Thesis (Ph.D.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 176-182) Also available in print.

Thesis (Ph. D.)--Universiteit Twente, 2004. / Thesis propositions sheet inserted. Includes bibliographical references (p. 167-184) and index.

Thesis (Ph. D.)--University of Texas at Austin, 2005. / Supervisor: David R. Maidment. Vita. Includes bibliographical references.

Thesis (M. Sc.)--University of Hong Kong, 2005.

No description available.

Effective information communication and public participation in the planning process are important elements for facilitating successful environmental decision-making. Previous research has demonstrated the importance of such factors for delivering benefits to a wide range of stakeholders in the planning system by increasing the transparency and efficiency of the planning process. Given the current problems facing onshore wind farm planning in the UK there is an urgent need to investigate alternative approaches for enhancing the quality of information dissemination and public participation in the planning process. Planning information relating to the potential visual impacts of wind farms is particularly important in the case of the wind farm planning, given the high levels of concern amongst members of the public regarding the perceived negative visual impact of proposed wind turbines on the landscape. However, shortcomings associated with traditional techniques used to assess such impacts have been highlighted in previous research, along with drawbacks related to the dissemination of such information to the public during the planning stages of wind farm development. This has been shown to affect the overall quality of public participation in the planning process. This research is concerned with evaluating the potential of innovative digital landscape visualisation and Internet-based techniques for addressing some of the shortcomings in these areas. This thesis describes the implementation of two survey studies designed to meet these objectives. The first study uses a postal questionnaire approach in order to determine the current 'state-of-play' regarding the levels of use of such innovative techniques for improving impact assessment and information dissemination in wind farm planning. In addition to a review of the existing literature, the findings of the survey provide further rationale for conducting the second (Internet-based) survey study, designed to evaluate the potential of online visualisation-based approaches for improving the quality and dissemination of visual information, and enhancing public participation in wind farm planning. The survey is based on visualisations created for an actual proposed wind farm development in South Wales, UK. The findings reinforced much of the existing research literature, confirming that innovative visualisation and Internet-based approaches do have good potential for augmenting existing methods of visual information creation, dissemination and public participation although a variety of observations and concerns were raised by survey respondents that highlighted the potential limitations of such approaches. Further avenues for research are then identified.

Most GIS systems use separate thematic "layers" to store different types of spatial data. Each of them contains specific characteristics of the area, so there are separate layers for the distribution of buildings, the road network or the relief of the terrain. The spatial information used in GIS can be grouped into four main groups: polygonal maps, terrain models, networks and discrete, unconnected objects. Polygonal maps and terrain models are considered to be "field" models of space, covering the whole map, so there is some kind of information available at every location. On the other hand, networks and discrete objects are representations of the "object" model of space, in which the map is populated by entities and the space between them is empty. Choropleth maps are the most common examples of polygonal maps and the three main representations of terrain models are Triangular Irregular Networks (TINs), grids and contour lines. Networks consist of connected edges, while discrete objects can be points, lines or polygons. In networks, polygonal maps and surfaces there is some model of connectivity available. Polygons are adjacent to each other, as are the elements in terrain models. Network data is connected along the edges and junctions are defined. Unconnected objects need have no connectivity information, but in that case the possible spatial queries are limited. The layers can be stacked on top of each other to perform various operations and analyses on them. However, there is no consistent method applicable to all data types because GIS has traditionally separated field and object layers and used different data structures to represent them. This thesis presents a unified spatial data model for these most common types of spatial information and intends to show that it has clear advantages for geographical analysis. The idea is to represent discrete object models as fields, so there is information available at all locations. The model is based on the Voronoi Diagram (VD) and the dual Delaunay Triangulation (DT), two well studied geometric structures. Depending on the application it may be appropriate to represent the data on the map by the simple VD/DT, or their derivatives - the Constrained DT (CDT), the Line Segment VD (LSVD) or the crust and the skeleton. All of these are directly related to each other and may be handled in a single manner in the computer. Algorithms and the storage of these various forms of the VD using the quad-edge data structure is described. This structure may be updated locally, and dynamic algorithms for each of these representations are presented. This allows for the development of a common interactive framework for what are traditionally considered to be distinct data types. The unified model is illustrated by a variety of GIS applications, and the implementation of several traditional GIS operations and queries is discussed.

