2018 QUARTER 02

KE-01 - The process of GIS&T design
  • Describe the major approaches to the design of geospatial systems
  • Analyze past cases to identify best practices of design and implementation
  • Compare and contrast the relative merits of the use-case driven and architecture-centric design processes
DM-07 - The Raster Data Model

The raster data model is a widely used method of storing geographic data. The model most commonly takes the form of a grid-like structure that holds values at regularly spaced intervals over the extent of the raster. Rasters are especially well suited for storing continuous data such as temperature and elevation values, but can hold discrete and categorical data such as land use as well.  The resolution of a raster is given in linear units (e.g., meters) or angular units (e.g., one arc second) and defines the extent along one side of the grid cell. High (or fine) resolution rasters have comparatively closer spacing and more grid cells than low (or coarse) resolution rasters, and require relatively more memory to store. Active research in the domain is oriented toward improving compression schemes and implementation for alternative cell shapes (such as hexagons), and better supporting multi-resolution raster storage and analysis functions.

DA-04 - The scope of GIS&T applications
  • Differentiate between project-specific applications and enterprise systems
  • Differentiate between applications for scientific research and resource management decision support
  • Identify tasks that are structured, semi-structured, and unstructured
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
AM-21 - The spatial weights matrix
  • Explain how different types of spatial weights matrices are defined and calculated
  • Discuss the appropriateness of different types of spatial weights matrices for various problems
  • Construct a spatial weights matrix for lattice, point, and area patterns
  • Explain the rationale used for each type of spatial weights matrix
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
  • Differentiate between mathematical and phenomenological theories of the nature of time
  • Recognize the role that time plays in “static” GISystems
  • Compare and contrast models of a given spatial process using continuous and discrete perspectives of time
  • Select the temporal elements of geographic phenomena that need to be represented in particular GIS applications
  • Exemplify different temporal frames of reference: linear and cyclical, absolute and relative