All Topics

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
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.

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
AM-43 - Location and Service Area Problems

Many facilities exist to provide essential services in a city or region. The service area of a facility refers to a geographical area where the intended service of the facility can be received effectively. Service area delineation varies with the particular service a facility provides. This topic examines two types of service areas, one that can be defined based on a predetermined range such as travel distance/time and another based on the nearest facility available. Relevant location models are introduced to identify the best location(s) of one or multiple facilities to maximize service provision or minimize the system-wide cost. The delineation of service areas and structuring of a location model draw extensively on existing functions in a GIS. The topic represents an important area of GIS&T.

GS-04 - Location Privacy

How effective is this fence at keeping people, objects, or sensitive information inside or outside? Location Privacy is concerned with the claim of individuals to determine when, how, and to what extent information about themselves and their location is communicated to others. Privacy implications for spatial data are growing in importance with growing awareness of the value of geo-information and the advent of the Internet of Things, Cloud-Based GIS, and Location Based Services.  

In the rapidly changing landscape of GIS and public domain spatial data, issues of location privacy are more important now than ever before. Technological trailblazing tends to precede legal safeguards. The development of GIS tools and the work of the GIS&T research and user community have typically occurred at a much faster rate than the establishment of legislative frameworks governing the use of spatial data, including privacy concerns. Yet even in a collaborative environment that characterizes the GIS&T community, and despite progress made, the issue of location privacy is a particularly thorny one, occurring as it does at the intersection of geotechnology and society.

AM-46 - Location-allocation modeling

Location-allocation models involve two principal elements: 1) multiple facility location; and 2) the allocation of the services or products provided by those facilities to places of demand. Such models are used in the design of logistic systems like supply chains, especially warehouse and factory location, as well as in the location of public services. Public service location models involve objectives that often maximize access and levels of service, while private sector applications usually attempt to minimize cost. Such models are often hard to solve and involve the use of integer-linear programming software or sophisticated heuristics. Some models can be solved with functionality provided in GIS packages and other models are applied, loosely coupled, with GIS. We provide a short description of formulating two different models as well as discuss how they are solved.