Master of Science / Department of Statistics / Michael J. Higgins / There have been a wave of recent interest in understanding the dynamics of vehicular emissions in university towns. Using data from a recent survey of Kansas State University students, faculty, and staff-which includes a detailed itinerary of a day’s worth of travel -I assess spatial and temporal trends of emissions at Kansas State University. By combining the survey data with secondary sources of data, including vehicular emissions data from Fueleconony.gov and trip distance information from Google, I obtain improved measure for the quantity of emissions produced during each trip. After an extensive cleaning of the data, I develop heat maps for emissions composed of shape files identifying zip-code boundaries and a raster layer. I find that most vehicular emissions are concentrated around campus, with the highest level of emissions occurring during rush hour. Furthermore, faculty and staff appear to, on average, produce more emissions than students. I also investigate how proposed methods for reducing emissions will affect these spatio-temporal trends. Specifically, I show that walking or biking short distances instead of driving may lead to a small overall reduction in vehicular emissions.

Owing to the advances of computer and communication technologies, clustering analysis on moving objects has attracted increasing attention in recent years. An interesting problem is to find the moving clusters composed of objects which move along for a sufficiently long period of time. However, a moving cluster inclines to break after some time because of the goal change in each individual object. In order to identify the set of moving clusters, we propose the formal definition of moving clusters with semantically clear parameters. Based on the definition, we propose delicate approaches to cluster moving objects. The proposed approaches are evaluated using data generated with and without underlying model. We validate our approaches with a through experimental evaluation and comparison.

Since the initialization of economic reforms in 1978, China has undergone significant urbanization and modernization at an increasingly rapid pace, with the national urbanization rate increasing from 17.9% in 1978 to 57.4% in 2016. An increasingly significant portion of China’s population is integrating itself into thriving urbanized areas. Though amounting to only 8.5% of the nation’s total population (1.5 billion), China’s ethnic minority population remains considerable in number. In the future, by adopting the National New-Type Urbanization Plan in 2014, China’s urbanization is expected to evolve into a more human-oriented process, as the plan ambitiously aims to increase the urban population by another 200 million, most of which will consist of Chinese ethnic minorities. It is hoped that this increase will boost the urbanization rate among Chinese ethnic minorities. The gaps within existing literature and the practicality of improving the inclusivity of the urban minority population in the urbanization process legitimize the development of a comprehensive and retrospective study of the evolution of spatial-temporal dynamics of the distribution of Chinese ethnic groups with a Chinese urbanization perspective on a national scale. Based on national census data from 1990, 2000, and 2010, this study adopts the Standard Deviational Ellipse as a distributional trend measurement of minorities in urban China and determines four major new features of the distribution of the Chinese ethnic minorities over the last twenty-years in China’s urbanization context. First, a three-stage peripheral-to-core transition pattern was observed. Second, it is observed that there is an escalating decline of the urban minority population in the central region of China, particularly since 2000. Third, national-level city agglomerations located in the eastern region of China have begun to play leading roles in minority urbanization, particularly those located in the Yangtze and Pearl River Delta. Fourth, in both China’s west region and its autonomous areas, as continuous beneficiaries of supportive policies, metropolises, such as provincial capitals, have been shaped into important regional minority population concentrations. This study also allows for a better insight of Chinese urbanization processes and their inter/intra-relating mechanisms in ethnic minority areas. Finally, this study’s findings provide insightful and detailed information for scholars, policy and, ultimately, decisionmakers, to improve the process for sustainable and inclusive urbanization in China.

