Thesis (Ph. D.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains ix, 145 p. : ill. (some col.), maps (some col.). Includes abstract. Includes bibliographical references (p. 129-141).

Thesis (Ph. D.)--Oregon State University, 2008. / Printout. Includes bibliographical references (leaves 150-155). Also available on the World Wide Web.

Cycling is an underutilized mode of transportation in cities across North America. Numerous factors contribute to low ridership levels, but a key deterrent to cycling is concern for personal safety. In an effort to increase cycling mode share, many cities are investing in cycling infrastructure, with several cities constructing connected bicycle networks. Monitoring the impact of new infrastructure is important for accountability to citizens and to encourage political will for future investments in cycling facilities. A lack of spatially continuous ridership data and methodological challenges have limited monitoring and evaluation of the impacts of infrastructure changes. The goal of our research was to demonstrate spatially explicit approaches for monitoring city-wide changes in patterns of safety and ridership following improvements to cycling infrastructure. To meet our goal, our first analysis demonstrated a method for monitoring changes in the spatial-temporal distribution of cycling incidents across a city. We compared planar versus network constrained kernel density estimation for visualizing cycling incident intensity across the street network of Vancouver, Canada using cycling incidents reported to the Insurance Corporation of British Columbia. Next, we applied a change detection algorithm to detect statistically significant change between maps of kernel density estimates. The utility of the network kernel density change detection method is demonstrated through a case study in the city of Vancouver, Canada where we compare cycling incident densities following construction of two cycle tracks in the downtown core. The methods developed and demonstrated for this study provide city planners, transportation engineers and researchers a means of monitoring city-wide changes in the patterns of cycling incidents following enhancements to cycling infrastructure. Our second analysis demonstrated how network constrained spatial analysis methods can be applied to emerging sources of crowdsourced cycling data to monitor city-wide changes in patterns of ridership. We used network constrained global and local measures of spatial autocorrelation, applied to crowdsourced ridership data from Strava, to examine changes in ridership patterns across Ottawa-Gatineau, Canada, following installation and closures of cycling infrastructure. City planners, transportation engineers and researchers can use the methods outlined here to monitor city-wide changes in ridership patterns following investment in cycling infrastructure or other changes to the transportation network. Through this thesis we help overcome the challenges associated with monitoring the impact of infrastructure changes on ridership and cycling safety. We demonstrated how network constrained spatial analysis methods can be applied to officially reported cycling incident data to identify changes in the spatial-temporal distribution of cycling safety across a transportation network. We also demonstrated how network appropriate spatial analysis techniques can be applied to large, emerging crowdsourced cycling datasets to monitor changes in patterns of ridership. These methods enhance our understanding of the city-wide impact of infrastructure changes on cycling safety and ridership patterns. / Graduate

This thesis is concerned with the prostitution in Pompeii with a focus on the physical space in which this social phenomenon was enacted. Despite the negative attitudes by much of Roman society towards prostitutes, the sex trade in Pompeii thrived, with numerous venues offering the sale of sex. Prostitutes stationed themselves throughout the town and solicited customers inside buildings or out on the street in whatever limited privacy could be managed. The purpose of this thesis is to examine the manner in which prostitution was present in Pompeii through the spatial analysis of venues of prostitution in the town. Among other structures including, taverns and baths, I will make a close examination of the one known purpose-built brothel, its location and layout, in order to analyze the manner in which prostitute and client could interact in such a setting. The artwork and the graffiti found within the brothel will also be useful for this examination, and will provide further insights to the customer experience in the brothel. Although prostitutes themselves were disapproved of for their lifestyle and profession, society accepted the presence of prostitution as a whole. Customers readily paid for the services of prostitutes in various venues that each offered a different environment and thus a different experience. The enjoyment had by customers during their interactions with prostitutes ensured their return business and promoted the success of the sex trade in the service industry at Pompeii. / Thesis / Master of Arts (MA)

No Abstract Provided. / Thesis / Master of Arts (MA)

With Canada's increasing population, natural disasters such as flooding events will have an increasing impact on human populations. The severity of these events requires that decision makers have a clear understanding of the flood risks that communities face in order to plan for and mitigate flood risks. One key component to understanding flood risk is flood exposure, an element of which is the presence of structures (e.g., residences, businesses, and other buildings) in an area that could be damaged by flooding. Presently, several resources exist at both the national and global level that can be used to estimate the spatial distribution of structures. These resources are typically generated at global scales and do not account for regional or local data or processes that could enhance the accuracy and precision of exposure estimation in sparsely populated areas. The present study investigates the feasibility of creating a region-specific dwelling distribution model that helps improve estimation of residential structures in rural areas. Herein, we describe a rural dwelling distribution model for the province of Alberta that can be used to assist in the estimation of structural exposure to flood risk. The model is based on a random forest classification algorithm and several publicly available datasets associated with dwelling and population density. The model was validated using visually referenced data collected from earth imagery. The resulting dwelling layer was then evaluated in its ability to spatially disaggregate census dwelling counts, as well as predict dwelling exposure in several scenarios. This method appears to be a useful alternative to globally scaled models, or using the census alone, particularly for rural areas of Canada. / Thesis / Master of Science (MSc)

