All Topics

FC-31 - Academic origins
  • Identify the key academic disciplines that contributed to the development of GIS&T
  • Evaluate the role that the Quantitative Revolution in geography played in the development of GIS
  • Describe the major research foci in GIS and related fields in the 1970s, 1980s, 1990s, and 2000s
  • Evaluate the importance of the NCGIA and UCGIS in coalescing GIScience as a sub-field of GIS&T
  • Discuss the contributions of early academic centers of GIS&T research and development (e.g., Harvard Laboratory for Computer Graphics, UK Experimental Cartography Unit)
FC-18 - Adjacency and connectivity
  • List different ways connectivity can be determined in a raster and in a polygon dataset
  • Explain the nine-intersection model for spatial relationships
  • Demonstrate how adjacency and connectivity can be recorded in matrices
  • Calculate various measures of adjacency in a polygon dataset
  • Create a matrix describing the pattern of adjacency in a set of planar enforced polygons
  • Describe real world applications where adjacency and connectivity are a critical component of analysis
DC-12 - Aerial photography image interpretation
  • Use photo interpretation keys to interpret features on aerial photographs
  • Calculate the nominal scale of a vertical aerial image
  • Calculate heights and areas of objects and distances between objects shown in a vertical aerial image
  • Produce a map of land use/land cover classes using a vertical aerial image
  • Describe the elements of image interpretation
KE-16 - Agency, organizational, and individual perspectives
  • Describe perspectives on the nature and scope of system benefits among agency officials, organizational personnel, and citizens
  • Discuss implications of unequal economic power on the kinds of organizations that use, and benefit from, GIS&T
AM-79 - Agent-based Modeling

Agent-based models are dynamic simulation models that provide insight into complex geographic systems. Individuals are represented as agents that are encoded with goal-seeking objectives and decision-making behaviors to facilitate their movement through or changes to their surrounding environment. The collection of localized interactions amongst agents and their environment over time leads to emergent system-level spatial patterns. In this sense, agent-based models belong to a class of bottom-up simulation models that focus on how processes unfold over time in ways that produce interesting, and at times surprising, patterns that we observe in the real world.

GS-20 - Aggregation of Spatial Entities and Legislative Redistricting

The partitioning of space is an essential consideration for the efficient allocation of resources. In the United States and many other countries, this parcelization of sub-regions for political and legislative purposes results in what is referred to as districts. A district is an aggregation of smaller, spatially bound units, along with their statistical properties, into larger spatially-bound units. When a district has the primary purpose of representation, individuals who reside within that district make up a constituency. Redistricting is often required as populations of constituents shift over time or resources that service areas change. Administrative challenges with creating districts have been greatly aided by increasing utilization of GIS. However, with these advances in geospatial methods, political disputes with the way in which districts increasingly snare the process in legal battles often centered on the topic of gerrymandering. This chapter focuses on the redistricting process within the United States and how the aggregation of representative spatial entities presents a mix of political, technical and legal challenges.

DC-18 - Algorithms and processing
  • Differentiate supervised classification from unsupervised classification
  • Describe the sequence of tasks involved in the geometric correction of the Advanced Very High Resolution Radiometer (AVHRR) Global Land Dataset
  • Compare pixel-based image classification methods with segmentation techniques
  • Explain how to enhance contrast of reflectance values clustered within a narrow band of wavelengths
  • Describe an application of hyperspectral image data
  • Produce pseudocode for common unsupervised classification algorithms, including chain method, ISODATA method, and clustering
  • Calculate a set of filtered reflectance values for a given array of reflectance values and a digital image filtering algorithm
  • Describe a situation in which filtered data are more useful than the original unfiltered data
  • Perform a manual unsupervised classification given a two-dimensional array of reflectance values and ranges of reflectance values associated with a given number of land cover categories
AM-02 - Analytical approaches
  • Compare and contrast spatial statistical analysis, spatial data analysis, and spatial modeling
  • Compare and contrast the methods of analyzing aggregate data as opposed to methods of analyzing a set of individual observations
  • Define the terms spatial analysis, spatial modeling, geostatistics, spatial econometrics, spatial statistics, qualitative analysis, map algebra, and network analysis
  • Differentiate between geostatistics and spatial statistics
  • Discuss situations when it is desirable to adopt a spatial approach to the analysis of data
  • Explain what is added to spatial analysis to make it spatio-temporal analysis
  • Explain what is special (i.e., difficult) about geospatial data analysis and why some traditional statistical analysis techniques are not suited to geographic problems
  • Outline the sequence of tasks required to complete the analytical process for a given spatial problem
  • Compare and contrast spatial statistics and map algebra as two very different kinds of data analysis
KE-04 - Application user assessment
  • Identify current and potential users of geospatial technology in an enterprise
  • Identify new geographic tasks or information that align with institutional missions and goals
  • Educate potential users on the value of geospatial technology
  • Classify potential users as casual or professional, early adopters or reluctant users
  • Recognize geographic tasks and geographic information that already exist in an enterprise
  • Evaluate the potential for using geospatial technology to improve the efficiency and/or effectiveness of existing activities
  • Differentiate the concepts of efficiency and effectiveness in application requirements
DA-07 - Applications in federal government
  • List and describe the types of data maintained by federal governments
  • Explain how geospatial information might be used in a taking of private property through a government’s claim of its right of eminent domain
  • Describe how geospatial data are used and maintained for land use planning, property value assessment, maintenance of public works, and other applications
  • Explain the concept of a “spatial decision support system”