Laura Tateosian

Perceptually based brush strokes for nonphotorealistic visualization

An important problem in the area of computer graphics is the visualization of large, complex information spaces. Datasets of this type have grown rapidly in recent years, both in number and in size. Images of the data stored in these collections must support rapid and accurate exploration and analysis. This article presents a method for constructing visualizations that are both effective and aesthetic. Our approach uses techniques from master paintings and human perception to visualize a multidimensional dataset. Individual data elements are drawn with one or more brush strokes that vary their appearance to represent the elements attribute values. The result is a nonphotorealistic visualization of information stored in the dataset. Our research extends existing glyph-based and nonphotorealistic techniques by applying perceptual guidelines to build an effective representation of the underlying data. The nonphotorealistic properties the strokes employ are selected from studies of the history and theory of Impressionist art. We show that these properties are similar to visual features that are detected by the low-level human visual system. This correspondence allows us to manage the strokes to produce perceptually salient visualizations. Psychophysical experiments confirm a strong relationship between the expressive power of our nonphotorealistic properties and previous findings on the use of perceptual color and texture patterns for data display. Results from these studies are used to produce effective nonphotorealistic visualizations. We conclude by applying our techniques to a large, multidimensional weather dataset to demonstrate their viability in a practical, real-world setting.

TanGeoMS: Tangible Geospatial Modeling System

We present TanGeoMS, a tangible geospatial modeling visualization system that couples a laser scanner, projector, and a flexible physical three-dimensional model with a standard geospatial information system (GIS) to create a tangible user interface for terrain data. TanGeoMS projects an image of real-world data onto a physical terrain model. Users can alter the topography of the model by modifying the clay surface or placing additional objects on the surface. The modified model is captured by an overhead laser scanner then imported into a GIS for analysis and simulation of real-world processes. The results are projected back onto the surface of the model providing feedback on the impact of the modifications on terrain parameters and simulated processes. Interaction with a physical model is highly intuitive, allowing users to base initial design decisions on geospatial data, test the impact of these decisions in GIS simulations, and use the feedback to improve their design. We demonstrate the system on three applications: investigating runoff management within a watershed, assessing the impact of storm surge on barrier islands, and exploring landscape rehabilitation in military training areas.

Engaging viewers through nonphotorealistic visualizations

Research in human visual cognition suggests that beautiful images can engage the visual system, encouraging it to linger in certain locations in an image and absorb subtle details. By developing aesthetically pleasing visualizations of data, we aim to engage viewers and promote prolonged inspection, which can lead to new discoveries within the data. We present three new visualization techniques that apply painterly rendering styles to vary interpretational complexity (IC), indication and detail (ID), and visual complexity (VC), image properties that are important to aesthetics. Knowledge of human visual perception and psychophysical models of aesthetics provide the theoretical basis for our designs. Computational geometry and nonphotorealistic algorithms are used to preprocess the data and render the visualizations. We demonstrate the techniques with visualizations of real weather and supernova data.

Designing a visualization framework for multidimensional data

Interest in visualization has grown in recent years, producing rapid advances in the diversity of research and in the scope of proposed techniques. Much of the initial focus in computer-based visualization concentrated on display algorithms, often for specific domains. For example, volume, flow, and terrain visualization techniques have generated significant insights into fundamental graphics and visualization theory, aiding the application experts who use these techniques to advance their own research. More recent work has extended visualization to abstract data sets like network intrusion detection, recommender systems, and database query results. This article describes our initial end-to-end system that starts with data management and continues through assisted visualization design, display, navigation, and user interaction. The purposes of this discussion are to (i) promote a more comprehensive visualization framework; (ii) describe how to apply expertise from human psychophysics, databases, rational logic, and artificial intelligence to visualization; and (iii) illustrate the benefits of a more complete framework using examples from our own experiences.

GIS-based Analysis of Coastal Lidar Time-Series

Introduction.- Processing coastal lidar time series.- Raster-based analysis.- Feature extraction and feature change metrics.- Volume analysis.- Visualizing coastal change.- Appendix.

