All Topics

A B C D E F G H I K L M N O P R S T U V W
AM-41 - Flow modeling
  • Describe practical situations in which flow is conserved while splitting or joining at nodes of the network
  • Apply a maximum flow algorithm to calculate the largest flow from a source to a sink, using the edges of the network, subject to capacity constraints on the arcs and the conservation of flow
  • Explain how the concept of capacity represents an upper limit on the amount of flow through the network
  • Demonstrate how capacity is assigned to edges in a network using the appropriate data structure
FC-05 - From concepts to data
  • Define the following terms: data, information, knowledge, and wisdom
  • Describe the limitations of various information stores for representing geographic information, including the mind, computers, graphics, and text
  • Transform a conceptual model of information for a particular task into a data model
KE-11 - Funding
  • Identify potential sources of funding (internal and external) for a project or enterprise GIS
  • Create proposals and presentations to secure funding
  • Analyze previous attempts at funding to identify successful and unsuccessful techniques
AM-88 - Fuzzy aggregation operators
  • Compare and contrast Boolean and fuzzy logical operations
  • Compare and contrast several operators for fuzzy aggregation, including those for intersect and union
  • Exemplify one use of fuzzy aggregation operators
  • Describe how an approach to map overlay analysis might be different if region boundaries were fuzzy rather than crisp
  • Describe fuzzy aggregation operators
DM-41 - Fuzzy logic
  • Describe how linear functions are used to fuzzify input data (i.e., mapping domain values to linguistic variables)
  • Support or refute the statement by Lotfi Zadeh, that “As complexity rises, precise statements lose meaning and meaningful statements lose precision,” as it relates to GIS&T
  • Explain why fuzzy logic, rather then Boolean algebra models, can be useful for representing real world boundaries between different tree species
DM-27 - Genealogical relationships: lineage, inheritance
  • Describe ways in which a geographic entity can be created from one or more others
  • Discuss the effects of temporal scale on the modeling of genealogical structures
  • Describe the genealogy (as identity-based change or temporal relationships) of particular geographic phenomena
  • Determine whether it is important to represent the genealogy of entities for a particular application
AM-78 - Genetic algorithms and artificial genomes
  • Create an artificial genome that can be used in a genetic algorithm to solve a specific problem
  • Describe a cluster in a way that could be represented in a genome
  • Explain how and why the representation of a GA’s chromosome strings can enhance or hinder the effectiveness of the GA
  • Use one of the many freely available GA packages to apply a GA to implement a simple genetic algorithm to a simple problem, such as optimizing the location of one or more facilities or optimizing the selection of habitat for a nature preserve geospatial pattern optimization (such as for finding clusters of disease points)
  • Describe a potential solution for a problem in a way that could be represented in a chromosome and evaluated according to some measure of fitness (such as the total distance everyone travels to the facility or the diversity of plants and animals that would be protected) genome
AM-77 - Genetic algorithms and global solutions

Genetic algorithms (GAs) are a family of search methods that have been shown to be effective in finding optimal or near-optimal solutions to a wide range of optimization problems. A GA maintains a population of solutions to the problem being solved and uses
crossover, mutation, and selection operations to iteratively modify them. As the population
evolves across generations, better solutions are created and inferior ones are selectively
discarded. GAs usually run for a fixed number of iterations (generations) or until further
improvements do not obtain. This contribution discusses the fundamental principles of
genetic algorithms and uses Python code to illustrate how GAs can be developed for both
numerical and spatial optimization problems. Computational experiments are used to
demonstrate the effectiveness of GAs and to illustrate some nuances in GA design.

DM-47 - Geographic coordinate system
  • Distinguish between various latitude definitions (e.g., geocentric, geodetic, astronomic latitudes)
  • Explain the angular measurements represented by latitude and longitude coordinates
  • Calculate the latitude and longitude coordinates of a given location on the map using the coordinate grid ticks in the collar of a topographic map and the appropriate interpolation formula
  • Mathematically express the relationship between Cartesian coordinates and polar coordinates
  • Calculate the uncertainty of a ground position defined by latitude and longitude coordinates specified in decimal degrees to a given number of decimal places
  • Use GIS software and base data encoded as geographic coordinates to geocode a list of address-referenced locations
  • Locate on a globe the positions represented by latitude and longitude coordinates
  • Write an algorithm that converts geographic coordinates from decimal degrees (DD) to degrees, minutes, seconds (DMS) format
FC-22 - Geometric primitives
  • Identify the three fundamental dimensionalities used to represent points, lines, and areas
  • Describe the data models used to encode coordinates as points, lines, or polygons
  • Critique the assumptions that are made in representing the world as points, lines, and polygons
  • Evaluate the correspondence between geographic phenomena and the shapes used to represent them

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