Local Ideal Point Method for GIS-based Multicriteria Analysis: A Case Study in London, Ontario

GIS-based multicriteria analysis (GIS-MCA) is a procedure for transforming and combining geographic data and value judgments (preferences) to evaluate a set of alternatives with respect to relevant criteria. Ideal Point Method (IPM) is one of the most often used GIS-MCA techniques. It has been applied in many research/planning areas including environmental planning, urban/regional planning, waste management, water resource management and agriculture. One of the limitations of IPM is that it has conventionally been used as a global approach based on the implicit assumption that its parameters do not vary as a function of geographic space. The conventional IPM assumes a spatial homogeneity of its parameters within the whole study area. This thesis proposes a new IPM called local IPM. The local version of IPM is developed by localizing two parameters (criterion weights and ideal/nadir points) based on the range-sensitivity principle. The IPM methods are used to evaluate and analyse the spatial patterns of the quality of employment in London, Ontario. The case study shows that there are significant differences between the spatial patterns generated by the local and conventional IPM. The local IPM not only can display the general ‘spatial trend’ of the quality of employment in London, but also is able to highlight the areas with relatively high quality of employment in different neighborhoods. Furthermore, the local IPM provides a tool for visualizing and exploring spatial patterns. The parameters influencing the local IPM results can be mapped and further examined with GIS

Spatial analysis of selected biodiversity features in protected areas: a case study in Tuscany region

The development of strategies for biodiversity analysis is critical at several levels, particularly at the national one. The World Conference on Biological Diversity held in Rio de Janeiro in 1992, the European Natura 2000 network and the Environmental Conference of the Regions of Europe (EN.CO.RE) brought forward several measures aiming at the preservation of Biodiversity. Targets for biodiversity preservation include protected areas among others. Accordingly, the analysis of the degree of biodiversity of protected areas proves to be a valid tool to evaluate the effectiveness of those measures. The present manuscript analyses the degree of some relevant features of biodiversity in the Region of Tuscany, through the implementation of multidimensional indicators in a Spatial MultiCriteria Analysis. After a state of the art of biodiversity definition, four indicators have been used for the analysis. A raster map in which pixels have higher or lower values of biodiversity was produced in order to investigate which of these values might be located in protected areas. Protected areas with high value of biodiversity confirmed that the adopted environmental policies are positively related to the conservation of biodiversity. The result of the analysis, corroborated through auto-correlational statistical analysis, has highlighted the important role of protected areas in maintaining a certain degree of biodiversity

Web 2.0-based Collaborative Multicriteria Spatial Decision Support System: A Case Study of Human-Computer Interaction Patterns

The integration of GIS and Multicriteria Decision Analysis (MCDA) capabilities into the Web 2.0 platform offers an effective Multicriteria Spatial Decision Support System (MC-SDSS) with which to involve the public, or a particular group of individuals, in collaborative spatial decision making. Understanding how decision makers acquire and integrate decision-related information within the Web 2.0-based collaborative MC-SDSS has been one of the major concerns of MC-SDSS designers for a long time. This study focuses on examining human-computer interaction patterns (information acquisition behavior) within the Web 2.0-based MC-SDSS environment. It reports the results of an experimental study that investigated the effects of task complexity, information aids, and decision modes on information acquisition metrics and their relations. The research involved three major steps: (1) developing a Web 2.0-based analytic-deliberative MC-SDSS for parking site selection in Tehran, Iran to analyze human-computer interaction patterns, (2) conducting experiments using this system and collecting the human-computer interaction data, and (3) analyzing the log data to detect the human-computer interaction patterns (information acquisition metrics). Using task complexity, decision aid, and decision mode as the independent factors, and the information acquisition metrics as the dependent variables, the study adopted a repeated-measures experimental design (or within-subjects design) to test the relevant hypotheses. Task complexity was manipulated in terms of the number of alternatives and attributes at four levels. At each level of task complexity, the participants carried out the decision making process in two different GIS-MCDA modes: individual and group modes. The decision information was conveyed to participants through common map and decision table information structures. The map and table were used, respectively, for the exploration of the geographic (or decision) and criterion outcome spaces. The study employed a process-tracing method to directly monitor and record the decision makers’ activities during the experiments. The data on the decision makers’ activities were recorded as Web-based event logs using a database logging technique. Concerningiv task complexity effects, the results of the study suggest that an increase in task complexity results in a decrease in the proportion of information searched and proportion of attribute ranges searched, as well as an increase in the variability of information searched per attribute. This finding implies that as task complexity increases decision makers use a more non-compensatory strategy. Regarding the decision mode effects, it was found that the two decision modes are significantly different in terms of: (1) the proportion of information search, (2) the proportion of attribute ranges examined, (3) the variability of information search per attribute, (4) the total time spent acquiring the information in the decision table, and (5) the average time spent acquiring each piece of information. Regarding the effect of the information aids (map and decision table) on the information acquisition behavior, the findings suggest that, in both of the decision modes, there is a significant difference between information acquisition using the map and decision table. The results show that decision participants have a higher number of moves and spend more time on the decision table than map. The study presented in this dissertation has implications for formulating behavioral theories in the spatial decision context and practical implications for the development of MC-SDSS. Specifically, the findings provide a new perspective on the use of decision support aids, and important clues for designers to develop an appropriate user-centered Web-based collaborative MC-SDSS. The study’s implications can advance public participatory planning and allow for more informed and democratic land-use allocation decisions

