abstract: In today's world, unprecedented amounts of data of individual mobile objects have become more available due to advances in location aware technologies and services. Studying the spatio-temporal patterns, processes, and behavior of mobile objects is an important issue for extracting useful information and knowledge about mobile phenomena. Potential applications across a wide range of fields include urban and transportation planning, Location-Based Services, and logistics. This research is designed to contribute to the existing state-of-the-art in tracking and modeling mobile objects, specifically targeting three challenges in investigating spatio-temporal patterns and processes; 1) a lack of space-time analysis tools; 2) a lack of studies about empirical data analysis and context awareness of mobile objects; and 3) a lack of studies about how to evaluate and test agent-based models of complex mobile phenomena. Three studies are proposed to investigate these challenges; the first study develops an integrated data analysis toolkit for exploration of spatio-temporal patterns and processes of mobile objects; the second study investigates two movement behaviors, 1) theoretical random walks and 2) human movements in urban space collected by GPS; and, the third study contributes to the research challenge of evaluating the form and fit of Agent-Based Models of human movement in urban space. The main contribution of this work is the conceptualization and implementation of a Geographic Knowledge Discovery approach for extracting high-level knowledge from low-level datasets about mobile objects. This allows better understanding of space-time patterns and processes of mobile objects by revealing their complex movement behaviors, interactions, and collective behaviors. In detail, this research proposes a novel analytical framework that integrates time geography, trajectory data mining, and 3D volume visualization. In addition, a toolkit that utilizes the framework is developed and used for investigating theoretical and empirical datasets about mobile objects. The results showed that the framework and the toolkit demonstrate a great capability to identify and visualize clusters of various movement behaviors in space and time. / Dissertation/Thesis / Ph.D. Geography 2011

ABSTRACT Research in GIScience has identified agent-based simulation methodologies as effective in the study of complex adaptive spatial systems (CASS). CASS are characterized by the emergent nature of their spatial expressions and by the changing relationships between their constituent variables and how those variables act on the system's spatial expression over time. Here, emergence refers to a CASS property where small-scale, individual action results in macroscopic or system-level patterns over time. This research develops and executes a spatially-explicit agent based model of Muscovy Duck home range behavior. Muscovy duck home range behavior is regarded as a complex adaptive spatial system for this research, where this process can be explained and studied with simulation techniques. The general animal movement model framework presented in this research explicitly considers spatial characteristics of the landscape in its formulation, as well as provides for spatial cognition in the behavior of its agents. Specification of the model followed a three-phase framework, including: behavioral data collection in the field, construction of a model substrate depicting land cover features found in the study area, and the informing of model agents with products derived from field observations. This framework was applied in the construction of a spatially-explicit agent-based model (SE-ABM) of Muscovy Duck home range behavior. The model was run 30 times to simulate point location distributions of an individual duck's daily activity. These simulated datasets were collected, and home ranges were constructed using Characteristic Hull Polygon (CHP) and Minimum Convex Polygon (MCP) techniques. Descriptive statistics of the CHP and MCP polygons were calculated to characterize the home ranges produced and establish internal model validity. As a theoretical framework for the construction of animal movement SE-ABM's, and as a demonstration of the potential of geosimulation methodologies in support of animal home range estimator validation, the model represents an original contribution to the literature. Implications of model utility as a validation tool for home range extents as derived from GPS or radio telemetry positioning data are discussed.