2016 QUARTER 02

A B C D E F G H I K L M N O P R S T U V W
CF6-1 - Vagueness
  • Compare and contrast the meanings of related terms such as vague, fuzzy, imprecise, indefinite, indiscrete, unclear, and ambiguous
  • Describe the cognitive processes that tend to create vagueness
  • Recognize the degree to which vagueness depends on scale
  • Evaluate vagueness in the locations, time, attributes, and other aspects of geographic phenomena
  • Differentiate between the following concepts: vagueness and ambiguity, well defined and poorly defined objects and fields, and discord and non-specificity
  • Identify the hedges used in language to convey vagueness
  • Evaluate the role that system complexity, dynamic processes, and subjectivity play in the creation of vague phenomena and concepts
  • Differentiate applications in which vagueness is an acceptable trait from those in which it is unacceptable
GS2-2 - Valuing and measuring benefits
  • Distinguish between operational, organizational, and societal activities that rely upon geospatial information
  • Describe the potential benefits of geospatial information in terms of efficiency, effectiveness, and equity
  • Explain how cost-benefit analyses can be manipulated
  • Compare and contrast the evaluation of benefits at different scales (e.g., national, regional/state, local)
  • Identify practical problems in defining and measuring the value of geospatial information in land or other business decisions
GD10-5 - Vector data extraction
  • Describe the source data, instrumentation, and workflow involved in extracting vector data (features and elevations) from analog and digital stereoimagery
  • Discuss future prospects for automated feature extraction from aerial imagery
  • Discuss the extent to which vector data extraction from aerial stereoimagery has been automated
DN1-4 - Vector-to-raster and raster-to-vector conversions
  • Explain how the vector/raster/vector conversion process of graphic images and algorithms takes place and how the results are achieved
  • Create estimated tessellated data sets from point samples or isolines using interpolation operations that are appropriate to the specific situation
  • Illustrate the impact of vector/raster/vector conversions on the quality of a dataset
  • Convert vector data to raster format and back using GIS software
GD4-2 - Vertical datums
  • Explain how a vertical datum is established
  • Differentiate between NAVD 29 and NAVD 88
  • Illustrate the difference between a vertical datum and a geoid
  • Illustrate the relationship among the concepts ellipsoidal (or geodetic) height, geoidal height, and orthometric elevation
  • Outline the historical development of vertical datums
CV4-6 - Virtual and immersive environments
  • Discuss the nature and use of virtual environments, such as Google Earth
  • Explain how various data formats and software and hardware environments support immersive visualization
  • Compare and contrast the relative advantages of different immersive display systems used for cartographic visualization (e.g., CAVEs, GeoWalls)
  • Evaluate the extent to which a GeoWall or CAVE does or does not enhance understanding of spatial data
  • Explain how the virtual and immersive environments become increasingly more complex as we move from the relatively non-immersive VRML desktop environment to a stereoscopic display (e.g., a GeoWall) to a more fully immersive CAVE
CV4-8 - Visualization of temporal geographic data
  • Describe how the adding time-series data reveals or does not reveal patterns not evident in a cross-sectional data
  • Describe how an animated map reveals patterns not evident without animation
  • Demonstrate how Bertin’s “graphic variables” can be extended to include animation effects
  • Create a temporal sequence representing a dynamic geospatial process
CV4-9 - Visualization of uncertainty
  • Describe a technique that can be used to represent the value of each of the components of data quality (positional and attribute accuracy, logical consistency, and completeness)
  • Apply multivariate and dynamic visualization methods to display uncertainty in data
  • Sketch a map with a reliability overlay using symbols suited to reliability representations
  • Develop graphic techniques that clearly show different forms of inexactness (e.g., existence uncertainty, boundary location uncertainty, attribute ambiguity, transitional boundary) of a given feature (e.g., a culture region)