Matching Items (2)
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- All Subjects: mobility
- All Subjects: spatial statistics
- Genre: Academic theses
- Creators: Alonzi, Elise
Description
As urban populations become increasingly dense, massive amounts of new 'big' data that characterize human activity are being made available and may be characterized as having a large volume of observations, being produced in real-time or near real-time, and including a diverse variety of information. In particular, spatial interaction (SI) data - a collection of human interactions across a set of origins and destination locations - present unique challenges for distilling big data into insight. Therefore, this dissertation identifies some of the potential and pitfalls associated with new sources of big SI data. It also evaluates methods for modeling SI to investigate the relationships that drive SI processes in order to focus on human behavior rather than data description.
A critical review of the existing SI modeling paradigms is first presented, which also highlights features of big data that are particular to SI data. Next, a simulation experiment is carried out to evaluate three different statistical modeling frameworks for SI data that are supported by different underlying conceptual frameworks. Then, two approaches are taken to identify the potential and pitfalls associated with two newer sources of data from New York City - bike-share cycling trips and taxi trips. The first approach builds a model of commuting behavior using a traditional census data set and then compares the results for the same model when it is applied to these newer data sources. The second approach examines how the increased temporal resolution of big SI data may be incorporated into SI models.
Several important results are obtained through this research. First, it is demonstrated that different SI models account for different types of spatial effects and that the Competing Destination framework seems to be the most robust for capturing spatial structure effects. Second, newer sources of big SI data are shown to be very useful for complimenting traditional sources of data, though they are not sufficient substitutions. Finally, it is demonstrated that the increased temporal resolution of new data sources may usher in a new era of SI modeling that allows us to better understand the dynamics of human behavior.
A critical review of the existing SI modeling paradigms is first presented, which also highlights features of big data that are particular to SI data. Next, a simulation experiment is carried out to evaluate three different statistical modeling frameworks for SI data that are supported by different underlying conceptual frameworks. Then, two approaches are taken to identify the potential and pitfalls associated with two newer sources of data from New York City - bike-share cycling trips and taxi trips. The first approach builds a model of commuting behavior using a traditional census data set and then compares the results for the same model when it is applied to these newer data sources. The second approach examines how the increased temporal resolution of big SI data may be incorporated into SI models.
Several important results are obtained through this research. First, it is demonstrated that different SI models account for different types of spatial effects and that the Competing Destination framework seems to be the most robust for capturing spatial structure effects. Second, newer sources of big SI data are shown to be very useful for complimenting traditional sources of data, though they are not sufficient substitutions. Finally, it is demonstrated that the increased temporal resolution of new data sources may usher in a new era of SI modeling that allows us to better understand the dynamics of human behavior.
ContributorsOshan, Taylor Matthew (Author) / Fotheringham, A. S. (Thesis advisor) / Farmer, Carson J.Q. (Committee member) / Rey, Sergio S.J. (Committee member) / Nelson, Trisalyn (Committee member) / Arizona State University (Publisher)
Created2017
Description
Mobility is an important aspect of the lives of religious individuals described by medieval texts in early and late medieval Ireland, and biogeochemical methods can be used to detect mobility in archaeological populations. Stories are recorded of monks and nuns traveling and founding monasteries across Ireland, Scotland, England, Wales, and other areas of Europe. However, these texts rarely address the quotidian lives of average monks and nuns who lived in monastic communities. This dissertation seeks to understand if travel was a typical part of the experiences of religious and lay people in early and late medieval Ireland. It also aims to increase understanding of how monastic communities related to the local lay communities, including addressing if the monastery was populated by those who grew up in the local area. Another methodological aim of this dissertation is to advance the field of archaeological biogeochemistry by (1) adding to the bioavailable strontium baseline in Ireland and (2) quantifying the contribution of ocean-derived strontium to coastal environments. These topics are explored through the biogeochemical analysis of 88 individuals buried at 5 early and late medieval monasteries in Ireland and the analysis of a total of 85 plant samples from four counties in Ireland. The three papers in this dissertation present: (1) a summary of the mobility of religious and lay people buried at the monasteries (Chapter 2), (2) a case study presenting evidence for fosterage of a local child at the early medieval monastery of Illaunloughan, Co. Kerry (Chapter 3), and (3) a study designed to quantify the impact of sea spray on bioavailable strontium in coastal environments (Chapter 4). The majority of lay and religious individuals studied were estimated to be local, indicating that medieval Irish Christianity was strongly rooted in the local community. The study of ocean-derived strontium in a coastal environment indicates that sea spray has a non-uniform impact on bioavailable strontium in coastal regions. These findings shed new light on medieval monastic and lay life in Ireland through the application of biogeochemical methods, contributing to the growth of the field of archaeological chemistry in Ireland.
ContributorsAlonzi, Elise (Author) / Knudson, Kelly (Thesis advisor) / Hegmon, Michelle (Committee member) / Scott, Rachel (Committee member) / Stojanowski, Christopher (Committee member) / Arizona State University (Publisher)
Created2018