All Topics

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 Map Types 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  Collaborative 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    
Typography    
Design and Aesthetics    
Map Production and Management    

 

B C D F G L M N R S T U V W
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.