Cartography and Visualization

The Cartography & Visualization section encapsulates competencies related to the design and use of maps and mapping technology. This section covers core topics of reference and thematic maps design, as well as the emerging topics of interaction design, web map design, and mobile map design. This section also covers historical and contemporary influences on cartography and evolving data and critical considerations for map design and use.  

Topics in this Knowledge Area are listed thematically below. Existing topics are in regular font and linked directly to their original entries (published in 2006; these contain only Learning Objectives). Entries that have been updated and expanded are in bold. Forthcoming, future topics are italicized

History & Trends Map Design Techniques Interactive Design Techniques
Cartography & Science Common Thematic Maps User Interface and User Experience (UI/UX) Design
Cartography & Art Multivariate Mapping Web Mapping
Cartography & Power Spatio-Temporal Representation Virtual & Immersive Environments
  Representing Uncertainty Big Data Visualization
  Terrain Representation Mobile Maps & Responsive Design
Data Considerations Cartograms Usability Engineering & Evaluation
Vector Formats & Sources Map Icon Design Geovisual Analytics
Raster Formats & Sources Narrative & Storytelling Geovisualization
  Flow Maps  
Map Design Fundamentals  Participatory Cartography  
Scale & Generalization Map Use  
Statistical Mapping (Enumeration, Normalization, Classification) Lesson Design in Cartography Education  
Map Projections Map Reading  
Visual Hierarchy & Layout Map Interpretation  
Symbolization & the Visual Variables Map Analysis  
Color Theory    
Design and Aesthetics    
Map Production and Management    


CV-40 - Mobile Maps and Responsive Design

Geographic information increasingly is produced and consumed on mobile devices. The rise of mobile mapping is challenging traditional design conventions in research, industry, and education, and cartographers and GIScientists now need to accommodate this mobile context. This entry introduces emerging design considerations for mobile maps. First, the technical enablements and constraints that make mobile devices unique are described, including Global Positioning System (GPS) receivers and other sensors, reduced screensize and resolution, reduced processing power and memory capacity, less reliable data connectivity, reduced bandwidth, and physical mobility through variable environmental conditions. Scholarly influences on mobile mapping also are reviewed, including location-based services, adaptive cartography, volunteered geographic information, and locational privacy. Next, two strategies for creating mobile maps are introduced—mobile apps installed onto mobile operating systems versus responsive web maps that work on mobile and nonmobile devices—and core concepts of responsive web design are reviewed, including fluid grids, media queries, breakpoints, and frameworks. Finally, emerging design recommendations for mobile maps are summarized, with representation design adaptations needed to account for reduced screensizes and bandwidth and interaction design adaptations needed to account for multi-touch interaction and post-WIMP interfaces.

CV-12 - Multivariate Mapping

Bivariate and multivariate maps encode two or more data variables concurrently into a single symbolization mechanism. Their purpose is to reveal and communicate relationships between the variables that might not otherwise be apparent via a standard single-variable technique. These maps are inherently more complex, though offer a novel means of visualizing the nuances that may exist between the mapped variables. As information-dense visual products, they can require considerable effort on behalf of the map reader, though a thoughtfully-designed map and legend can be an interesting opportunity to effectively convey a comparative dimension.

This chapter describes some of the key types of bivariate and multivariate maps, walks through some of the rationale for various techniques, and encourages the reader to take an informed, balanced approach to map design weighing information density and visual complexity. Some alternatives to bivariate and multivariate mapping are provided, and their relative merits are discussed.

CV-20 - Raster Formats and Sources

Raster data is commonly used by cartographers in concert with vector data. Choice of raster file format is important when using raster data or producing raster output from vector data. Raster formats are designed for specific purposes and have limitations in color representation and data loss. The simplest raster formats are just a single two-dimensional array of pixels, where multi-band raster datasets use additional data values to represent color or other data. The article covers considerations for the intended use of raster formats. Formats and resolutions appropriate for the web may not be appropriate for print or higher resolution devices. Several types of raster sources are available including single band measures, imagery, and existing raster maps or basemaps. The future of raster will evolve as more formats, sources, and computational improvements are made.

CV-18 - Representing Uncertainty

Using geospatial data involves numerous uncertainties stemming from various sources such as inaccurate or erroneous measurements, inherent ambiguity of the described phenomena, or subjectivity of human interpretation. If the uncertain nature of the data is not represented, ill-informed interpretations and decisions can be the consequence. Accordingly, there has been significant research activity describing and visualizing uncertainty in data rather than ignoring it. Multiple typologies have been proposed to identify and quantify relevant types of uncertainty and a multitude of techniques to visualize uncertainty have been developed. However, the use of such techniques in practice is still rare because standardized methods and guidelines are few and largely untested. This contribution provides an introduction to the conceptualization and representation of uncertainty in geospatial data, focusing on strategies for the selection of suitable representation and visualization techniques.