Given the large volume of data that is regularly accumulated, the need to properly manage, efficiently display and correctly interpret, becomes more important. Complex analysis of data is best performed using statistical models and in particular those with a geographical element are best analysed using Spatial Statistical Methods, including local regression. Spatial Statistical Methods are employed in a wide range of disciplines to analyse and interpret data where it is necessary to detect significant spatial patterns or relationships. The topic of the research presented in this thesis is an exploration of the most effective methods of visualising results. A human being is capable of processing a vast amount of data as long as it is effectively displayed. However, the perceptual load will at some point exceed the cognitive processing ability and therefore the ability to comprehend data. Although increases in data scale did increase the cognitive load and reduce processing, prior knowledge of geographical information systems did not result in an overall processing advantage. The empirical work in the thesis is divided into two parts. The first part aims to gain insight into visualisations which would be effective for interpretation and analysis of Geographically Weighted Regression (GWR), a popular Spatial Statistical Method. Three different visualisation techniques; two dimensional, three dimensional and interactive, are evaluated through an experiment comprising two data set sizes. Interactive visualisations perform best overall, despite the apparent lack of researcher familiarity. The increase in data volume can present additional complexity for researchers. Although the evaluation of the first experiment augments understanding of effective visualisation display, the scale at which data can be adequately presented within these visualisations is unclear. Therefore, the second empirical investigation seeks to provide insight into data scalability, and human cognitive limitations associated with data comprehension. The general discussion concludes that there is a need to better inform researchers of the potential of interactive visualisations. People do need to be properly trained to use these systems, but the limits of human perceptual processing also need to be considered in order to permit more efficient and insightful analysis.

Ho, Siu Tung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (p. 43-44). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 2 --- Methodology and Algorithm --- p.6 / Chapter 2.1 --- Testing one. homogeneous cluster --- p.8 / Chapter 3 --- Simulation Study --- p.17 / Chapter 3.1 --- Simulation Plan --- p.19 / Chapter 3.1.1 --- One single cluster --- p.19 / Chapter 3.1.2 --- Two separated clusters --- p.20 / Chapter 3.2 --- Measure of Performance --- p.26 / Chapter 3.3 --- Simulation Results --- p.27 / Chapter 3.3.1 --- One single cluster --- p.27 / Chapter 3.3.2 --- Two separated clusters --- p.30 / Chapter 4 --- Conclusion and further research --- p.36 / Chapter 4.1 --- Constructing Data depth --- p.38 / Bibliography --- p.43

Enrollment projections are used by school administrators to predict the number of students expected to attend a school district within a defined period of time. This dissertation examines methods used for making enrollment projections and seeks to improve these methods through the application of geographic principles. The presented thesis challenges the existing aspatial framework used to calculate grade progression rates, arguing that a spatial framework improves projection accuracy. Grade progression rates are the critical element in enrollment projections and this dissertation's major contribution is the analysis of four different grade progression rate calculations at the school district level. This dissertation also argues that grade progression rates represent spatial relationships of migration that exist between adjacent school districts and uses these spatial relationships to create a new spatial Bayesian approach. This dissertation demonstrates that geographic methods can be successfully integrated to improve enrollment project accuracy through the reduction of the small number problem. In addition, this research identifies the importance of smoothing effects of the modified cohort progression method when compared to Bayesian approaches.

Geostatistical linear interpolation procedures such as kriging require knowledge of the covariance structure of the spatial process under investigation. In practice, the covariance of the process is unknown, and must be estimated from the available data. As the quality of the resulting predictions, and associated mean square prediction errors, depends on adequate specification of the covariance structure, it is important that the analyst be able to detect inadequacies in the specified covariance model. Case-deletion diagnostics are currently used by geostatisticians to evaluate spatial models. The second chapter of the thesis describes a particular case-deletion diagnostic based on standardized PRESS residuals, and its use in assessing the predictive capacity of spatial covariance models. Distributional properties of this statistic, denoted T [subscript PR], are discussed, and a saddlepoint approximation to its distribution is derived. Guidelines for calculating approximate p-values for the statistic under an hypothesized covariance model are also given. A simulation study demonstrates that the distributional and p-value approximations are accurate. The proposed method is illustrated through an example, and recommendations for calculation of T [subscript PR], and associated approximate p-values on a regional basis are given. The third chapter investigates the behavior of the standardized PRESS residuals under various misspecifications of the covariance matrix, V. A series of simulation studies show consistent patterns in the standardized PRESS residuals under particular types of misspecifications of V. It is observed that misspecification of V may lead to variability among the standardized PRESS residuals greater or less than would be expected if V was correctly specified, depending on the nature of the misspecification. Based on this observation, an adjustment to normal probability plots of the standardized PRESS residuals is proposed. The adjusted normal probability plots may be used to identify potential improvements to covariance models, without requiring extensive further calculations. / Graduation date: 1996