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CV-16 - Virtual and Immersive Environments

A virtual environment (VE) is a 3D computer-based simulation of a real or imagined environment in which users can navigate and interactive with virtual objects. VEs have found popular use in communicating geographic information for a variety of domain applications. This entry begins with a brief history of virtual and immersive environments and an introduction to a common framework used to describe characteristics of VEs. Four design considerations for VEs then are reviewed: cognitive, methodological, social, and technological. The cognitive dimension involves generating a strong sense of presence for users in a VE, enabling users to perceive and study represented data in both virtual and real environments. The methodological dimension covers methods in collecting, processing, and visualizing data for VEs. The technological dimension surveys different VE hardware devices (input, computing, and output devices) and software tools (desktop and web technologies). Finally, the social dimension captures existing use cases for VEs in geo-related fields, such as geography education, spatial decision support, and crisis management.

CV-36 - Geovisual Analytics

Geovisual analytics refers to the science of analytical reasoning with spatial information as facilitated by interactive visual interfaces. It is distinguished by its focus on novel approaches to analysis rather than novel approaches to visualization or computational methods alone. As a result, geovisual analytics is usually grounded in real-world problem solving contexts. Research in geovisual analytics may focus on the development of new computational approaches to identify or predict patterns, new visual interfaces to geographic data, or new insights into the cognitive and perceptual processes that users apply to solve complex analytical problems. Systems for geovisual analytics typically feature a high-degree of user-driven interactivity and multiple visual representation types for spatial data. Geovisual analytics tools have been developed for a variety of problem scenarios, such as crisis management and disease epidemiology. Looking ahead, the emergence of new spatial data sources and display formats is expected to spur an expanding set of research and application needs for the foreseeable future. 

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-19 - Big Data Visualization

As new information and communication technologies have altered so many aspects of our daily lives over the past decades, they have simultaneously stimulated a shift in the types of data that we collect, produce, and analyze. Together, this changing data landscape is often referred to as "big data." Big data is distinguished from "small data" not only by its high volume but also by the velocity, variety, exhaustivity, resolution, relationality, and flexibility of the datasets. This entry discusses the visualization of big spatial datasets. As many such datasets contain geographic attributes or are situated and produced within geographic space, cartography takes on a pivotal role in big data visualization. Visualization of big data is frequently and effectively used to communicate and present information, but it is in making sense of big data – generating new insights and knowledge – that visualization is becoming an indispensable tool, making cartography vital to understanding geographic big data. Although visualization of big data presents several challenges, human experts can use visualization in general, and cartography in particular, aided by interfaces and software designed for this purpose, to effectively explore and analyze big data.

CV-23 - Map analysis
  • Create a profile of a cross section through a terrain using a topographic map and a digital elevation model (DEM)
  • Measure point-feature movement and point-feature diffusion on maps
  • Describe maps that can be used to find direction, distance, or position, plan routes, calculate area or volume, or describe shape
  • Explain how maps can be used in determining an optimal route or facility selection
  • Explain how maps can be used in terrain analysis (e.g., elevation determination, surface profiles, slope, viewsheds, and gradient)
  • Explain how the types of distortion indicated by projection metadata on a map will affect map measurements
  • Explain the differences between true north, magnetic north, and grid north directional references
  • Compare and contrast the manual measurement of the areas of polygons on a map printed from a GIS with those calculated by the computer and discuss the implications these variations in measurement might have on map use
  • Determine feature counts of point, line, and area features on maps
  • Analyze spatial patterns of selected point, line, and area feature arrangements on maps
  • Calculate slope using a topographic map and a DEM
  • Calculate the planimetric and actual road distances between two locations on a topographic map
  • Plan an orienteering tour of a specific length that traverses slopes of an appropriate steepness and crosses streams in places that can be forded based on a topographic map
  • Describe the differences between azimuths, bearings, and other systems for indicating directions
CV-24 - User-Centered Design and Evaluation
  • Describe the baseline expectations that a particular map makes of its audience
  • Compare and contrast the interpretive dangers (e.g., ecological fallacy, Modifiable Areal Unit Problem) that are inherent to different types of maps or visualizations and their underlying geographic data
  • Identify several uses for which a particular map is or is not effective
  • Identify the particular design choices that make a map more or less effective
  • Evaluate the effectiveness of a map for its audience and purpose
  • Design a testing protocol to evaluate the usability of a simple graphical user interface
  • Perform a rigorous sampled field check of the accuracy of a map
  • Discuss the use limitations of the USGS map accuracy standards for a range of projects demanding different levels of precision (e.g., driving directions vs. excavation planning)
CV-25 - Metadata, Quality, and Uncertainty
  • Describe a scenario in which possible errors in a map may impact subsequent decision making, such as a land use decision based on a soils map
  • Evaluate the uncertainty inherent in a map
  • Compare the decisions made using a map with a reliability overlay from those made using a map pair separating data and reliability, both drawn from the same dataset
  • Critique the assumption that maps can or should be “accurate”
CV-02 - Cartography and Technology
  • Discuss the impact that mapping on the Web via applications such as Google Earth have had on the practice of cartography
  • Explain how emerging technologies in related fields (e.g., the stereoplotter, aerial and satellite imagery, GPS and LiDAR, the World Wide Web, immersive and virtual environments) have advanced cartography and visualization methods
  • Explain how MacEachren’s Cartography-cubed (C3) concept can be used to understand the evolving role of cartography and visualization
  • Explain how software innovations such as Synagraphic Mapping System (SYMAP), Surfer, and automated contouring methods have affected the design of maps
  • Evaluate the advantages and limitations of various technological approaches to mapping
  • Select new technologies in related fields that have the most potential for use in cartography and visualization
CV-22 - Map interpretation
  • Identify the landforms represented by specific patterns in contours on a topographic map
  • Hypothesize about geographic processes by synthesizing the patterns found on one or more thematic maps or data visualizations
  • Match features on a map to corresponding features in the world
  • Compare and contrast the interpretation of landscape, geomorphic features, and human settlement types shown on a series of topographic maps from several different countries

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