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Spatiotemporal data mining, analysis, and visualization of human activity data

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This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data mining, machine learning, and…

This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data mining, machine learning, and geovisualization techniques. Three different types of spatiotemporal activity data were collected through different data collection approaches: (1) crowd sourced geo-tagged digital photos, representing people's travel activity, were retrieved from the website Panoramio.com through information retrieval techniques; (2) the same techniques were used to crawl crowd sourced GPS trajectory data and related metadata of their daily activities from the website OpenStreetMap.org; and finally (3) preschool children's daily activities and interactions tagged with time and geographical location were collected with a novel TabletPC-based behavioral coding system. The proposed methodology is applied to these data to (1) automatically recommend optimal multi-day and multi-stay travel itineraries for travelers based on discovered attractions from geo-tagged photos, (2) automatically detect movement types of unknown moving objects from GPS trajectories, and (3) explore dynamic social and socio-spatial patterns of preschool children's behavior from both geographic and social perspectives.
ContributorsLi, Xun (Author) / Anselin, Luc (Thesis advisor) / Koschinsky, Julia (Committee member) / Maciejewski, Ross (Committee member) / Rey, Sergio (Committee member) / Griffin, William (Committee member) / Arizona State University (Publisher)
Created2012
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Understanding open spaces in an arid city

Description

This doctoral dissertation research aims to develop a comprehensive definition of urban open spaces and to determine the extent of environmental, social and economic impacts of open spaces on cities and the people living there. The approach I take to define urban open space is to apply fuzzy set theory…

This doctoral dissertation research aims to develop a comprehensive definition of urban open spaces and to determine the extent of environmental, social and economic impacts of open spaces on cities and the people living there. The approach I take to define urban open space is to apply fuzzy set theory to conceptualize the physical characteristics of open spaces. In addition, a 'W-green index' is developed to quantify the scope of greenness in urban open spaces. Finally, I characterize the environmental impact of open spaces' greenness on the surface temperature, explore the social benefits through observing recreation and relaxation, and identify the relationship between housing price and open space be creating a hedonic model on nearby housing to quantify the economic impact. Fuzzy open space mapping helps to investigate the landscape characteristics of existing-recognized open spaces as well as other areas that can serve as open spaces. Research findings indicated that two fuzzy open space values are effective to the variability in different land-use types and between arid and humid cities. W-Green index quantifies the greenness for various types of open spaces. Most parks in Tempe, Arizona are grass-dominant with higher W-Green index, while natural landscapes are shrub-dominant with lower index. W-Green index has the advantage to explain vegetation composition and structural characteristics in open spaces. The outputs of comprehensive analyses show that the different qualities and types of open spaces, including size, greenness, equipment (facility), and surrounding areas, have different patterns in the reduction of surface temperature and the number of physical activities. The variance in housing prices through the distance to park was, however, not clear in this research. This dissertation project provides better insight into how to describe, plan, and prioritize the functions and types of urban open spaces need for sustainable living. This project builds a comprehensive framework for analyzing urban open spaces in an arid city. This dissertation helps expand the view for urban environment and play a key role in establishing a strategy and finding decision-makings.
ContributorsKim, Won Kyung (Author) / Wentz, Elizabeth (Thesis advisor) / Myint, Soe W (Thesis advisor) / Brazel, Anthony (Committee member) / Guhathakurta, Subhrajit (Committee member) / Arizona State University (Publisher)
Created2011
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Assessing Usable Ground and Surface Water Level Correlation Factors in the Western United States

Description
The Western Continental United States has a rapidly changing and complex ecosystem that provides valuable resources to a large portion of the nation. Changes in social and environmental factors have been observed to be significantly correlated to usable ground and surface water levels. The assessment of water level changes and…

The Western Continental United States has a rapidly changing and complex ecosystem that provides valuable resources to a large portion of the nation. Changes in social and environmental factors have been observed to be significantly correlated to usable ground and surface water levels. The assessment of water level changes and their influences on a semi-national level is needed to support planning and decision making for water resource management at local levels. Although many studies have been done in Ground and Surface Water (GSW) trend analysis, very few have attempted determine correlations with other factors. The number of studies done on correlation factors at a semi-national scale and near decadal temporal scale is even fewer. In this study, freshwater resources in GSW changes from 2004 to 2017 were quantified and used to determine if and how environmental and social variables are related to GSW changes using publicly available remotely sensed and census data. Results indicate that mean annual changes of GSW of the study period are significantly correlated with LULC changes related to deforestation, urbanization, environmental trends, as well as social variables. Further analysis indicates a strong correlation in the rate of change of GSW to LULC changes related to deforestation, environmental trends, as well as social variables. GSW slope trend analysis also reveals a negative trend in California, New Mexico, Arizona, and Nevada. Whereas a positive GSW trend is evident in the northeast part of the study area. GSW trends were found to be somewhat consistent in the states of Utah, Idaho, and Colorado, implying that there was no GSW changes over time in these states.
ContributorsReynolds, Ryan (Author) / Myint, Soe (Thesis advisor) / Werth, Susanna (Committee member) / Brazel, Anthony (Committee member) / Arizona State University (Publisher)
Created2018
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Examining Processes That Reflect Heterogeneity in Maritally Satisfied Couples

Description
In the mid-1970s, social scientists began observing marital dyad conversations in laboratory settings with the hope of determining which observable features best discriminate couples who report being either satisfied or unsatisfied with their relationship. These studies continued until about a decade ago when, in addition to increasing laboratory costs slowing…

In the mid-1970s, social scientists began observing marital dyad conversations in laboratory settings with the hope of determining which observable features best discriminate couples who report being either satisfied or unsatisfied with their relationship. These studies continued until about a decade ago when, in addition to increasing laboratory costs slowing the pace of new data collection, researchers realized that distressed couples were easier to quantitatively describe than nondistressed couples. Specifically, distressed couples exhibit rigid patterns of negativity whereas couples who report being maritally satisfied show minimal rigidity in the opposite direction \u2014 positivity. This was, and is, a theoretical dilemma: how can clinicians understand and eventually modify distressed relationships when the behavior of satisfied couples are less patterned, less predictable and more diverse? A recent study by Griffin and Li (2015), using contemporary machine learning techniques, reanalyzed existing marital interaction data and found that, contrary to expectation and existing theory, nondistressed couples should be further subdivided into two groups \u2014 those who are predictably positive or neutral and those who interact using diverse and varying levels of positive and negative behaviors. The latter group is the focus of this thesis. Using these recent findings as discussion points, I review how the unexpected behaviors in this novel group can maintain and possibly perpetuate marital satisfaction.
ContributorsAbdul-Quadir, Hasana (Author) / Griffin, William A. (Thesis director) / Li, Xun (Committee member) / Barrett, The Honors College (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor) / School of International Letters and Cultures (Contributor) / Hugh Downs School of Human Communication (Contributor)
Created2015-05