Masters of Science / Over the years, South Africa has produced over 468 million tons of mine waste yearly, in which gold mining waste accounted for 221 million tons (47%) of all mine waste produced, making it the largest, single source of waste and pollution. The exposure of these mine wastes such as tailings dams, waste rocks to oxidation and leaching has been the source of heavy metal release into the environment. This study assessed the magnitude of possibly leachable metals, its distribution and associations and predicted the AMD load discharge over time, from Mogale’s tailings dam into the environs in Randfontein area, Witwatersrand Basin, South Africa. Fifty-one tailings dam samples were analysed for their mineral and multi-elements contents. Petrography studies was done by X-Ray Diffraction (XRD) technique to determine the mineralogical composition. X-ray fluorescence (XRF) and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) techniques were used to determine the multi-elements content in the tailings dam samples. The dataset were evaluated using multivariate statistics, Geographical Information Systems (GIS) and geochemical mass balance techniques. From the results, the tailings dam lithology was grouped into four distinct layers. The uppermost oxidized layer is siliceous and contains the highest SiO2 (87.32%) contents, which is with the lowest contents in Tot/S, U, As, Zn, Ni, Co, and Cu. A downward decrease in SiO2 (76.39%) contents occurs, coupled by an increase in Fe2O3, Tot/S, U, As, Zn, Ni, Co, and Cu, reaching maximum contents in layer 3. Layer 4 is the least weathered horizon. The cluster analysis grouped the samples into four sub-clusters based on the variation in SiO2 and Al2O3 contents. Factor analysis (83.542% total data variance) related the four controlling factors of element distribution to the occurrence in ore elements (sulphides), silicates, mining additives and refractory minerals. Elements of the same origin show a similar concentration trend down hole in the GIS interpolation analysis. The geochemical mass balance showed variable gain and loss of oxides and trace elements within each layer. Based on the variation patterns of the Tot/S contents and other mobile elements, about 0.164kg/tonne/yr(±0.02) of the tailings materials are leached yearly. Layer 1 is the most altered. This assessment and prediction study therefore gives an insight to the geochemical behaviour of an abandoned tailings dam, highlighting its extent of oxidation. However, the interaction between the oxidized zone and transition zone should be given more attention, to determine the actual extent of damage.