Multi-criteria site selection workflow for geological storage of hydrogen in depleted gas fields: A case for the UK

Underground hydrogen storage (UHS) plays a critical role in ensuring the stability and security of the future clean energy supply. However, the efficiency and reliability of UHS technology depend heavily on the careful and criteria-driven selection of suitable storage sites. This study presents a hybrid multi-criteria decision-making framework integrating the Analytical Hierarchy Process (AHP) and Preference Ranking Organisation Method for Enrichment of Evaluations (PROMETHEE) to identify and select the best hydrogen storage sites among depleted gas reservoirs in the UK. To achieve this, a new set of site selection criteria is proposed in light of the technical and economic aspects of UHS, including location, reservoir rock quality and tectonic characteristics, maximum achievable hydrogen well deliverability rate, working gas capacity, cushion gas volume requirement, distance to future potential hydrogen clusters, and access to intermittent renewable energy sources (RESs). The framework is implemented to rank 71 reservoirs based on their potential and suitability for UHS. Firstly, the reservoirs are thoroughly evaluated for each proposed criterion and then the AHP-PROMETHEE technique is employed to prioritise the criteria and rank the storage sites. The study reveals that the total calculated working gas capacity based on single-well plateau withdrawal rates is around 881 TWh across all evaluated reservoirs. The maximum well deliverability rates for hydrogen withdrawal are found to vary considerably among the sites; however, 22 % are estimated to have deliverability rates exceeding 100 sm3/d, and 63 % are located within a distance of 100 km from a major hydrogen cluster. Moreover, 70 % have access to nearby RESs developments, with an estimated cumulative RESs capacity of approximately 181 GW. The results highlight the efficacy of the proposed multi-criteria site selection framework. The top five highest-ranked sites for UHS based on the evaluated criteria are the Cygnus, Hamilton, Saltfleetby, Corvette, and Hatfield Moors gas fields. The insights provided by this study can contribute to informed decision-making, sustainable development, and the overall progress of future UHS projects within the UK and globally

Prioritizing Offshore Vendor Selection Criteria for the North American Geospatial Industry

The U.S. market for geospatial services totaled US $2.2 billion in 2010, representing 50% of the global market. Data-processing firms subcontract labor-intensive portions of data services to offshore providers in South and East Asia and Eastern Europe. In general, half of all offshore contracts fail within the first 5 years because one or more parties consider the relationship unsuccessful. Despite the high failure rates, no study has examined the offshore vendor selection process in the geospatial industry. The purpose of this study was to determine the list of key offshore vendor selection criteria and the efficacy of the analytic hierarchy process (AHP) for ranking the criteria that North American geospatial companies consider in the offshore vendor selection process. After the selection of the initial list of factors from the literature and their validation in a pilot study, a final survey instrument was developed and administered to 15 subject matter experts (SMEs) in North America. The SMEs expressed their preferences for one criterion over another by pairwise comparisons, which served as input to the AHP procedure. The results showed that the quality of deliverables was the top ranked (out of 26) factors, instead of the price, which ranked third. Similarly, SMEs considered social and environmental consciousness on the vendor side as irrelevant. More importantly, the findings indicated that the structured AHP process provides a useful and effective methodology whose application may considerably improve the quality of the overall vendor selection process. Last, improved and stabilized business relationships leading to predictable budgets might catalyze social change, supporting stable employment. Consumers could benefit from derivative improvements in product quality and pricing

Decision Support System for Container Port Selection using Multiple-Objective Decision Analysis

