published_or_final_version / Geography / Master / Master of Geographic Information System

published_or_final_version / Environmental Management / Master / Master of Science in Environmental Management

The focus of this dissertation is a methodology to select an appropriate subnetwork from a large urban transportation network that experiences changes to a small fraction of the whole network. Subnetwork selection techniques are most effective when using a regional dynamic traffic assignment model. The level of detail included in the regional model relieves the user of manually coding subnetwork components because they can be extracted from the full model. This method will reduce the resources necessary for an agency to complete an analysis through time and cost savings. Dynamic traffic assignment also has the powerful capability of determining rerouting due to network changes. However, the major limitation of these new dynamic models is the computational demand of the algorithms, which inhibit use of full regional models for comparing multiple scenarios. By examining a smaller window of the network, where impacts are expected to occur, the burden of computer power and time can be overcome. These methods will contribute to the accuracy of dynamic transportation systems analysis, increase the tractability of these advanced traffic models, and help implement new modeling techniques previously limited by network size. The following describes how to best understand the effects of reducing a network to a subarea and how this technique may be implemented in practice. / text

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A prototype raster geographic information system (GIS) for agricultural water quality analysis was developed considering the farm as an aggregation of spatial units with homogeneous physical and management characteristics. A crop model that simulates the farm and environment response to different management scenarios was integrated with the GIS. The integrated GIS-model is then run on each homogeneous area. The results of crop yield and chemical leaching are geographically referenced for further display and analysis, and to serve as an input to the decision model. A decision model based on maximization of expected utility (MEU) was also integrated to help assess and evaluate the impacts of fertilizer application on the faun system and the environment. By using utilities for both crop yield and chemical leaching the model circumvents the issue of assigning a monetary value to the environment. Accommodating both the farmers' goals, in terms of higher yield and the well being of the environment, in terms of lower chemical leaching, the model computes the expected utility of each management scenario. The management practice with the maximum expected utility is then recommended. The integrated model was tested with an example of lettuce production in Arizona. Results were compared to published field reports, the model recommendation matched well with the field results. The prototype model was simple to use, and very well integrated, which makes it an alternative to the more complex and expensive coupling of commercial GIS and simulation models.

M. Tech.: Electrical Engineering. / The purpose of this research was to design a low cost mobile positioning system based on Global System for Mobile communication network. The positioning system utilises Timing Advance, Signal Strength, a calibrated propagation system based on per -cell modelling and field measurements data to calculate the mobile position. Clutter and terrain features such as trees and buildings were modelled to closely represent the real environment to enhance the accuracy of the Signal Strength prediction. The key pillar of this approach is its ability to establish the contribution of each of the localised features to the propagation model. Based on the magnitude of the contribution of each feature, a conclusive correction factor for each feature was obtained. The proposed system is evaluated using field measurements collected from a Global System for Mobile communication network in diverse geographic locations in the outskirts of Pretoria. A fair correlation was established between field measurements and propagation model predictions.

This study focused on the optimisation of offshore marine fish-cage farming in Tenerife, Canary Islands. The main objective was to select the most suitable sites for offshore cage culture. This is a key factor in any aquaculture operation, affecting both success and sustainability. Moreover, it can solve conflicts between different coastal activities, making a rational use of the coastal space. Site selection was achieved by using Geographical Information Systems (GIS) based models and related technology, such as satellite images and Global Positioning System (GPS), to support the decision-making process. Three different cage systems were selected and proposed for different areas around Tenerife. Finally, a particulate waste distribution model (uneaten feed and faeces) was developed, also using GIS, for future prediction of the dispersive nature of selected sites. This can reduce the number of sites previously identified as most suitable, by predicting possible environmental impacts on the benthos if aquaculture was to be developed on a specific site. The framework for spatial multi-criteria decision analysis used in this study began with a recognition and definition of the decision problem. Subsequently, 31 production functions (factors and constraints) were identified, defined and subdivided into 8 sub-models. These sub-models were then integrated into a GIS database in the form of thematic layers and later scored for standardization. At this stage, the database was verified by field sampling to establish the quality of data used. The decision maker's preferences were incorporated into the decision model by assigning weights of relative importance to the evaluation under consideration. These, together with the thematic layers, were integrated by using Multi-criteria Evaluation (MCE) and simple overlays to provide an overall assessment of possible alternatives. Finally, sensitivity analysis was performed to determine the model robustness. The integration, manipulations and presentation of the results by means of GIS-based models in this sequential and logical flow of steps proved to be very effective for helping the decision-making process of site selection in study. On the whole, this study revealed the usefulness of GIS as an aquaculture planning and management tool. Cage systems that can withstand harsh environments were found to be suitable for use over a broader area of Tenerife's coastline. Thus, the more robust self-tensioned cage (SeaStation®) could be used over a greater area than the weaker gravity cages (Corelsa®). From the 228 km2 of available area for siting cages in the coastal regions with depth of 50 m, the suitable area (sum of scores 6, 7 and 8) for siting SeaStation® cages was 61 km2, while the suitable area for SeaStation® and Corelsa® cages was 49 and 37 km2 respectively. Most of the variation between these three cage systems was found among the intermediate suitability scores. It was concluded that the biggest differences in suitable area among cage systems are between Corelsa® and SeaStation® systems, followed by differences between Corelsa® and OceanSpar® cages, and OceanSpar® and SeaStation® respectively. This variability was mostly located on the N and NNW of the island, where waves, both long and short-term, are higher.

published_or_final_version / Urban Design / Master / Master of Urban Design

published_or_final_version / abstract / toc / Ecology and Biodiversity / Doctoral / Doctor of Philosophy

published_or_final_version / Geography and Geology / Master / Master of Philosophy