Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Levels of Use of a GIS

Levels of Use of a GIS

Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...

Vector Algebra: Graphical Method

Vector Algebra: Graphical Method

Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
We use the laws of geometry to construct resultant vectors, followed by trigonometry to find vector magnitudes and directions. For a geometric construction of the sum of two vectors in a plane, we follow the parallelogram rule. Suppose two vectors are at arbitrary positions. Translate either one of...

Selected Data About Geographic Locations

Selected Data About Geographic Locations

Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...

Plotting of Topographic Maps

Plotting of Topographic Maps

Topographic maps represent the Earth's surface features using contour lines, which connect points of equal elevation to create a two-dimensional representation of three-dimensional terrain. Creating a topographic map requires a systematic approach.Begin by plotting a scaled grid and marking intersections corresponding to the survey's elevation data points. Assign elevation values at these intersections to build the base map. Next, determine contour levels using a consistent contour interval,...

Introduction to GIS

Introduction to GIS

Geographic Information Systems (GIS) are tools for storing, analyzing, and displaying spatial data alongside related attributes. Unlike traditional information systems that address general queries, GIS incorporates spatial components, enabling users to answer "where" and "how far." For example, GIS can process housing data linked to geographic locations like zip codes, allowing insights into population density or housing distribution through thematic maps.GIS integrates technologies such as...

Thematic Layering in GIS

Thematic Layering in GIS

In the past, planning projects such as schools or public facilities required extensive manual effort to gather and compile data. Information such as property boundaries, soil characteristics, road networks, zoning regulations, and flood zones had to be sourced individually from courthouses, utility providers, and registry offices. Assembling these datasets into a coherent format often took several months, delaying project timelines.The introduction of Geographic Information Systems (GIS)...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

LAMDA: Aiding Visual Exploration of Atomic Displacements in Molecular Dynamics Simulations.

IEEE transactions on visualization and computer graphics·2026

Same author

Reframing Pattern: A Comprehensive Approach to a Composite Visual Variable.

IEEE transactions on visualization and computer graphics·2025

Same author

FEWSim: A Visual Analytic Framework for Exploring the Nexus of Food-Energy-Water Simulations.

IEEE computer graphics and applications·2025

Same author

Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey.

SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining·2025

Same author

Augmented Dynamic Data Physicalization: Blending Shape-Changing Data Sculptures With Virtual Content for Interactive Visualization.

IEEE transactions on visualization and computer graphics·2025

Same author

Understanding Collaborative Learning of Molecular Structures in AR with Eye Tracking.

IEEE computer graphics and applications·2025

Search research articles

Related Experiment Video

Updated: May 9, 2026

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

Bristle Maps: a multivariate abstraction technique for geovisualization.

SungYe Kim¹, Ross Maciejewski, Abish Malik

¹School of Electrical and Computer Engineering, Purdue University, 465 Northwestern Avenue, West Lafayette, IN 47907, USA. inside@purdue.edu

IEEE Transactions on Visualization and Computer Graphics

|July 13, 2013

Summary

Bristle Maps offer a new way to visualize complex spatiotemporal data, enabling multiattribute analysis. This novel technique effectively displays multidimensional information, improving data exploration and understanding.

Related Experiment Videos

Last Updated: May 9, 2026

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

Area of Science:

Geographic Information Science
Data Visualization
Computer Science

Background:

Spatiotemporal data analysis requires effective visualization methods.
Existing techniques often struggle with multidimensional and multiattribute data.
Novel approaches are needed for enhanced data exploration and interpretation.

Purpose of the Study:

To introduce Bristle Maps, a novel method for spatiotemporal data aggregation, abstraction, and stylization.
To enable multiattribute visualization, exploration, and analysis of multidimensional data.
To provide a multiparameter encoding scheme within a single visual paradigm.

Main Methods:

Kernel density estimation to approximate spatiotemporal event data as a continuous function.
Encoding probability values into a bristle map with lines varying in length, density, color, orientation, and transparency.
Application of the bristle map encoding scheme to categorical spatiotemporal police reports.

Main Results:

Bristle Maps effectively display multidimensional data using a multiparameter encoding scheme.
The technique allows for visualization of data magnitude, variable comparisons, and multivariate attribute combinations.
Quantitative and qualitative evaluations show Bristle Maps are competitive with conventional geovisualization techniques in task completion time and accuracy.

Conclusions:

Bristle Maps provide an effective method for visualizing complex spatiotemporal data.
The technique enhances the amount of information displayed in a single plot.
Bristle Maps offer a competitive and versatile approach to geovisualization.