All Topics

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
CV-28 - Lesson Design in Cartography Education

This entry describes six general variables of lesson design in cartography education and offers some practical advice for the development of materials for teaching cartography. First, a lesson’s scope concerns the set of ideas included in a lesson and helps identify different types of lessons based on the kinds of knowledge that they contain. Second, learning objectives concern the things that students should be able to do following a lesson and relate to different cognitive processes of learning. Third, a lesson’s scheme deals with the organizational framework for delivering content. Fourth, a lesson’s guidance concerns the amount and quality of supportive information provided. Fifth, a lesson’s sequence may involve one or more strategies for ordering content. Sixth, a lesson’s activity concerns what students do during a lesson and is often associated with different learning outcomes. These six variables help differentiate traditions for teaching cartography, elucidate some of the recurring challenges in cartography education, and offer strategies for designing lessons to foster meaningful learning outcomes.

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
DC-27 - Light Detection and Ranging (LiDAR)

LiDAR (Light Detection and Ranging) is a remote sensing technology that collects information reflected or refracted from the Earth’s surface. The instrumentation that collects LiDAR data can be housed on drones, airplanes, helicopters, or satellites, and consists of a laser scanner that transmits pulses of light. These transmitted pulses reflect or refract from objects on the Earth’s surface or from the surface itself, and the time delay is recorded. Knowing the travel time and the speed of light, an elevation of each pulse above the surface can be determined. From the pulse data collected, the user can determine the topography and landscape features of the Earth or whatever surface has received the pulses. The evolution of software that displays and analyzes LiDAR data and the development of new and more compact file formats have allowed the use of LiDAR to grow dramatically in recent years.

PD-01 - Linear Programming and GIS

Linear programming is a set of methods for finding optimal solutions to mathematical models composed of a set of linear functions. Many spatial location problems can be structured as linear programs. However, even modest-sized problem instances can be very difficult to solve due to the combinatorial complexity of the problems and the associated computational expense that they incur. Geographic Information Systems software does not typically incorporate formal linear programming functionality, and instead commonly uses heuristic solution procedures to generate near-optimal solutions quickly. There is growing interest in integrating the spatial analytic tools incorporated in Geographic Information Systems with the solution power of linear programming software to generate guaranteed optimal solutions to spatial location problems.

DM-16 - Linear Referencing

Linear referencing is a term that encompasses a family of concepts and techniques for associating features with a spatial location along a network, rather than referencing those locations to a traditional spherical or planar coordinate system. Linear referencing is used when the location on the network, and the relationships to other locations on the network, are more significant than the location in 2D or 3D space. Linear referencing is commonly used in transportation applications, including roads, railways, and pipelines, although any network structure can be used as the basis for linearly referenced features. Several data models for storing linearly referenced data are available, and well-defined sets of procedures can be used to implement linear referencing for a particular application. As network analysis and network based statistical analysis become more prevalent across disciplines, linear referencing is likely to remain an important component of the data used for such analyses.