Ecosystems and their components (e.g., organisms, physicochemical variables) are dynamic in space and time. This dynamism makes ecological change notoriously difficult to study and manage. This thesis therefore aims to develop new ways of using spatiotemporal information for inference and prediction. Applying theoretical and statistical concepts to patterns of spatiotemporal variation in aquatic ecosystems led to three discoveries that show promise as ecological applications. First, I show that temporal variability of an ecosystem process can be inferred from its spatial variability. This application may be the first quantitative form of the widely-used method, space-for-time substitution. Its use is supported by an analytical framework giving the conditions under which space is a good surrogate for time. Second, I demonstrate the use of spatiotemporal patterns to predict responses of variables when ecosystem fragments are connected. Connection leads to large shifts in spatiotemporal pattern and other response metrics (e.g., temporal variability) for variables showing asynchrony and concentration gradients among sites (e.g., populations). Meanwhile, these changes are minimal if variables exhibit synchrony and homogeneity across space (e.g., energetic variables). A final discovery is that temporal attributes like stability are strong predictors of persistent spatial variation – a pattern that reflects how reliably resource concentrations occur in the same locations. This finding suggests the potential of time-for-space substitution, where one or few well-resolved time series could be used to infer landscape patterns. All but one of the tested approaches were data efficient and broadly-applicable across ecosystems and ecological processes. They thus contribute new possibilities for prediction when data are scarce, as well as new perspectives on dynamics in multi-variable landscapes. Research here shows that work at the intersection of spatial and temporal pattern can strengthen the interpretation of ecosystem dynamics and, more generally, foster synthesis from populations to landscapes. / Thesis / Doctor of Philosophy (PhD) / The physical and biological components of ecosystems are constantly in flux, varying in value among locations (spatially) and over time (temporally). This dynamism makes it difficult to predict current or future behaviours of ecological variables (e.g., population size). This thesis tests the potential of using spatial and temporal patterns to make inferences and predictions about changes in ecological systems. I tested three new theory-based tools in aquatic ecosystems, finding that: The size of temporal fluctuations in an ecosystem variable can be predicted from the size of value-differences among locations; spatial and temporal patterns can predict how a variable responds when isolated fragments of ecosystems are connected; and attributes of ecosystem variables (e.g., their stability) can indicate the likelihood of resources recurring in the same location. Findings show that new insight into spatial and temporal patterns can help prediction and management in complex landscapes.

This thesis explores the forms, fields and forces that relate to state governance of ‘the creative industries’ in South West England (1997-2010). Focusing on regional agencies that were involved in delivering Labour’s agenda for a ‘creative economy and elements of Creative Britain (DCMS et al., 2008), questions of multi-scalar governance, spatial-temporal ‘fix’ and re-scaling state space (Goodwin et al, 2005; Jessop, 2007) are examined. Despite the reported economic importance of ‘the creative industries’ (The Work Foundation, 2007), ‘joined up’ governance at the regional scale proved difficult to manage. A congested and turbulent institutional landscape at national and regional level was compounded by lack of fit between cultural and economic policies (Jayne, 2005; O’Connor, 2007; Pratt, 2005). Towards the end of Labour’s rule, Government fiscal reform and economic recession further threatened both economic and cultural 'state spaces' (Brenner, 2004) and by mid 2010 the regional experiment was over. Using a multi-level and in-depth case study approach, the thesis looks at how ‘historically specific configurations of state space are produced and incessantly reworked’ (Brenner, 2004: 76). Following discourse on ‘new state space’ (Jones and Jessop, 2010), a political geography of a state landscape is explored. Of particular significance, and highlighting the problematic interface between the economic and cultural spheres, are Culture South West, South West Screen and the South West Creative Economy Partnership. An argument is made that state bodies are both reactive and proactive mediators, whose ‘imaginaries of power’such as ‘the creative industries’, are hegemonic devices that evolve over time and space. Whether intentional or serendipity, the effects of structural and processual inter-relations are occasional ‘moments’ (Jones, 2009a) of coherence when governance success prevails. These moments are critical to state bodies for (re)producing hierarchies, (re)affirming power relations and (re)aligning political goals.

More frequent and harsh storms coupled with sea level rise are affecting Canada’s sensitive coastlines. This research studies Isle Madame in Cape Breton, Nova Scotia which has been designated by Natural Resource Canada as a sea level rise vulnerable coastal community in Canada. The research models the spatial and temporal impacts of sea level rise from storm surge by focusing on identifying vulnerable areas in the community via geographical information systems (GIS) using ArcGIS, as well as modeling dynamic coastal damage via system dynamics using STELLA. The research evaluates the impacts in terms of the environmental, social, cultural, economic pillars that profile the coastal community for a series of modelled Storm Scenarios. This research synthesizes information from a variety of sources including the coastal ecology and natural resources, as well as human society and socioeconomic indicators included in the four mentioned pillars. The objective of the research is to determine vulnerable areas on Isle Madame susceptible to storm damage, and consequently, to improve local community knowledge and preparedness to more frequent harsh storms. This research therefore presents a dynamic model for the evaluation of storm impacts in Isle Madame designed with the goal to help the community ultimately to plan and implement a strategy to adapt to pending environmental change.