<p> Federal, state and local officials are planning for a (M) 7.8 San Andreas Earthquake Scenario in the Southern California Catastrophic Earthquake Response Plan that would require initial emergency food and water resources to support from 2.5 million to 3.5 million people over an eight-county region in Southern California. However, a model that identifies locations of affected populations&mdash;with consideration for social vulnerability, estimates of their emergency logistical resource requirements, and their resource requirements over time&mdash;has yet to be developed for the emergency response plan.</p><p> The aim of this study was to develop a modeling methodology for emergency logistical resource requirements of affected populations in the (M) 7.8 San Andreas Earthquake Scenario in Southern California. These initial resource requirements, defined at three-days post-event and predicted through a probabilistic risk model, were then used to develop a relative risk ratio and to estimate resources requirements over time. The model results predict an &ldquo;at-risk&rdquo; population of 3,352,995 in the eight-county study region. In Los Angeles County, the model predicts an &ldquo;at- risk&rdquo; population of 1,421,415 with initial requirements for 2,842,830 meals and 4,264,245 liters of water. The model also indicates that communities such as Baldwin Park, Lancaster-Palmdale and South Los Angeles will have long-term resource requirements.</p><p> Through the development of this modeling methodology and its applications, the planning capability of the Southern California Catastrophic Earthquake Response Plan is enhanced and provides a more effective baseline for emergency managers to target emergency logistical resources to communities with the greatest need. The model can be calibrated, validated, generalized, and applied in other earthquake or multi-hazard scenarios through subsequent research.</p><p>

abstract: Economic inequality is always presented as how economic metrics vary amongst individuals in a group, amongst groups in a population, or amongst some regions. Economic inequality can substantially impact the social environment, socioeconomics as well as human living standard. Since economic inequality always plays an important role in our social environment, its study has attracted much attention from scholars in various research fields, such as development economics, sociology and political science. On the other hand, economic inequality can result from many factors, phenomena, and complex procedures, including policy, ethnic, education, globalization and etc. However, the spatial dimension in economic inequality research did not draw much attention from scholars until early 2000s. Spatial dependency, perform key roles in economic inequality analysis. The spatial econometric methods do not merely convey a consequence of the characters of the data exclusively. More importantly, they also respect and quantify the spatial effects in the economic inequality. As aforementioned, although regional economic inequality starts to attract scholars' attention in both economy and regional science domains, corresponding methodologies to examine such regional inequality remain in their preliminary phase, which need substantial further exploration. My thesis aims at contributing to the body of knowledge in the method development to support economic inequality studies by exploring the feasibility of a set of new analytical methods in use of regional inequality analysis. These methods include Theil's T statistic, geographical rank Markov and new methods applying graph theory. The thesis will also leverage these methods to compare the inequality between China and US, two large economic entities in the world, because of the long history of economic development as well as the corresponding evolution of inequality in US; the rapid economic development and consequent high variation of economic inequality in China. / Dissertation/Thesis / Masters Thesis Geography 2016

A number of GIS architectures and technologies have emerged recently to facilitate the visualisation and processing of geospatial data over the Web. The work presented in this dissertation builds on these efforts and undertakes to overcome some of the major problems with traditional GIS client architectures, including application bloat, lack of customisability, and lack of interoperability between GIS products. In this dissertation we describe how a new client-side GIS architecture was developed and implemented as a proof-of-concept application called RADGIS, which is based on open standards and emerging distributed component-based software paradigms. RADGIS reflects the current trend in development focus from Web browser-based applications to customised clients, based on open standards, that make use of distributed Web services. While much attention has been paid to exposing data on the Web, there is growing momentum towards providing “value-added” services. A good example of this is the tremendous industry interest in the provision of location-based services, which has been discussed as a special use-case of our RADGIS architecture. Thus, in the near future client applications will not simply be used to access data transparently, but will also become facilitators for the location-transparent invocation of local and remote services. This flexible architecture will ensure that data can be stored and processed independently of the location of the client that wishes to view or interact with it. Our RADGIS application enables content developers and end-users to create and/or customise GIS applications dynamically at runtime through the incorporation of GIS services. This ensures that the client application has the flexibility to withstand changing levels of expertise or user requirements. These GIS services are implemented as components that execute locally on the client machine, or as remote CORBA Objects or EJBs. Assembly and deployment of these components is achieved using a specialised XML descriptor. This XML descriptor is written using a markup language that we developed specifically for this purpose, called DGCML, which contains deployment information, as well as a GUI specification and links to an XML-based help system that can be merged with the RADGIS client application’s existing help system. Thus, no additional requirements are imposed on object developers by the RADGIS architecture, i.e. there is no need to rewrite existing objects since DGCML acts as a runtime-customisable wrapper, allowing existing objects to be utilised by RADGIS. While the focus of this thesis has been on overcoming the above-mentioned problems with traditional GIS applications, the work described here can also be applied in a much broader context, especially in the development of highly customisable client applications that are able to integrate Web services at runtime.