also poor and employed. Finally, the longitudinal data was used to do spatial forecasting of future unemployment trends and these accounted for up to 60 per cent of change in unemployment. These national and provincial spatial unemployment models consisted of coefficients like the percentage of people employed in mining and agriculture. This research added new knowledge in terms of the spatio-temporal understanding of unemployment in South Africa. It created a methodology to overcome modifiable areal unit problems (MAUP) and a longitudinal dataset of unemployment and related socio-economic variables. Refined spatial data was this research’s main challenge and it recommends that unemployment data should be released at the most detailed spatial level possible - like sub-place or enumeration areas. The quality and timeliness of data remain obstacles for policy-making. Therefore, labour market data at a sub-place level would provide a more meaningful analysis. The results from census 2011 will allow the creation of longitudinal socio-economic trends at a spatially detailed level in South Africa in the future.
The use of spatial analysis and participatory approaches in strategic environmental assessment (SEA) : identifying and predicting the ecological impacts of development on the KwaZulu-Natal North Coast of South Africa.
(2010) Ahmed, Fathima.; Bob, Urmilla.; Ahmed, Fethi B.
The high pressures for coastal development, translated as prolific land cover transformation, coupled with the weaknesses of management to protect the environment has led to the gradual deterioration of environmental conditions in many coastal areas. Land use decisions in coastal areas are based on opportunities and constraints affected by both biophysical and socio-economic drivers, and hence present one of the main issues integrating the large debate on sustainable development in coastal zones (Lourenço and Machado, 2007: 1). The aim of this study is to investigate the effectiveness of the integration of spatial analysis and participatory approaches in SEA (particularly its ability to identify and predict ecological impacts) on the KwaZulu-Natal north coast of South Africa. The study adopted a conceptual framework based on landscape ecology, which was underpinned within the overarching political ecology framework. The former underscores the importance of integration, while the latter critiques the institutionalization of environmental concerns, which are characterized by inequalities in terms of social and political power and of how problems are defined, mediated and resolved. Hence this conceptual framework was considered appropriate to assess the strategic environmental issues pertaining to the coastal zone on the KwaZulu-Natal north coast. The researcher used participatory methods, primarily focus group discussions (which included venn diagramming, ranking exercises and participatory mapping) which were triangulated with both quantitative and qualitative methods as part of an integrated impact assessment. These relate to the use of semistructured questionnaires which were administered to a purposive sample of six key stakeholder interest groups within the study area. A spatial GIS time series analysis of land use and cover change was employed to determine baseline conditions, changes in the state of key ecosystems, key development drivers and emerging threats. Additionally, a policy and institutional review was undertaken. The analysis revealed that major natural land cover classes are in decline in the study area,within a time period of less than 10 years. The most sensitive ecosystems were found to be grasslands (-19.99%), coastal forest (-40%), wetlands (-37.49%) and secondary dunes (- 21.44%). Furthermore, agriculture and forestry are also indicating severe declines. The reasons attributed to this transformation of land cover are increasingly being linked with economic motives such as individual private land-owner dynamics, tourism growth and development in the area. Furthermore, the policy agendas are clearly economically motivated. These losses signify the cumulative decline in ecosystem goods and services, and could undermine pose risks to the society that relies on them either directly or indirectly. One of the main considerations in this research endeavor was to formulate a Strategic Environmental Assessment (SEA) Framework to inform future ICZM in the study area. SEA is planning with a long-term perspective, with a focus on a spatial rather than a project level, an element that is clearly lacking in the current development scenario of this coastline. It is critical that the SEA Framework advocated in this study include a range of variables that will permit short-term, medium-term and long-term monitoring and evaluation aimed at ensuring sustainable planning in the area.

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