More frequent and harsh storms coupled with sea level rise are affecting Canada’s sensitive coastlines. This research studies Isle Madame in Cape Breton, Nova Scotia which has been designated by Natural Resource Canada as a sea level rise vulnerable coastal community in Canada. The research models the spatial and temporal impacts of sea level rise from storm surge by focusing on identifying vulnerable areas in the community via geographical information systems (GIS) using ArcGIS, as well as modeling dynamic coastal damage via system dynamics using STELLA. The research evaluates the impacts in terms of the environmental, social, cultural, economic pillars that profile the coastal community for a series of modelled Storm Scenarios. This research synthesizes information from a variety of sources including the coastal ecology and natural resources, as well as human society and socioeconomic indicators included in the four mentioned pillars. The objective of the research is to determine vulnerable areas on Isle Madame susceptible to storm damage, and consequently, to improve local community knowledge and preparedness to more frequent harsh storms. This research therefore presents a dynamic model for the evaluation of storm impacts in Isle Madame designed with the goal to help the community ultimately to plan and implement a strategy to adapt to pending environmental change.

This thesis presents results from spatial-temporal and volumetric change analysis of blowouts on the Cape Cod National Seashore (CCNS) landscape in Massachusetts, USA. The purpose of this study is to use methods of analysing areal and volumetric changes in coastal dunes, specifically blowouts, and to detect patterns of change in order to contribute to the knowledge and literature on blowout evolution. In Chapter 2.0, the quantitative analysis of blowout change patterns in CCNS was examined at a landscape scale using Spatial-Temporal Analysis of Moving Polygons (STAMP). STAMP runs as an ArcGIS plugin and uses neighbouring year polygon layers of our digitized blowouts from sequential air photo and LiDAR data (1985, 1994, 2000, 2005, 2009, 2011, and 2012 for 30 erosional features, and 1998, 2000, 2007, and 2010 for 10 depositional features). The results from STAMP and the additional computations provided the following information on the evolution of blowouts: (1) both geometric and movement events occur on CCNS; (2) generation of blowouts in CCNS is greatest in 1985 and is potentially related to vegetation planting campaigns by the Park; (3) features are expanding towards dominant winds from the North West and the South West; (5) the erosional and depositional features are becoming more circular as they develop, (6) the evolution of CCNS blowouts follows a similar pattern to Gares and Nordstrom’s (1995) model with two additional stages: merging or dividing, and re-activation. In Chapter 3.0, the quantitative analysis of volumetric and areal change of 10 blowouts in CCNS at a landscape scale is examined using airborne LiDAR and air photos. The DEMs of neighbouring years (1998, 2000, 2007, and 2010) were differenced using Geomorphic Change Detection (GCD) software. Areal change was detected by differencing the area of polygons that were manually digitized in ArcGIS. The changes in wind data and vegetation cover were also examined. The results from the GCD and areal change analysis provide the following information on blowout evolution: (1) blowouts generate/initiate; (2) multiple blowouts can merge into an often larger blowout; (3) and blowouts can experience volumetric change with minimal aerial change and vice versa. From the analyzes of hourly Provincetown wind data (1998-2010), it was evident that blowouts developed within all three time intervals. The percentages of comparable winds (above 9.6 m s-1) were highest in 1998, 1999, 2007 and 2010. It is speculated that tropical storms and nor'easters are important drivers in the development of CCNS blowouts. In addition, supervised classifications were run on sequential air photos (1985 to 2009) to analyze vegetation cover. The results indicated an increase in vegetation cover and decrease of active sands over time. Two potential explanations that link increased vegetation to blowout development are: (1) sparse vegetation creates a more conducive environment for the initiation of blowouts by providing stability for the lateral walls, and (2) high wind events (e.g. hurricanes and nor'easters) could cause vegetation removal, allowing for areas of exposed sand for blowout initiation and development. / Graduate / 0799 / 0368 / kimia.abhar@gmail.com