The research presented in this Thesis is primarily concerned with the field of Geographical Information Systems (GIS) - specifically, the business applications of the technology. The empirical problem addressed is the selection of branch banks as candidates for closure using the network of branch banks of the Commonwealth Bank of Australia in the Sydney metropolitan region as the case study. Decisions to close branches are made by the Bank on the basis of performance indicators that are essentially financial. In this research, however, an alternative approach is adopted: the problem is addressed using a set of spatial criteria. Following the deregulation of the finance industry in the 1980's and the rapid introduction of new electronic channels for delivering financial services, the major banking institutions have been engaged in a process of reorganising their networks of branch banks. The most visible manifestation of this has been the ongoing and widespread closure of branches. Selecting branch banks for closure is a typical example of a complex semi-structured multi-dimensional, multi-criteria, decision-making problem. It has been well documented in previous research that Multi-Criteria Decision-Making (MCDM) models are the most appropriate ones for solving problems in this particular domain. The identification of branches for closure is also characterised by a significant spatial dimension. Decisions are based on a consideration of a number of geographical criteria and various forms of spatial analysis may be involved. An appropriate technology to assist with solving decision-making problems with a significant spatial dimension is a Spatial Decision Support System (SDSS). Most SDSS have been based on the integration of Geographical Information Systems (GIS) technology with analytical models that are proven to be best suited to specific decision-making problems and this is the approach adopted in this research. The prototype MCBC-SDSS (Multi-Criteria Branch Closure SDSS) developed here is based on the integration through the loose coupling of the ArcView GIS software with the Criterium DecisionPlus (CDP) software, which contains the suite of non-spatial analytical models that provide the analytical capability for solving multi-criteria problems. ArcView GIS is used as the engine that drives the system and to provide the analytical and display facilities to support the spatial data involved. Two MCDM models from the CDP software are used to support the decision-making analysis - the Analytical Hierarchy Process (AHP) and Simple Multi-Attribute Rating Technique (SMART). The integration of GIS with the MCDM models is based on a considerable amount of software enhancement, interface development, and computer programming. The development of the integrated system is designed to create an intelligent and user-friendly SDSS, the application of which, from the user's perspective, is a seamless operation. The success of the MCBC-SDSS is demonstrated by its application to identify candidates for closure among the 197 branches of the CBA in the Sydney metropolitan area in 2000 - the year when the building of the database for the research had been completed. The analysis is based purely on spatial considerations that have been gleaned from a major review of the literature that previous researchers have identified as affecting branch viability and performance. A set of 17 spatial variables was used as the criteria in the MCDM models. The criteria are organised in two blocks: the first includes 9 criteria relating to the characteristics of demand for branch service in the branch trade areas ('catchment area' specific criteria) while the second includes 8 criteria relating to aspects of supply provided by the existing branches in their location ('location specific' criteria). Using the developed approach, the MCBC-SDSS has been used directly to compare alternatives against criteria, not only spatial based but also financial ones, thus providing a basis for identifying the best choices regarding branch closure. The steps in the preparation of the data and the iterative procedure for implementing the MCDM models are explained and illustrated. This involves building the initial evaluation matrix, normalising the raw criteria scores, assigning weights to the criteria, and calculating priorities. Based on these, the AHP and SMART models then calculate a decision score for each branch that is used as the basis for creating the preference ranking of the branches. In this, branches with a high rank score based on the combined weighted contribution of the 17 criteria are considered to be operationally viable. On the other hand, branches with the lowest rank scores are considered as potential candidates for closure. The preference rankings generated by the models have been tested to examine their robustness in terms of the validity of criteria and their weights used in the decision analysis. Sensitivity analysis has been conducted, the results of which show that the preference rankings are stable. Different approaches have been used to validate the initial criteria, and analyse their contribution to the ranking of branch banks for closure. These help identify critical spatial variables among the 17 initial criteria selected, and suggest that some of the criteria initially selected could be deleted from the criteria list used to generate the preference rankings without substantially affecting the results. The reasonableness of the resulting preference ranking has been further demonstrated from analyses based on changing criteria weights and alternatives. The research successfully demonstrates one of the ways of enhancing the functionality of a GIS through its integration with non-spatial analytical models to develop a SDSS to aid solving decision-making problems in the selected domain. Given that to date there has been relatively few applications of SDSS similar to that developed in this research to real world decision-making problems, the procedure adopted makes it suitable for decision-making in a range of other service business applications characterised by a significant spatial dimension and multiple outlets including shopping centres, motor car dealerships, restaurant and supermarket chains. Instead of just providing solutions, however, the SDSS-based analysis in this research can better be thought of as adding value to spatial data that forms an important source of information required by decision-makers, providing insight about the situation, uncertainty, objectives, and trade-offs involved in reaching decisions, and being capable of generating alternative scenarios based on different inputs to the models that may be used to identify recommended courses of action. It can lead to better and more effective decision-making in institutions involving multi-outlet retail and service businesses and hence enables both integrated data analysis and modelling while taking multiple criteria and decision-makers' preferences into consideration.

This thesis is structured around the analysis of a model that describes the Cantonment, the Civil Lines, the Sadr Bazar and part of the Native City of the Western Indian settlement of Poona in the late nineteenth and early twentieth centuries.

<p>Since Dengue fever (DF) and its related forms, Dengue Hemorrhagic fever (DHF) and Dengue Shock Syndrome (DSS) have become important health concerns worldwide, it is also imperative to develop methods which will help in the analysis of the incidences. Dengue fever cases are growing in number as it also invades widely, affecting larger number of countries and crossing climatic boundaries. Considering that the disease as of now has neither an effective vaccine nor a cure, monitoring in order to prevent or control is the resorted alternative. GIS and its related technologies offer a wealth of interesting capabilities towards achieving this goal.</p><p><strong> </strong></p><p>The intention of this study was to develop methods to describe dengue fever outbreaks taking Rio de Janeiro, Brazil as a case study. Careful study of Census data with appropriate attributes was made to find out their potential influence on dengue fever incidence in the various regions or census districts. Dengue incidence data from year 2000 to year 2008 reported by the municipal secretariat of Rio was used to extract the necessary census districts. Base map files in MapInfo format were converted to shape files.  Using ArcGIS it was possible to merge the dengue fever incidence data with the available base map file of the City of Rio according to corresponding census districts. Choropleth maps were then created using different attributes from which patterns and trends could be used to describe the characteristic of the outbreak with respect to the socio-economic conditions. Incidence data were also plotted in Excel to see temporal variations. Cluster analysis were performed with the Moran I technique on critical periods and years of dengue outbreak. Using the square root of dengue incidence from January to April 2002 and 2008, inverse distance was selected as the conceptualised spatial relationship, Euclidean distance as the distance method. More detailed analyses were then done on the selected critical years of dengue outbreak, (years 2002 and 2008), to investigate the influence of socio-economic variables on dengue incidence per census district.</p><p> </p><p>Dengue incidence rate appeared to be higher during the rainy and warmer months between December and May. Outbreaks of dengue occurred in years 2002 and 2008 over the study period of year 2000 to 2008. Some factors included in the census data were influential in the dengue prevalence according to districts. Satisfactory results can be achieved by using this strategy as a quick method for assessing potential dengue attack, spread and possible enabling conditions. The method has the advantage where there is limited access to field work, less financial means for acquisition of data and other vital resources.</p><p>A number of difficulties were encountered during the study however and leaves areas where further work can be done for improvements. More variables would be required in order to make a complete and comprehensive description of influential conditions and factors.  There is still a gap in the analytical tools required for multi-dimensional investigations as the ones encountered in this study.  It is vital to integrate ‘GPS’ and ‘Remote Sensing’ in order to obtain a variety of up-to-date data with higher resolution.</p><p> </p>

