2019 QUARTER 03

A B C D E F G H I K L M N O P R S T U V W
KE-09 - Labor and management
  • Identify the positions necessary to design and implement a GIS
  • Discuss the advantages and disadvantages of outsourcing elements of the implementation of a geospatial system, such as data entry
  • Evaluate the labor needed in past cases to build a new geospatial enterprise
  • Create a budget of expected labor costs, including salaries, benefits, training, and other expenses
DC-02 - Land records
  • Distinguish between GIS, LIS, and CAD/CAM in the context of land records management
  • Evaluate the difference in accuracy requirements for deeds systems versus registration systems
  • Exemplify and compare deed descriptions in terms of how accurately they convey the geometry of a parcel
  • Distinguish between topological fidelity and geometric accuracy in the context of a plat map
AM-54 - Landscape Metrics

Landscape metrics are algorithms that quantify the spatial structure of patterns – primarily composition and configuration - within a geographic area. The term "landscape metrics" has historically referred to indices for categorical land cover maps, but with emerging datasets, tools, and software programs, the field is growing to include other types of landscape pattern analyses such as graph-based metrics, surface metrics, and three-dimensional metrics. The choice of which metrics to use requires careful consideration by the analyst, taking into account the data and application. Selecting the best metric for the problem at hand is not a trivial task given the large numbers of metrics that have been developed and software programs to implement them.

FC-32 - Learning from experience
  • Explain how knowledge of the history of the development of enterprise GIS can aid in an implementation process
  • Evaluate case studies of past GISs to identify factors leading to success and failure
  • Discuss the evolution of isolated GIS projects to enterprise GIS
AM-40 - Least-cost (shortest) path analysis
  • Describe some variants of Dijkstra’s algorithm that are even more efficient
  • Discuss the difference of implementing Dijkstra’s algorithm in raster and vector modes
  • Demonstrate how K-shortest path algorithms can be implemented to find many efficient alternate paths across the network
  • Compute the optimum path between two points through a network with Dijkstra’s algorithm
  • Explain how a leading World Wide Web-based routing system works (e.g., MapQuest, Yahoo Maps, Google)
GS-23 - Legal mechanisms for sharing geospatial information
  • Describe contracts, licenses, and other mechanisms for sharing geospatial data
  • Outline the terms of a licensing agreement with a local engineering consulting firm that a manager of a county government GIS office would employ if charged to recoup revenue through sale and licensure of county data
GS-03 - Liability
  • Describe the nature of tort law generally and nuisance law specifically
  • Describe strategies for managing liability risk, including disclaimers and data quality standards
  • Describe cases of liability claims associated with misuse of geospatial information, erroneous information, and loss of proprietary interests
  • Differentiate among contract liability, tort liability, and statutory liability
PD-01 - Linear programming
  • Explain the role of constraint functions using the simplex method
  • Explain the role of objective functions in linear programming
  • Describe the structure of linear programs
  • Explain the role of constraint functions using the graphical method
  • Implement linear programs for spatial allocation problems
PD-01 - Linear programming
  • Explain the role of constraint functions using the simplex method
  • Explain the role of objective functions in linear programming
  • Describe the structure of linear programs
  • Explain the role of constraint functions using the graphical method
  • Implement linear programs for spatial allocation problems
AM-23 - Local measures of spatial association
  • Describe the effect of non-stationarity on local indices of spatial association
  • Decompose Moran’s I and Geary’s c into local measures of spatial association
  • Compute the Gi and Gi* statistics
  • Explain how geographically weighted regression provides a local measure of spatial association
  • Explain how a weights matrix can be used to convert any classical statistic into a local measure of spatial association
  • Compare and contrast global and local statistics and their uses

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