2020 QUARTER 01

A B C D E F G H I K L M N O P R S T U V W
DM-21 - Modeling three-dimensional (3-D) entities
  • Identify GIS application domains in which true 3-D models of natural phenomena are necessary
  • Illustrate the use of Virtual Reality Modeling Language (VRML) to model landscapes in 3-D
  • Explain how octatrees are the 3-D extension of quadtrees
  • Explain how voxels and stack-unit maps that show the topography of a series of geologic layers might be considered 3-D extensions of field and vector representations respectively
  • Explain how 3-D models can be extended to additional dimensions
  • Explain the use of multi-patching to represent 3-D objects
  • Explain the difficulties in creating true 3-D objects in a vector or raster format
  • Differentiate between 21/2-D representations and true 3-D models
DM-19 - Modeling uncertainty
  • Differentiate among modeling uncertainty for entire datasets, for features, and for individual data values
  • Describe SQL extensions for querying uncertainty information in databases
  • Describe extensions to relational DBMS to represent different types of uncertainty in attributes, including both vagueness/fuzziness and error-based uncertainty
  • Discuss the role of metadata in representing and communicating dataset-level uncertainty
  • Create a GIS database that models uncertain information
  • Identify whether it is important to represent uncertainty in a particular GIS application
  • Describe the architecture of data models (both field- and object-based) to represent feature-level and datum-level uncertainty
  • Evaluate the advantages and disadvantages of existing uncertainty models based on storage efficiency, query performance, ease of data entry, and ability to implement in existing software
AM-44 - Modelling Accessibility

Modelling accessibility involves combining ideas about destinations, distance, time, and impedances to measure the relative difficulty an individual or aggregate region faces when attempting to reach a facility, service, or resource. In its simplest form, modelling accessibility is about quantifying movement opportunity. Crucial to modelling accessibility is the calculation of the distance, time, or cost distance between two (or more) locations, which is an operation that geographic information systems (GIS) have been designed to accomplish. Measures and models of accessibility thus draw heavily on the algorithms embedded in a GIS and represent one of the key applied areas of GIS&T.

AM-13 - Multi-criteria evaluation
  • Describe the implementation of an ordered weighting scheme in a multiple-criteria aggregation
  • Compare and contrast the terms multi-criteria evaluation, weighted linear combination, and site suitability analysis
  • Differentiate between contributing factors and constraints in a multi-criteria application
  • Explain the legacy of multi-criteria evaluation in relation to cartographic modeling
  • Determine which method to use to combine criteria (e.g., linear, multiplication)
  • Create initial weights using the analytical hierarchy process (AHP)
  • Calibrate a linear combination model by adjusting weights using a test data set
AM-66 - Multi-layer feed-forward neural networks
  • Analyze the stability of the network using multiple runs with the same training data and architecture
  • Compare and contrast classification results when the architecture of the network and initial parameters are changed
  • Differentiate between feed-forward and recurrent architectures
  • Describe the architecture and components of a feed-forward neural network
KE-34 - Multi-Organizational GIS Coordination

For many years, collaboration has been a key cornerstone in the success of efforts achieved by the geospatial community.  When paired with governance, collaborative efforts often lead to sustainability and have the effect of broadening the benefits that can be achieved.  The following text shares how the geospatial community uses collaboration and governance as tools to achieve benefits across the community.  Case studies are provided to illustrate the process and the outcomes achieved. 

CV-12 - Multivariate Mapping

Bivariate and multivariate maps encode two or more data variables concurrently into a single symbolization mechanism. Their purpose is to reveal and communicate relationships between the variables that might not otherwise be apparent via a standard single-variable technique. These maps are inherently more complex, though offer a novel means of visualizing the nuances that may exist between the mapped variables. As information-dense visual products, they can require considerable effort on behalf of the map reader, though a thoughtfully-designed map and legend can be an interesting opportunity to effectively convey a comparative dimension.

This chapter describes some of the key types of bivariate and multivariate maps, walks through some of the rationale for various techniques, and encourages the reader to take an informed, balanced approach to map design weighing information density and visual complexity. Some alternatives to bivariate and multivariate mapping are provided, and their relative merits are discussed.

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