Visualisation of Origins, Destinations and Flows with OD Maps

We present a new technique for the visual exploration of origins (O) and destinations (D) arranged in geographic space. Previous attempts to map the flows between origins and destinations have suffered from problems of occlusion usually requiring some form of generalisation, such as aggregation or flow density estimation before they can be visualized. This can lead to loss of detail or the introduction of arbitrary artefacts in the visual representation. Here, we propose mapping OD vectors as cells rather than lines, comparable with the process of constructing OD matrices, but unlike the OD matrix, we preserve the spatial layout of all origin and destination locations by constructing a gridded two‐level spatial treemap. The result is a set of spatially ordered small multiples upon which any arbitrary geographic data may be projected. Using a hash grid spatial data structure, we explore the characteristics of the technique through a software prototype that allows interactive query and visualisation of 105‐106 simulated and recorded OD vectors. The technique is illustrated using US county to county migration and commuting statistics

Doctor of Philosophy

dissertationRecent advancements in mobile devices - such as Global Positioning System (GPS), cellular phones, car navigation system, and radio-frequency identification (RFID) - have greatly influenced the nature and volume of data about individual-based movement in space and time. Due to the prevalence of mobile devices, vast amounts of mobile objects data are being produced and stored in databases, overwhelming the capacity of traditional spatial analytical methods. There is a growing need for discovering unexpected patterns, trends, and relationships that are hidden in the massive mobile objects data. Geographic visualization (GVis) and knowledge discovery in databases (KDD) are two major research fields that are associated with knowledge discovery and construction. Their major research challenges are the integration of GVis and KDD, enhancing the ability to handle large volume mobile objects data, and high interactivity between the computer and users of GVis and KDD tools. This dissertation proposes a visualization toolkit to enable highly interactive visual data exploration for mobile objects datasets. Vector algebraic representation and online analytical processing (OLAP) are utilized for managing and querying the mobile object data to accomplish high interactivity of the visualization tool. In addition, reconstructing trajectories at user-defined levels of temporal granularity with time aggregation methods allows exploration of the individual objects at different levels of movement generality. At a given level of generality, individual paths can be combined into synthetic summary paths based on three similarity measures, namely, locational similarity, directional similarity, and geometric similarity functions. A visualization toolkit based on the space-time cube concept exploits these functionalities to create a user-interactive environment for exploring mobile objects data. Furthermore, the characteristics of visualized trajectories are exported to be utilized for data mining, which leads to the integration of GVis and KDD. Case studies using three movement datasets (personal travel data survey in Lexington, Kentucky, wild chicken movement data in Thailand, and self-tracking data in Utah) demonstrate the potential of the system to extract meaningful patterns from the otherwise difficult to comprehend collections of space-time trajectories

Spatial Clustering, Inequality and Income Convergence

This paper examines the relationship between spatial clustering and inequality at the county scale with overall state per capita income in the U.S. over the period 1969-2000. For each of the 48 coterminous states we examine measures of inequality and spatial clustering and explore how a state's overall income level may be influenced by, or influence, these measures. Our exploratory analysis utilizes the open- source package Space-Time Analysis of Regional Systems (STARS) to illustrate some new techniques for analyzing regional income dynamics. The results provide insight into the possible relationships between inequality, clustering and relative income levels, and generates a number of interesting avenues for future research.spatial clustering; spatial dependence; inequality; convergence; geocomputation

Integrating Multiple 3D Views through Frame-of-reference Interaction

Frame-of-reference interaction consists of a unified set of 3D interaction techniques for exploratory navigation of large virtual spaces in nonimmersive environments. It is based on a conceptual framework that considers navigation from a cognitive perspective, as a way of facilitating changes in user attention from one reference frame to another, rather than from the mechanical perspective of moving a camera between different points of interest. All of our techniques link multiple frames of reference in some meaningful way. Some techniques link multiple windows within a zooming environment while others allow seamless changes of user focus between static objects, moving objects, and groups of moving objects. We present our techniques as they are implemented in GeoZui3D, a geographic visualization system for ocean data

Stacking-based visualization of trajectory attribute data

Visualizing trajectory attribute data is challenging because it involves showing the trajectories in their spatio-temporal context as well as the attribute values associated with the individual points of trajectories. Previous work on trajectory visualization addresses selected aspects of this problem, but not all of them. We present a novel approach to visualizing trajectory attribute data. Our solution covers space, time, and attribute values. Based on an analysis of relevant visualization tasks, we designed the visualization solution around the principle of stacking trajectory bands. The core of our approach is a hybrid 2D/3D display. A 2D map serves as a reference for the spatial context, and the trajectories are visualized as stacked 3D trajectory bands along which attribute values are encoded by color. Time is integrated through appropriate ordering of bands and through a dynamic query mechanism that feeds temporally aggregated information to a circular time display. An additional 2D time graph shows temporal information in full detail by stacking 2D trajectory bands. Our solution is equipped with analytical and interactive mechanisms for selecting and ordering of trajectories, and adjusting the color mapping, as well as coordinated highlighting and dedicated 3D navigation. We demonstrate the usefulness of our novel visualization by three examples related to radiation surveillance, traffic analysis, and maritime navigation. User feedback obtained in a small experiment indicates that our hybrid 2D/3D solution can be operated quite well