CV-04 - Scale and Generalization

Scale and generalization are two fundamental, related concepts in geospatial data. Scale has multiple meanings depending on context, both within geographic information science and in other disciplines. Typically it refers to relative proportions between objects in the real world and their representations. Generalization is the act of modifying detail, usually reducing it, in geospatial data. It is often driven by a need to represent data at coarsened resolution, being typically a consequence of reducing representation scale. Multiple computations and graphical modication processes can be used to achieve generalization, each introducing increased abstraction to the data, its symbolization, or both.

CV-17 - Spatiotemporal Representation

Space and time are integral components of geographic information. There are many ways in which to conceptualize space and time in the geographic realm that stem from time geography research in the 1960s. Cartographers and geovisualization experts alike have grappled with how to represent spatiotemporal data visually. Four broad types of mapping techniques allow for a variety of representations of spatiotemporal data: (1) single static maps, (2) multiple static maps, (3) single dynamic maps, and (4) multiple dynamic maps. The advantages and limitations of these static and dynamic methods are discussed in this entry. For cartographers, identifying the audience and purpose, medium, available data, and available time to design the map are vital aspects to deciding between the different spatiotemporal mapping techniques. However, each of these different mapping techniques offers its own advantages and disadvantages to the cartographer and the map reader. This entry focuses on the mapping of time and spatiotemporal data, the types of time, current methods of mapping, and the advantages and limitations of representing spatiotemporal data.

CV-05 - Statistical Mapping (Enumeration, Normalization, Classification)

Proper communication of spatial distributions, trends, and patterns in data is an important component of a cartographers work. Geospatial data is often large and complex, and due to inherent limitations of size, scalability, and sensitivity, cartographers are often required to work with data that is abstracted, aggregated, or simplified from its original form. Working with data in this manner serves to clarify cartographic messages, expedite design decisions, and assist in developing narratives, but it also introduces a degree of abstraction and subjectivity in the map that can make it easy to infer false messages from the data and ultimately can mislead map readers. This entry introduces the core topics of statistical mapping around cartography. First, we define enumeration and the aggregation of data to units of enumeration. Next, we introduce the importance of data normalization (or standardization) to more truthfully communicate cartographically and, lastly, discuss common methods of data classification and how cartographers bin data into groups that simplify communication.

CV-08 - Symbolization and the Visual Variables

Maps communicate information about the world by using symbols to represent specific ideas or concepts. The relationship between a map symbol and the information that symbol represents must be clear and easily interpreted. The symbol design process requires first an understanding of the underlying nature of the data to be mapped (e.g., its spatial dimensions and level of measurement), then the selection of symbols that suggest those data attributes. Cartographers developed the visual variable system, a graphic vocabulary, to express these relationships on maps. Map readers respond to the visual variable system in predictable ways, enabling mapmakers to design map symbols for most types of information with a high degree of reliability.

CV-14 - Terrain Representation

Terrain representation is the manner by which elevation data are visualized. Data are typically stored as 2.5D grid representations, including digital elevation models (DEMs) in raster format and triangulated irregular networks (TINs). These models facilitate terrain representations such as contours, shaded relief, spot heights, and hypsometric tints, as well as automate calculations of surface derivatives such as slope, aspect, and curvature. 3D effects have viewing directions perpendicular (plan), parallel (profile), or panoramic (oblique view) to the elevation’s vertical datum plane. Recent research has focused on automating, stylizing, and enhancing terrain representations. From the user’s perspective, representations of elevation are measurable or provide a 3D visual effect, with much overlap between the two. The ones a user can measure or derive include contours, hypsometric tinting, slope, aspect, and curvature. Other representations focus on 3D effect and may include aesthetic considerations, such as hachures, relief shading, physiographic maps, block diagrams, rock drawings, and scree patterns. Relief shading creates the 3D effect using the surface normal and illumination vectors with the Lambertian assumption. Non-plan profile or panoramic views are often enhanced by vertical exaggeration. Cartographers combine techniques to mimic or create mapping styles, such as the Swiss-style.

CV-10 - Typography

The selection of appropriate type on maps, far from an arbitrary design decision, is an integral part of establishing the content and tone of the map. Typefaces have personalities, which contribute to the rhetorical message of the map. It is important to understand how to assess typefaces for their personalities, but also to understand which typefaces may be more or less legible in a labeling context. Beyond the choice of typeface, effective map labels will have a visual hierarchy and allow the user to easily associate labels to their features and feature types. The cartographer must understand and modify typographic visual variables to support both the hierarchy and label-feature associations.