All Topics

A B C D E F G H I K L M N O P R S T U V W
AM-61 - Coordinate transformations
  • Cite appropriate applications of several coordinate transformation techniques (e.g., affine, similarity, Molodenski, Helmert)
  • Describe the impact of map projection transformation on raster and vector data
  • Differentiate between polynomial coordinate transformations (including linear) and rubbersheeting
AM-18 - Cost surface
  • Define “friction surface”
  • Apply the principles of friction surfaces in the calculation of least-cost paths
  • Explain how friction surfaces are enhanced by the use of impedance and barriers
AM-54 - Coupling scientific models with GIS
  • Discuss the current state-of-the-art of the coupling of scientific models and simulations with GIS
  • Design a modeling procedure to integrate a spatial arrangement constraint for a mathematical optimization model
GS-18 - Cultural influences
  • Collaborate effectively with colleagues of differing social backgrounds in developing balanced GIS applications
  • Describe the ways in which the elements of culture (e.g., language, religion, education, traditions) may influence the understanding and use of geographic information
  • Recognize the impact of one’s social background on one’s own geographic worldview and perceptions and how it influences one’s use of GIS
AM-57 - Data conversion
  • Identify the conceptual and practical difficulties associated with data model and format conversion
  • Convert a data set from the native format of one GIS product to another
  • Discuss the role of metadata in facilitating conversation of data models and data structures between systems
  • Describe a workflow for converting and implementing a data model in a GIS involving an Entity-Relationship (E-R) diagram and the Universal Modeling Language (UML)
KE-08 - Data costs
  • Identify potential sources of data (free or commercial) needed for a particular application or enterprise
  • Judge the relative merits of obtaining free data, purchasing data, outsourcing data creation, or producing and managing data in-house for a particular application or enterprise
  • Estimate the cost to collect needed data from primary sources (e.g., remote sensing, GPS)
AM-36 - Data mining approaches
  • Describe how data mining can be used for geospatial intelligence
  • Explain how the analytical reasoning techniques, visual representations, and interaction techniques that make up the domain of visual analytics have a strong spatial component
  • Demonstrate how cluster analysis can be used as a data mining tool
  • Interpret patterns in space and time using Dorling and Openshaw’s geographical analysis machine (GAM) demonstration of disease incidence diffusion
  • Differentiate between data mining approaches used for spatial and non-spatial applications
  • Explain how spatial statistics techniques are used in spatial data mining
  • Compare and contrast the primary types of data mining: summarization/characterization, clustering/categorization, feature extraction, and rule/relationships extraction
DM-02 - Data retrieval strategies
  • Analyze the relative performance of data retrieval strategies
  • Implement algorithms that retrieve geospatial data from a range of data structures
  • Describe the particular advantages of Morton addressing relative to geographic data representation
  • Discuss the advantages and disadvantages of different data structures (e.g., arrays, linked lists, binary trees, hash tables, indexes) for retrieving geospatial data
  • Compare and contrast direct and indirect access search and retrieval methods
KE-18 - Data sharing among public and private agencies, organizations, and individuals
  • Describe formal and informal arrangements that promote geospatial data sharing (e.g., FGDC, ESDI, memoranda of agreements, informal access arrangements, targeted funding support)
  • Describe a situation in which politics interferes with data sharing and exchange
DM-59 - Data warehouses
  • Differentiate between a data warehouse and a database
  • Describe the functions that gazetteers support
  • Differentiate the retrieval mechanisms of data warehouses and databases
  • Discuss the appropriate use of a data warehouse versus a database

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