Visualizations of coastal terrain time series

In coastal regions, water, wind, gravitation, vegetation, and human activity continuously alter landscape surfaces. Visualizations are important for understanding coastal landscape evolution and its driving processes. Visualizing change in highly dynamic coastal terrain poses a formidable challenge; the combination of natural and anthropogenic forces leads to cycles of retreat and recovery and complex morphology of landforms. In recent years, repeated high-resolution laser terrain scans have generated a time series of point cloud data that represent landscapes at snapshots in time, including the impacts of major storms. In this article, we build on existing approaches for visualizing spatial–temporal data to create a collection of perceptual visualizations to support coastal terrain evolution analysis. We extract terrain features and track their migration; we derive temporal summary maps and heat graphs that quantify the pattern of elevation change and sediment redistribution and use the space–time cube concept to create visualizations of terrain evolution. The space–time cube approach allows us to represent shoreline evolution as an isosurface extracted from a voxel model created by stacking time series of digital elevation models. We illustrate our approach on a series of Light Detection and Ranging surveys of sandy North Carolina barrier islands. Our results reveal terrain changes of shoreline and dune ridge migration, dune breaches and overwash, the formation of new dune ridges, and the construction and destruction of homes, changes which are due to erosion and accretion, hurricanes, and human activities. These events are all visualized within their geographic and temporal contexts.

Who’s Watching Your Food? A Flexible Framework for Public Health Monitoring

By responding to potentially life-threatening emergencies such as foodborne illnesses and water contamination, U.S. public health agencies play a vital role in promoting human health and protecting the environment. Local, state, and federal partners must collaborate to strategically plan initiatives, allocate resources, and evaluate emergency response activities. These collaborative decision-making processes can be improved by using web-based mapping applications for visualization and analysis. We developed a web-based GIS framework which is applied to public health data for North Carolinas (NC) Department of Health and Human Services. The application visualizes all state-regulated food service facilities and supports query and analysis tools crucial for food recalls or radiation contamination tracking. Built with PostgreSQL/PostGIS, GeoServer, and a customized GeoExplorer map viewer, the framework delivers a web-based mapping tool that is flexible and Open Source. The flexibility of the framework is an important dimension of its scalability, allowing it to be customizable, modular, and portable so that it is easily configurable to support additional research and education initiatives. This approach reverses a trend toward application-specific web mapping development in Open Source GIS. To demonstrate flexibility, we configured an additional website for forest landowner management to be used by another state agency, the NC Forest Service.

Stevens dot patterns for 2D flow visualization

This paper describes a new technique to visualize 2D flow fields with a sparse collection of dots. A cognitive model proposed by Kent Stevens describes how spatially local configurations of dots are processed in parallel by the low-level visual system to perceive orientations throughout the image. We integrate this model into a visualization algorithm that converts a sparse grid of dots into patterns that capture flow orientations in an underlying flow field. We describe how our algorithm supports large flow fields that exceed the capabilities of a display device, and demonstrate how to include properties like direction and velocity in our visualizations. We conclude by applying our technique to 2D slices from a simulated supernova collapse.

GazeGIS: A Gaze-Based Reading and Dynamic Geographic Information System

Location is an important component of a narrative. Mapped place names provide vital geographical, economic, historical, political, and cultural context for the text. Online sources such as news articles, travel logs, and blogs frequently refer to geographic locations, but often these are not mapped. When a map is provided, the reader is still responsible for matching references in the text with map positions. As they read a place name within the text, readers must locate its map position, then find their place again in the text to resume reading, and repeat this for each toponym. We propose a gaze-based reading and dynamic geographic information system (GazeGIS) which uses eye tracking and geoparsing to enable a more cohesive reading experience by dynamically mapping locations just as they are encountered within the text. We developed a prototype GazeGIS application and demonstrated its application to several narrative passages. We conducted a study in which participants read text passages using the system and evaluated their experience. We also explored an application for intelligence analysis and discuss how experts in this domain envision its use. Layman and intelligence expert evaluations indicate a positive reception for this new reading paradigm. This could change the way we read online news and e-books, the way school children study political science and geography, the way officers study military history, the way intelligence analysts consume reports, and the way we plan our next vacation.

Raster-Based Analysis

Raster-based analysis on two or more DEMs can provide information about change patterns and trends. A common approach to mapping elevation change between two surveys is DEM differencing, performed by map algebra within GIS (r.mapcalc in GRASS). For a larger number of elevation data snapshots, per cell statistics can be applied to the raster DEMs to derive summary maps, which reveal the spatial patterns of stable and dynamic sites, the time periods when sites reach their highest or lowest elevations, and the trends in elevation change.