<p>In this thesis work, we compare the results obtained from two kinds of teams forming a hierarchical organization participating in a fire fighting simulation environment called as C3Fire. First kind of teams used paper-based maps for spatial reasoning of the command tool while the other kind of teams has GIS based maps with full access to positioning data of the fire fighting units as well as sensor information about fire break.</p><p>The collected data was from 11 teams of each kind having 6 members in each team making a total of 132 participants belonging to different parts of the world.</p><p>We made a statistical analysis on the data with help of T-Test statistical medhod and a tool is designed by using Java as programming language and PostgreSQL database for importing data from log files and then applying statistical T-Test method on the fetching data from log files.The results are stored in database as well as excel files. Then a comparison is done to analyze the unit performance, communication and efficiency of both kinds of teams.</p>

<p>Command and control is central in all distributed tactical operations such as rescue operations and military operations. It takes place in a complex system of humans and artefacts, striving to reach common goals. The command and control complexity springs from several sources, including dynamism, uncertainty, risk, time pressure, feedback delays and interdependencies. Stemming from this complexity, the thesis approaches two important and related problem areas in command and control research. On a general level, the thesis seeks to approach the problems facing the command and control operators and the problems facing the designers in the associated systems development process.</p><p>We investigate the specific problem of operators losing sight of the overall perspective when working with large maps in geographical information systems with limited screen area. To approach this problem, we propose high-precision input techniques that reduce the need for zooming and panning in touch-screen systems, and informative unit representations that make better use of the screen area available. The results from an experimental study show that the proposed input techniques are as fast and accurate as state-of-the-art techniques without the need to resort to zooming. Furthermore, results from a prototype design show that the proposed unit representation reduces on-screen clutter and makes use of off-screen units to better exploit the valuable screen area.</p><p>Developing command and control systems is a complex task with several pitfalls, including getting stuck in exhaustive analyses and overrated reliance on rational methods. In this thesis, we employ a design-oriented research framework that acknowledges creative and pragmatic ingredients to handle the pitfalls. Our approach adopts the method of reconstruction and exploration of mission histories from distributed tactical operations as a means for command and control analysis. To support explorative analysis of mission histories within our framework, we propose tools for communication analysis and tools for managing metadata such as reflections, questions, hypotheses and expert comments. By using these tools together with real data from live tactical operations, we show that they can manage large amounts of data, preserve contextual data, support navigation within data, make original data easily accessible, and strengthen the link between metadata and supporting raw data. Furthermore, we show that by using these tools, multiple analysts, experts, and researchers can exchange comments on both data and metadata in a collaborative and explorative investigation of a complex scenario.</p> / Report code: LiU-Tek-Lic-2004:61.

This thesis presents an assessment of the variation in solifluction occurrence, morphometry and movement rates in the Abisko region, northern Sweden. Variations in movement rates are analyzed both on a regional and local scale. The main methodological contributions of this thesis have been to provide new techniques of analyzing spatial and temporal variations of solifluction in order to detect long term temporal trends and to regionalize the variations in movement rates. The spatial analysis is achieved by using a combination of field measurements, GIS and remote sensing techniques and statistical analysis. The results are presented in six papers, focusing on the morphometry of solifluction landforms (paper I), the occurrence of permafrost (paper II), the spatial and temporal variations of lobe front movement rates using aerial photographs (paper III), the temporal, regional and local spatial variations in movement rates (paper IV – VI) and statistical modelling of the occurrence of solifluction landforms and calculation of geomorphic work (paper V and VI). The results show that, on a regional scale, vegetation patterns are a major control on the occurrence of turf-banked solifluction landforms, with high NDVI-values (vegetation) associated with the presence of forms. Elevation is also a major control on a regional scale with a decrease in lobe dimensions and movement rates with increased elevation. High soil moisture values are associated with larger landforms and increased movement rates. Movement rates are generally higher in the western part of the region and appear to increase with higher MAAT. Equally, geomorphic work is greatest in the western part of the region. The important controls on a local scale vary from site to site, but include vegetation, slope angle and soil moisture. The photo analysis indicates that annual movement rates of lobe fronts in Kärkevagge and Låktatjåkka valley over the period 1959-2000 ranges from not-detectable to 63mm/yr. The permafrost model shows probabilities &gt;0.8 for permafrost at elevations above 1300 m a.s.l. in the western part of the region, decreasing to altitudes over 850 m a.s.l. in the eastern part of the region. Calculated geomorphic work suggests that solifluction is a significant denudational agent in the sub-Arctic mountains of northern Sweden, but less so than previously estimated.

