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CV-42 - Collaborative Cartography

Collaborative cartography is a newly emerging approach for engaging community-centered processes of map production to represent harm caused by oppressive systems and pathways for healed futures. While mapping has a long history of engagement in activist movements, community involvement is often segmented to considerations determining the topic of the map and the subsequent supporting data-collection/validation processes. Collaborative cartography, however, ensures that communities are also central to discussions around and implementation of the design of the map. While the cartographic processes may differ from those of a professional cartographer, the term cartography and cartographer are used (rather than mapping or mapmaker) to indicate the close attention to design this technique facilitates. A collaborative cartographer commits to work that supports community control, embraces multiple forms of knowledge, and engages in non-linear and iterative process. These three key elements work together to support the production of a map whose standards of effectiveness are defined specifically by the needs, desires, and goals of those who produced it. This may lead to the creation of maps that fall outside of traditional expectations of cartographic design, aesthetic, and function. However, such creative ruptures are considered a necessary aspect in the pursuit of community empowerment and liberation.

DA-36 - GIS&T and Public Policy

Public policy is the formal and informal guiding principles that are used by governments and other decision-making entities to guide our everyday lives. Geographic Information Science and Technology (GIS&T) has had an impact on the public policy process since GIS&T’s earliest beginnings in the 1960s. Advances in the development and availability of both geospatial technology and geospatial data paralleled a growing use of data-driven rational planning and decision-making models in policy making at all levels of government. Today more than ever, successful public policy depends on high-quality data and the technology that communicates its meaning effectively. Beyond the rational application of scientific or systematic methods, public policy is about values and how values affect, and are affected by, policies. This requires delivery of credible information in a transparent, understandable form not only to decision makers responsible for adopting policy, but also to various categories of stakeholders whose behavior will be impacted in some way by the policy’s implementation. GIS&T continues to play an important role in that endeavor, including making value conflicts more seeable and knowable. Included in the entry is a summary of the public policy process and its participants, followed by a brief overview of how GIST’s role in public policy has evolved over the last 50 years. The entry concludes by outlining a sample of real-world applications and presenting a discussion of related issues and future considerations.

AM-106 - Error-based Uncertainty

The largest contributing factor to spatial data uncertainty is error. Error is defined as the departure of a measure from its true value. Uncertainty results from: (1) a lack of knowledge of the extent and of the expression of errors and  (2) their propagation through analyses. Understanding error and its sources is key to addressing error-based uncertainty in geospatial practice. This entry presents a sample of issues related to error and error based uncertainty in spatial data. These consist of (1) types of error in spatial data, (2) the special case of scale and its relationship to error and (3) approaches to quantifying error in spatial data.

FC-32 - Semantic Information Elicitation

The past few decades have been characterized by an exponential growth of digital information resources. A considerable amount of this information is semi-structured, such as XML files and metadata records and unstructured, such as scientific reports, news articles, and historical archives. These resources include a wealth of latent knowledge in a form mainly intended for human use. Semantic information elicitation refers to a set of related processes: semantic information extraction, linking, and annotation that aim to make this knowledge explicit to help computer systems make sense of the content and support ontology construction, information organization, and knowledge discovery.

In the context of GIScience research, semantic information extraction aims at processing unstructured and semi-structured resources and identifying specific types of information: places, events, topics, geospatial concepts, and relations. These may be further linked to ontologies and knowledge bases to enrich the original unstructured content with well-defined meaning, provide access to information not explicit in the original sources, and support semantic annotation and search. Semantic analysis and visualization techniques are further employed to explore aspects latent in these sources such as the historical evolution of cities, the progression of phenomena and events and people’s perception of places and landscapes.

DC-39 - Time-of-Arrival (TOA) Localization for Indoor GIS

Indoor geographic information system (GIS) opens up a new frontier for identifying, analyzing and solving complex problems. In many indoor GIS-driven applications such as indoor wayfinding and logistics planning and management, determination of location information deserves special attention because global positioning system (GPS) may be inaccessible. Alternative methods and systems have emerged to overcome this hurdle. The time-of-arrival (TOA) measurement is one of the most adopted metrics in numerous modern systems such as radar, acoustic/ultra-sound-based tracking, ultra-wide band (UWB) indoor localization, wireless sensor networks (WSN) and Internet of things (IoT) localization. This topic presents the TOA technique and methods to solve the localization and synchronization problem. We also introduce variants of the TOA system schemes, which are adopted by real-world applications. As a use case of the TOA technique realized in practice, a UWB localization system is introduced. Examples are given to demonstrate that indoor localization and GIS are tightly interconnected.

GS-25 - Spatial Decision Support

It has been estimated that 80% of all datasets include geographic references. Since these data often factor into preparing important decisions, we can assume that a significant proportion of all decisions have a geospatial aspect to them. Therefore, spatial decision support is an intrinsic component of societal decision-making. It is thus necessary for current and aspiring analysts, and for decision-makers and other stakeholders, to understand the fundamental concepts, techniques, and challenges of spatial decision support. This GIS&T topic explores the unique nature and basic concepts of spatial decision support, discusses the relationship between Spatial Decision Support Systems (SDSS) and Geographic Information Systems (GIS), and briefly introduces Multi-Criteria Decision Analysis (MCDA) as a decision support technique. The impact of Web-based and mobile information technology, ever-increasing accessibility of geospatial data, and participatory approaches to decision-making are touched upon and additional resources for further reading provided.

DM-87 - Raster resampling
  • Evaluate methods used by contemporary GIS software to resample raster data on-the-fly during display
  • Select appropriate interpolation techniques to resample particular types of values in raster data (e.g., nominal using nearest neighbor)
  • Resample multiple raster data sets to a single resolution to enable overlay
  • Resample raster data sets (e.g., terrain, satellite imagery) to a resolution appropriate for a map of a particular scale
  • Discuss the consequences of increasing and decreasing resolution
DM-88 - Coordinate transformations
  • Cite appropriate applications of several coordinate transformation techniques (e.g., affine, similarity, Molodenski, Helmert)
  • Describe the impact of map projection transformation on raster and vector data
  • Differentiate between polynomial coordinate transformations (including linear) and rubbersheeting