A Fast and Scalable System to Visualize Contour Gradient from Spatio-temporal Data

Changes in geological processes that span over the years may often go unnoticed due to their inherent noise and variability. Natural phenomena such as riverbank erosion, and climate change in general, is invisible to humans unless appropriate measures are taken to analyze the underlying data. Visualization helps geological sciences to generate scientific insights into such long-term geological events. Commonly used approaches such as side-by-side contour plots and spaghetti plots do not provide a clear idea about the historical spatial trends. To overcome this challenge, we propose an image-gradient based approach called ContourDiff. ContourDiff overlays gradient vector over contour plots to analyze the trends of change across spatial regions and temporal domain. Our approach first aggregates for each location, its value differences from the neighboring points over the temporal domain, and then creates a vector field representing the prominent changes. Finally, it overlays the vectors (differential trends) along the contour paths, revealing the differential trends that the contour lines (isolines) experienced over time. We designed an interface, where users can interact with the generated visualization to reveal changes and trends in geospatial data. We evaluated our system using real-life datasets, consisting of millions of data points, where the visualizations were generated in less than a minute in a single-threaded execution. We show the potential of the system in detecting subtle changes from almost identical images, describe implementation challenges, speed-up techniques, and scope for improvements. Our experimental results reveal that ContourDiff can reliably visualize the differential trends, and provide a new way to explore the change pattern in spatiotemporal data. The expert evaluation of our system using real-life WRF (Weather Research and Forecasting) model output reveals the potential of our technique to generate useful insights on the spatio-temporal trends of geospatial variables

Phase transitions during fruiting body formation in Myxococcus xanthus

The formation of a collectively moving group benefits individuals within a population in a variety of ways such as ultra-sensitivity to perturbation, collective modes of feeding, and protection from environmental stress. While some collective groups use a single organizing principle, others can dynamically shift the behavior of the group by modifying the interaction rules at the individual level. The surface-dwelling bacterium Myxococcus xanthus forms dynamic collective groups both to feed on prey and to aggregate during times of starvation. The latter behavior, termed fruiting-body formation, involves a complex, coordinated series of density changes that ultimately lead to three-dimensional aggregates comprising hundreds of thousands of cells and spores. This multi-step developmental process most likely involves several different single-celled behaviors as the population condenses from a loose, two-dimensional sheet to a three-dimensional mound. Here, we use high-resolution microscopy and computer vision software to spatiotemporally track the motion of thousands of individuals during the initial stages of fruiting body formation. We find that a combination of cell-contact-mediated alignment and internal timing mechanisms drive a phase transition from exploratory flocking, in which cell groups move rapidly and coherently over long distances, to a reversal-mediated localization into streams, which act as slow-spreading, quasi-one-dimensional nematic fluids. These observations lead us to an active liquid crystal description of the myxobacterial development cycle.Comment: 16 pages, 5 figure

Ribosomal trafficking is reduced in Schwann cells following induction of myelination.

Local synthesis of proteins within the Schwann cell periphery is extremely important for efficient process extension and myelination, when cells undergo dramatic changes in polarity and geometry. Still, it is unclear how ribosomal distributions are developed and maintained within Schwann cell projections to sustain local translation. In this multi-disciplinary study, we expressed a plasmid encoding a fluorescently labeled ribosomal subunit (L4-GFP) in cultured primary rat Schwann cells. This enabled the generation of high-resolution, quantitative data on ribosomal distributions and trafficking dynamics within Schwann cells during early stages of myelination, induced by ascorbic acid treatment. Ribosomes were distributed throughout Schwann cell projections, with ~2-3 bright clusters along each projection. Clusters emerged within 1 day of culture and were maintained throughout early stages of myelination. Three days after induction of myelination, net ribosomal movement remained anterograde (directed away from the Schwann cell body), but ribosomal velocity decreased to about half the levels of the untreated group. Statistical and modeling analysis provided additional insight into key factors underlying ribosomal trafficking. Multiple regression analysis indicated that net transport at early time points was dependent on anterograde velocity, but shifted to dependence on anterograde duration at later time points. A simple, data-driven rate kinetics model suggested that the observed decrease in net ribosomal movement was primarily dictated by an increased conversion of anterograde particles to stationary particles, rather than changes in other directional parameters. These results reveal the strength of a combined experimental and theoretical approach in examining protein localization and transport, and provide evidence of an early establishment of ribosomal populations within Schwann cell projections with a reduction in trafficking following initiation of myelination