This study aims to develop a method to investigate the relationship between settlement locations and the morphological landforms using geographical information systems (GIS). The method is applied to &Ccedil / ankiri province, a mountainous terrain, which is covered in seventy-seven sheets of topographic maps at 1:25.000 scale. Three databases are created and used in this study: 1) Settlement database comprising various topographic and landform attributes of 891 settlements, 2) Morphological landform database composed of 4042 landform polygon elements digitized from 1:25.000 topographic maps, and 3) Topographic database containing the digital elevation model of the area and its derivatives. The first step in the algorithm is to classify the area into four main landform classes, namely, valley, slope, flood and top. Unsuitable landforms are then clipped out based on the thresholds derived from three topographic properties (elevation, slope and aspect). Accordingly, about 2 % of the settlements and 12 % of the area are removed. The relationship is investigated using the percentages of remaining settlements and landform classes. Further analyses such as position of the settlement within the landform polygon and type of the nearest landforms are carried out for final interpretation. Following conclusions are reached on the relationship between settlement location and morphological landforms: - Percentages of settlements for flood, valley, slope and top are 8.37, 27.52, 58.60 and 5.50, respectively. Considering the percentages of the landforms provided in the area, however, valley is the most preferred landform followed by flood type. Slope and top landforms are less preferred. About 86 % of the settlements are concentrated along valley-slope boundary. - Morphological boundaries of flood and top landforms are consistent with the settlement zones. The valley-slope boundary, on the other hand, which is the most populated area, cross-cut the settlements zones.

Tornadoes are one of Mother Nature’s deadliest phenomena. They affect a large region of the United States. The risk of tornadoes is contingent on dynamic atmospheric conditions that are most likely during spring but which can occur anytime of the year, making the storms challenging to forecast. Using geographical information systems (GIS), a web-based spatial decision support system (SDSS) was created to help understand the spatial dimension of tornado risk assessment. The risk values are calculated using Tornado Days rather than taking a crude density measurement. The SDSS hosts GIS web services that are displayed on an Adobe Flex application. The web application allows users to view, research, query and extract information from the attributes of the GIS files. There is also a dynamic risk tool which gives users the ability to click anywhere inside the study area and get the percentage of risk that a tornado will occur within 25 miles of that very point. The web application eliminates users and viewers from conducting their own research and GIS work. In addition, automated updating models and macros were created to update the tornado database on an annual basis.

Shallow lake wetlands, for which aquatic plants (macrophytes) and water clarity are the key indicators of ecological status, provide valuable services to wildlife and humanity. Conservation of these ecosystems requires development of rapid and large scale monitoring strategies, where remote sensing and Geographic Information Systems (GIS) can be advantageous. In this study, high spatial resolution Quickbird and IKONOS and medium spatial resolution Landsat and Aster images were used for monitoring the aquatic plants and water clarity in Lakes Mogan and Eymir. Classification of emergent plants with high spatial resolution data yielded overall accuracies greater than 90% for both lakes, while overall accuracies obtained from the medium spatial resolution data ranged between 80% and 93% for Lake Mogan and between 70% and 78% for Lake Eymir. It was found that there was 23ha reed bed loss in Lake Mogan between 2002 and 2005 and an additional 14ha was lost between 2005 and 2006. In Lake Eymir, no significant change in reed bed area was detected from high spatial resolution images / however medium spatial resolution images revealed 8ha of change which was attributed to the presence of mixed pixels due to low resolution. The overall accuracies for submerged plant coverage classification from Quickbird images in Lake Mogan were 83% (2005) and 79% (2006) and for classification of submerged plants species were 72% (2005) and 69% (2006). Moreover, it was found that blue band together with the ratio of red band to blue band, were the best predictors of Secchi disc depth.