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CV-35 - Geovisualization

Geovisualization is primarily understood as the process of interactively visualizing geographic information in any of the steps in spatial analyses, even though it can also refer to the visual output (e.g., plots, maps, combinations of these), or the associated techniques. Rooted in cartography, geovisualization emerged as a research thrust with the leadership of Alan MacEachren (Pennsylvania State University) and colleagues when interactive maps and digitally-enabled exploratory data analysis led to a paradigm shift in 1980s and 1990s. A core argument for geovisualization is that visual thinking using maps is integral to the scientific process and hypothesis generation, and the role of maps grew beyond communicating the end results of an analysis or documentation process. As such, geovisualization interacts with a number of disciplines including cartography, visual analytics, information visualization, scientific visualization, statistics, computer science, art-and-design, and cognitive science; borrowing from and contributing to each. In this entry, we provide a definition and a brief history of geovisualization including its fundamental concepts, elaborate on its relationship to other disciplines, and briefly review the skills/tools that are relevant in working with geovisualization environments. We finish the entry with a list of learning objectives, instructional questions, and additional resources.

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-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.

CV-09 - Color Theory

Color is the result of the visual perception of an energy source. It is described by its physical characteristics, mainly as a tridimensional variable modeled into a color space. Online tools exist to facilitate the use of color schemes to design a color palette, for artists, web designers, statisticians, etc. Colors in maps and visualizations must be combined to promote the visual hierarchy and harmony, balancing legibility, perceptual processing, and aesthetics. Color is a powerful visual variable and requires understanding the perception of color relationships. Existing color schemes are very useful to select a suitable color palette. As color is not experienced similarly across all map readers, issues about real-world connotations, conventions, specific color contrasts, and adaptation to color visual deficiencies and devices, are also to be taken into account when designing a color palette. This entry describes the main guidelines regarding color theory and related design practices as applied to map or geovisualization design.

GS-27 - GIS&T for Equity and Social Justice

A geographic information system (GIS) can be used effectively for activities, programs, and analyses focused on equity and social justice (ESJ).  Many types of inequities exist in society, but race and space are key predictors of inequity. A key concept of social justice is that any person born into society, no matter where they were born or live, will have an equitable opportunity to achieve successful life outcomes and to thrive. Geographic information science and its technologies (GIS&T) provide powerful tools to analyze equity and social justice issues and help government agencies apply an equity lens to every aspect of their administration. Given the reliance on spatial data to represent and analyze matters of ESJ, the use of these tools is necessary, logical, and appropriate. Some types of analyses and mapping commonly used with ESJ programs require careful attention to how data are combined and represented, risking misleading or false conclusions otherwise. Such outcomes could build mistrust when trust is most needed. A GIS-supported lifecycle for ESJ is presented that includes stages of exploratory issue analysis, community feedback, pro-equity programs analysis, management monitoring and stakeholder awareness, program performance metrics, and effectiveness analysis.

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-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.

CP-14 - Web GIS

Web GIS allows the sharing of GIS data, maps, and spatial processing across private and public computer networks. Understanding web GIS requires learning the roles of client and server machines and the standards and protocols around how they communicate to accomplish tasks. Cloud computing models have allowed web-based GIS operations to be scaled out to handle large jobs, while also enabling the marketing of services on a per-transaction basis.

A variety of toolkits allow the development of GIS-related websites and mobile apps. Some web GIS implementations bring together map layers and GIS services from multiple locations. In web environments, performance and security are two concerns that require heightened attention. App users expect speed, achievable through caching, indexing, and other techniques. Security precautions are necessary to ensure sensitive data is only revealed to authorized viewers.

Many organizations have embraced the web as a way to openly share spatial data at a relatively low cost. Also, the web-enabled expansion of spatial data production by nonexperts (sometimes known as “neogeography”) offers a rich field for alternative mappings and critical study of GIS and society.

PD-19 - GIS APIs

GIS APIs are collections of library modules that resemble various functionalities of GIS software through programming. GIS APIs evolved from desktop GIS. GIS APIs, as a distributed solution, are interoperable, scalable, light-weight, user-friendly, and versatile to a wide range of GIS users. This entry provides an overview of common GIS APIs, their functionalities as well as other related APIs. The general procedure to develop customized GIS applications is briefly discussed and demonstrated in a case study.

AM-40 - Areal Interpolation

Areal interpolation is the process of transforming spatial data from source zones with known values or attributes to target zones with unknown attributes. It generates estimates of source zone attributes over target zone areas. It aligns areal spatial data attributes over a single spatial framework (target zones) to overcome differences in areal reporting units due to historical boundary changes of reporting areas, integrating data from domains with different reporting conventions or in situations when spatially detailed information is not available. Fundamentally, it requires assumptions about how the target zone attribute relates to the source zones. Areal interpolation approaches can be grouped into two broad categories: methods that link target and source zones by their spatial properties (area to point, pycnophylactic and areal weighed interpolation) and methods that use ancillary or auxiliary information to control, inform, guide, and constrain the interpolation process (dasymetric, statistical, streetweighted and point-based interpolation). Additionally, there are new opportunities to use novel data sources to inform areal interpolation arising from the many new forms of spatial data supported by ubiquitous web- and GPS-enabled technologies including social media, PoI check-ins, spatial data portals (e.g for crime, house sales, microblogging sites) and collaborative mapping activities (e.g. OpenStreetMap).