2019 QUARTER 04

A B C D E F G H I K L M N O P R S T U V W
DM-12 - The spaghetti model
  • Identify a widely-used example of the spaghetti model (e.g., AutoCAD DWF, ESRI shapefile)
  • Write a program to read and write a vector data file using a common published format
  • Explain the conditions under which the spaghetti model is useful
  • Explain how the spaghetti data model embodies an object-based view of the world
  • Describe how geometric primitives are implemented in the spaghetti model as independent objects without topology
DM-13 - The topological model
  • Define terms related to topology (e.g., adjacency, connectivity, overlap, intersect, logical consistency)
  • Describe the integrity constraints of integrated topological models (e.g., POLYVRT)
  • Discuss the historical roots of the Census Bureau’s creation of GBF/DIME as the foundation for the development of topological data structures
  • Explain why integrated topological models have lost favor in commercial GIS software
  • Evaluate the positive and negative impacts of the shift from integrated topological models
  • Discuss the role of graph theory in topological structures
  • Exemplify the concept of planar enforcement (e.g., TIN triangles)
  • Demonstrate how a topological structure can be represented in a relational database structure
  • Explain the advantages and disadvantages of topological data models
  • Illustrate a topological relation
DM-10 - The Triangulated Irregular Network (TIN) model
  • Describe how to generate a unique TIN solution using Delaunay triangulation
  • Describe the architecture of the TIN model
  • Construct a TIN manually from a set of spot elevations
  • Delineate a set of break lines that improve the accuracy of a TIN
  • Describe the conditions under which a TIN might be more practical than GRID
  • Demonstrate the use of the TIN model for different statistical surfaces (e.g., terrain elevation, population density, disease incidence) in a GIS software application
FC-27 - Thematic accuracy
  • Explain the distinction between thematic accuracy, geometric accuracy, and topological fidelity
  • Outline the SDTS and ISO TC211 standards for thematic accuracy
  • Discuss how measures of spatial autocorrelation may be used to evaluate thematic accuracy
  • Describe the component measures and the utility of a misclassification matrix
  • Describe the different measurement levels on which thematic accuracy is based
AM-86 - Theory of error propagation
  • Describe stochastic error models
  • Exemplify stochastic error models used in GIScience
FC-08 - Time

Time is a fundamental concept in geography and many other disciplines. This article introduces time at three levels. At the philosophical level, the article reviews various notions on the nature of time from early mythology to modern science and reveals the dual nature of reality: external (absolute, physical) and internal (perceived, cognitive). At the analytical level, it introduces the measurement of time, the two frames of temporal reference: calendar time and clock time, and the standard time for use globally. The article continues to discuss time in GIS at the practical level. The GISystem was first created as a “static” computer-based system that stores the present status of a dynamic system. Now, GISystems can track and model the dynamics in geographical phenomena and human-environment interactions. Representations of time in dynamic GISystems adopt three perspectives: discrete time, continuous time and Minkowski’s spacetime, and three representations: ordinal, interval, and cyclical. The appropriate perspective and representation depend on the observed temporal patterns, which can be static, oscillating, chaotic, or stochastic. Recent progress in digital technology brings us opportunities and challenges to collect, manage and analyze spatio-temporal data to advance our understanding of dynamical phenomena.

DM-28 - Topological relationships
  • Define various terms used to describe topological relationships, such as disjoint, overlap, within, and intersect
  • List the possible topological relationships between entities in space (e.g., 9-intersection) and time
  • Use methods that analyze topological relationships
  • Recognize the contributions of topology (the branch of mathematics) to the study of geographic relationships
  • Describe geographic phenomena in terms of their topological relationships in space and time to other phenomena
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.

DC-28 - United States Census Data

The Census Bureau collects extensive numeric data on the residents of the United States as well ast the national economy.  This is accomplished both through a decennial census as well as numerous other more frequent surveys. The decennial census is a fundamental basis of American democracy, mandated by the U.S. Constitution and essential for the equal representation in a democratic government. Numeric census data are maintained in vast collections of tables and organized at many different levels of geographies. From the Census website, the geographic and tabular data can be downloaded and then joined for display and analysis within a GIS. Because of the nature of individual data aggregated over areas and other matters, care must be taken to avoid statistical errors when undertaking spatial analyses.

DC-24 - Unmanned Aerial Systems (UAS)

Unmanned Aerial Systems (UAS) are revolutionizing how GIS&T researchers and practitioners model and analyze our world. Compared to traditional remote sensing approaches, UAS provide a largely inexpensive, flexible, and relatively easy-to-use platform to capture high spatial and temporal resolution geospatial data. Developments in computer vision, specifically Structure from Motion (SfM), enable processing of UAS-captured aerial images to produce three-dimensional point clouds and orthophotos. However, many challenges persist, including restrictive legal environments for UAS flight, extensive data processing times, and the need for further basic research. Despite its transformative potential, UAS adoption still faces some societal hesitance due to privacy concerns and liability issues.

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