Ports are essential for maritime transportation and global supply chains since they are nodes that connect the sea- and land-based modes of transportation. With containerization and supply chains stimulating global trade, ports are challenged to adjust to changes in the market to create value to their customers. Therefore, this dissertation research focuses on the container port selection decision analysis to provide information to help shipping lines select the best port for their shipping networks. Since the problem is complex, dynamic, and involves multiple and conflicting criteria, the research proposes to use the multi-objective decision analysis with Value-Focused Thinking approach. The first chapter analyzes the port selection literature by timeline, journals, geographical location, and focus of the studies. Also, the research identifies the multiple criteria used in the port selection literature, as well as the models and approaches used for the analysis of the port selection decision problem. The second chapter develops a container port selection decision model for shipping lines using ports in West Africa. This model uses a multi-attribute value theory with valued-focused thinking and Alternative-Focused Thinking methodologies. The third chapter develops a port selection decision support system for shipping lines to select the best port in the U.S. Gulf Coast considering the impact of the Panama Canal’s expansion. The decision support system uses the multi-objective decision analysis with Value-Focused Thinking approach, incorporating the opinion of an industry expert for the development of the value model. It also includes a cost model to quantify the cost of the alternatives. A Monte Carlo simulation is used to help decision makers understand the value and cost risks of the decision. The contribution of this research is that it provides a tool to decision makers of the shipping lines industry to improve the decision making process to select the port that will add the most affordable value to the global supply chains of their customers. In addition, researchers can use the proposed methodology for future port selection studies in other regions and from the perspectives of other stakeholders

Spatial multicriteria decision analysis for the siting of on-shore wind power in Kemiönsaari

Wind power is a low-carbon energy production form that reduces the dependence of society on fossil fuels. Finland has adopted wind energy production into its climate change mitigation policy, and that has lead to changes in legislation, guidelines, regional wind power areas allocation and establishing a feed-in tariff. Wind power production has indeed boosted in Finland after two decades of relatively slow growth, for instance from 2010 to 2011 wind energy production increased with 64 %, but there is still a long way to the national goal of 6 TWh by 2020. This thesis introduces a GIS-based decision-support methodology for the preliminary identification of suitable areas for wind energy production including estimation of their level of risk. The goal of this study was to define the least risky places for wind energy development within Kemiönsaari municipality in Southwest Finland. Spatial multicriteria decision analysis (SMCDA) has been used for searching suitable wind power areas along with many other location-allocation problems. SMCDA scrutinizes complex ill-structured decision problems in GIS environment using constraints and evaluation criteria, which are aggregated using weighted linear combination (WLC). Weights for the evaluation criteria were acquired using analytic hierarchy process (AHP) with nine expert interviews. Subsequently, feasible alternatives were ranked in order to provide a recommendation and finally, a sensitivity analysis was conducted for the determination of recommendation robustness. The first study aim was to scrutinize the suitability and necessity of existing data for this SMCDA study. Most of the available data sets were of sufficient resolution and quality. Input data necessity was evaluated qualitatively for each data set based on e.g. constraint coverage and attribute weights. Attribute quality was estimated mainly qualitatively by attribute comprehensiveness, operationality, measurability, completeness, decomposability, minimality and redundancy. The most significant quality issue was redundancy as interdependencies are not tolerated by WLC and AHP does not include measures to detect them. The third aim was to define the least risky areas for wind power development within the study area. The two highest ranking areas were Nordanå-Lövböle and Påvalsby followed by Helgeboda, Degerdal, Pungböle, Björkboda, and Östanå-Labböle. The fourth aim was to assess the recommendation reliability, and the top-ranking two areas proved robust whereas the other ones were more sensitive.Siirretty Doriast

Multi-method Exploration of the Economic Sustainability of Probiotic Yoghurt Kitchens in Mwanza, Tanzania

This research aimed to examine the economic and locational aspects of a probiotic yoghurt kitchen development project facilitated by Western Heads East in Mwanza, Tanzania. This study is based upon 41 semi-structured interviews with 57 participants in three groups: kitchen group members, customers, and staff of the African Probiotic Yoghurt Network. This research contributes to the literature on development geography, specifically on the ins and outs of the everyday of the kitchens, as well as proposing a new approach to multicriteria evaluation using qualitative data, and the ‘researcher as instrument’ approach. The results demonstrate that while there are problems in the operation and communication of the kitchens and overseeing organization, this type of project should not be written off