More frequent and harsh storms coupled with sea level rise are affecting Canada’s sensitive coastlines. This research studies Isle Madame in Cape Breton, Nova Scotia which has been designated by Natural Resource Canada as a sea level rise vulnerable coastal community in Canada. The research models the spatial and temporal impacts of sea level rise from storm surge by focusing on identifying vulnerable areas in the community via geographical information systems (GIS) using ArcGIS, as well as modeling dynamic coastal damage via system dynamics using STELLA. The research evaluates the impacts in terms of the environmental, social, cultural, economic pillars that profile the coastal community for a series of modelled Storm Scenarios. This research synthesizes information from a variety of sources including the coastal ecology and natural resources, as well as human society and socioeconomic indicators included in the four mentioned pillars. The objective of the research is to determine vulnerable areas on Isle Madame susceptible to storm damage, and consequently, to improve local community knowledge and preparedness to more frequent harsh storms. This research therefore presents a dynamic model for the evaluation of storm impacts in Isle Madame designed with the goal to help the community ultimately to plan and implement a strategy to adapt to pending environmental change.

This thesis presents results from spatial-temporal and volumetric change analysis of blowouts on the Cape Cod National Seashore (CCNS) landscape in Massachusetts, USA. The purpose of this study is to use methods of analysing areal and volumetric changes in coastal dunes, specifically blowouts, and to detect patterns of change in order to contribute to the knowledge and literature on blowout evolution. In Chapter 2.0, the quantitative analysis of blowout change patterns in CCNS was examined at a landscape scale using Spatial-Temporal Analysis of Moving Polygons (STAMP). STAMP runs as an ArcGIS plugin and uses neighbouring year polygon layers of our digitized blowouts from sequential air photo and LiDAR data (1985, 1994, 2000, 2005, 2009, 2011, and 2012 for 30 erosional features, and 1998, 2000, 2007, and 2010 for 10 depositional features). The results from STAMP and the additional computations provided the following information on the evolution of blowouts: (1) both geometric and movement events occur on CCNS; (2) generation of blowouts in CCNS is greatest in 1985 and is potentially related to vegetation planting campaigns by the Park; (3) features are expanding towards dominant winds from the North West and the South West; (5) the erosional and depositional features are becoming more circular as they develop, (6) the evolution of CCNS blowouts follows a similar pattern to Gares and Nordstrom’s (1995) model with two additional stages: merging or dividing, and re-activation. In Chapter 3.0, the quantitative analysis of volumetric and areal change of 10 blowouts in CCNS at a landscape scale is examined using airborne LiDAR and air photos. The DEMs of neighbouring years (1998, 2000, 2007, and 2010) were differenced using Geomorphic Change Detection (GCD) software. Areal change was detected by differencing the area of polygons that were manually digitized in ArcGIS. The changes in wind data and vegetation cover were also examined. The results from the GCD and areal change analysis provide the following information on blowout evolution: (1) blowouts generate/initiate; (2) multiple blowouts can merge into an often larger blowout; (3) and blowouts can experience volumetric change with minimal aerial change and vice versa. From the analyzes of hourly Provincetown wind data (1998-2010), it was evident that blowouts developed within all three time intervals. The percentages of comparable winds (above 9.6 m s-1) were highest in 1998, 1999, 2007 and 2010. It is speculated that tropical storms and nor'easters are important drivers in the development of CCNS blowouts. In addition, supervised classifications were run on sequential air photos (1985 to 2009) to analyze vegetation cover. The results indicated an increase in vegetation cover and decrease of active sands over time. Two potential explanations that link increased vegetation to blowout development are: (1) sparse vegetation creates a more conducive environment for the initiation of blowouts by providing stability for the lateral walls, and (2) high wind events (e.g. hurricanes and nor'easters) could cause vegetation removal, allowing for areas of exposed sand for blowout initiation and development. / Graduate / 0799 / 0368 / kimia.abhar@gmail.com