2018 QUARTER 03

A B C D E F G H I K L M N O P R S T U V W
DM-16 - Linear referencing
  • Discuss dynamic segmentation as a process for transforming between linear and planar coordinate systems
  • Construct a data structure to contain point or linear geometry for database record events that are referenced by their position along a linear feature
  • Explain how linear referencing allows attributes to be displayed and analyzed that do not correspond precisely with the underlying segmentation of the network features
  • Describe how linear referencing can eliminate unnecessary segmentation of the underlying network features due to attribute value changes over time
  • Demonstrate how linear referenced locations are often much more intuitive and easy to find in the real world than geographic coordinates
DM-50 - Linear referencing systems
  • Describe an application in which a linear referencing system is particularly useful
  • Explain how the datum associated with a linear referencing system differs from a horizontal or vertical datum
  • Identify several different linear referencing methods (e.g., mileposts, reference posts, link and node) and compare them to planar grid systems
  • Identify the characteristics that all linear referencing systems have in common Unit GD4 Datums (core unit) “Horizontal” datums define the geometric relationship between a coordinate system grid and the Earth’s surface, where the Earth’s surface is approximated by an ellipsoid or other figure. “Vertical” datums are elevation reference surfaces, such as mean sea level.
  • Explain how a network can be used as the basis for reference as opposed to the more common rectangular coordinate systems
  • Discuss the magnitude and cause of error generated in the transformation from linear to planar coordinate systems
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
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.

CP-12 - Location-Based Services

Location-Based Services (LBS) are mobile applications that provide information depending on the location of the user. To make LBS work, different system components are needed, i.e., mobile devices, positioning, communication networks, and service and content provider. Almost every LBS application needs several key elements to handle the main tasks of positioning, data modeling, and information communication. With the rapid advances in mobile information technologies, LBS have become ubiquitous in our daily lives with many application fields, such as navigation and routing, social networking, entertainment, and healthcare. Several challenges also exist in the domain of LBS, among which privacy is a primary one. This topic introduces the key components and technologies, modeling, communication, applications, and the challenges of LBS.

DM-35 - Logical Data Models

A logical data model is created for the second of three levels of abstraction, conceptual, logical, and physical. A logical data model expresses the meaning context of a conceptual data model, and adds to that detail about data (base) structures, e.g. using topologically-organized records, relational tables, object-oriented classes, or extensible markup language (XML) construct  tags. However, the logical data model formed is independent of a particular database management software product. Nonetheless such a model is often constrained by a class of software language techniques for representation, making implementation with a physical data model easier. Complex entity types of the conceptual data model must be translated into sub-type/super-type hierarchies to clarify data contexts for the entity type, while avoiding duplication of concepts and data. Entities and records should have internal identifiers. Relationships can be used to express the involvement of entity types with activities or associations. A logical schema is formed from the above data organization. A schema diagram depicts the entity, attribute and relationship detail for each application. The resulting logical data models can be synthesized using schema integration to support multi-user database environments, e.g., data warehouses for strategic applications and/or federated databases for tactical/operational business applications.

KE-19 - Managing GIS operations and infrastructure
  • Calculate the estimated schedule required to carry out all of the implementation steps for an enterprise GIS of a given size
  • List some of the topics that should be addressed in a justification for implementing an enterprise GIS (e.g., return on investment, workflow, knowledge sharing)
  • Indicate the possible justifications that can be used to implement an enterprise GIS
  • Exemplify each component of a needs assessment for an enterprise GIS
  • Describe the components of a needs assessment for an enterprise GIS
DM-40 - Managing versioned geospatial databases
  • Describe an application in which it is crucial to maintain previous versions of the database
  • Describe existing algorithms designed for performing dynamic queries
  • Demonstrate how both the time criticality and the data security might determine whether one performs change detection on-line or off-line in a given scenario
  • Explain why the lack of a data librarian to manage data can have disastrous consequences on the resulting dataset
  • Produce viable queries for change scenarios using GIS or database management tools
AM-06 - Map algebra
  • Explain the categories of map algebra operations (i.e., local, focal, zonal, and global functions)
  • Explain why georegistration is a precondition to map algebra
  • Differentiate between map algebra and matrix algebra using real examples
  • Perform a map algebra calculation using command line, form-based, and flow charting user interfaces
  • Describe a real modeling situation in which map algebra would be used (e.g., site selection, climate classification, least-cost path)
  • Describe how map algebra performs mathematical functions on raster grids

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