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FC-04 - Perception and Cognitive Processing of Geographic Phenomena: a Choropleth Map Case Study

The near ubiquity of maps has created a population the is well adept at reading and understanding maps.  But, while maps are familiar, understanding how the human brain processes that information is less known.  Discussing the processing of geographic phenomena could take different avenues: specific geospatial thinking skills, general perception and cognition processes, or even different parts of the human brain that are invoked when thinking geographically.  This entry focuses on tracing the processing of geographic phenomena using a choropleth map case study, beginning from perception — the moment the phenomena enter the human brain via our senses, to cognition — how meaning and understanding are generated. 

FC-17 - Proximity and Distance Decay

Distance decay is an essential concept in geography. At its core, distance decay describes how the relationship between two entities generally gets weaker as the separation between them increases. Inspired by long-standing ideas in physics, the concept of distance decay is used by geographers to analyze two kinds of relationships. First, the term expresses how measured interactions (such as trade volume or migration flow) generally decrease as the separation between entities increases, as is analyzed by spatial interaction models. Second, the term is used to describe how the implicit similarity between observations changes with separation, as measured by variograms. For either type of relationship, we discuss how "separation" must be clearly articulated according to the mechanism of the relationship under study. In doing this, we suggest that separation need not refer to positions in space or time, but can involve social or behavioral perceptions of separation, too. To close, we present how the "death of distance" is transforming distance decay in uneven ways.

FC-22 - Geometric Primitives and Algorithms

Geometric primitives are the representations used and computations performed in a GIS that concern the spatial aspects of the data, data objects described by coordinates. In vector geometry, we distinguish in zero-, one-, two-, and three-dimensional objects, better known as points, linear features, areal or planar features, and volumetric features. A GIS stores and performs computations on all of these. Often, planar features form a collective known as a (spatial) subdivision. Computations on geometric objects show up in data simplification, neighborhood analysis, spatial clustering, spatial interpolation, automated text placement, segmentation of trajectories, map matching, and many other tasks. They should be contrasted with computations on attributes or networks.

There are various kinds of vector data models for subdivisions. The classical ones are known as spaghetti and pizza models, but nowadays it is recognized that topological data models are the representation of choice. We overview these models briefly.

Computations range from simple to highly complex: deciding whether a point lies in a rectangle needs four comparisons, whereas performing map overlay on two subdivisions requires advanced knowledge of algorithm design. We introduce map overlay, Voronoi diagrams, and Delaunay triangulations and mention algorithmic approaches to compute them.

FC-19 - Networks

A network is a widely used term with different definitions and methodologies depending on the applications. In GIS, a network refers to an arrangement of elements (i.e., nodes, links) and information on their connections and interactions. There are two types of networks: physical and logical. While a physical network has tangible objects (e.g., road segments), a logical network represents logical connections among nodes and links. A network can be represented with a mathematical notion called graph theory. Different network components are utilized to describe characteristics of a network including loops, walks, paths, circuits, and parallel edges. Network data are commonly organized in a vector format with network topology, specifically connectivity among nodes and links, whereas raster data can be also utilized for a least-cost problem over continuous space. Network data is utilized in a wide range of network analyses, including the classic shortest path problem.

FC-29 - Public and Private Sector Origins
  • Identify some of the key federal agencies and programs that provided the impetus for the development of GIS&T
  • Explain how the federalization of land management in Canada led to the development of the Canadian Geographic Information System in the 1960s
  • Discuss the role of the U.S. Census Bureau in contributing to the development of the U.S. geospatial industry
  • Discuss the role of the U.S. Geological Survey in contributing to the development of the U.S. geospatial industry
  • Describe the mechanical and computerized technologies used by civilian and military mapping agencies between World War II and the advent of GIS
  • Trace the history of the relationship between the intelligence community and the geospatial industry
  • Compare and contrast the initiatives of various countries to move their national mapping activities to geospatial data
  • Describe the role of NASA and the Landsat program in promoting development of digital image processing and raster GIS systems
  • Identify some of the key commercial activities that provided an impetus for the development of GIS&T
  • Differentiate the dominant industries using geospatial technologies during the 1980s, 1990s, and 2000s
  • Describe the contributions of McHarg and other practitioners in developing geographic analysis methods later incorporated into GIS
  • Evaluate the correspondence between advances in hardware and operating system technology and changes in GIS software
  • Describe the influence of evolving computer hardware and of private sector hardware firms such as IBM on the emerging GIS software industry
  • Discuss the emergence of the GIS software industry in terms of technology evolution and markets served by firms such as ESRI, Intergraph, and ERDAS