All Topics

A B C D E F G H I K L M N O P R S T U V W
DM-02 - Data retrieval strategies
  • Analyze the relative performance of data retrieval strategies
  • Implement algorithms that retrieve geospatial data from a range of data structures
  • Describe the particular advantages of Morton addressing relative to geographic data representation
  • Discuss the advantages and disadvantages of different data structures (e.g., arrays, linked lists, binary trees, hash tables, indexes) for retrieving geospatial data
  • Compare and contrast direct and indirect access search and retrieval methods
KE-18 - Data sharing among public and private agencies, organizations, and individuals
  • Describe formal and informal arrangements that promote geospatial data sharing (e.g., FGDC, ESDI, memoranda of agreements, informal access arrangements, targeted funding support)
  • Describe a situation in which politics interferes with data sharing and exchange
DM-59 - Data warehouses
  • Differentiate between a data warehouse and a database
  • Describe the functions that gazetteers support
  • Differentiate the retrieval mechanisms of data warehouses and databases
  • Discuss the appropriate use of a data warehouse versus a database
DM-62 - Database administration
  • Describe how using standards can affect implementation of a GIS
  • Explain how validation and verification processes can be used to maintain database integrity
  • Summarize how data access processes can be a factor in development of an enterprise GIS implementation
  • Describe effective methods to get stakeholders to create, adopt, or develop and maintain metadata for shared datasets
FC-24 - Definitions within a conceptual model of uncertainty
  • Describe a stochastic error model for a natural phenomenon
  • Differentiate between the following concepts: vagueness and ambiguity, well defined and poorly defined objects, and fields or discord and non-specificity
  • Explain how the familiar concepts of geographic objects and fields affect the conceptualization of uncertainty
CV-29 - Design and Aesthetics

Design and aesthetics are fundamental to cartographic practice. Developing students’ skills in design and aesthetics is a critical part of cartography education, yet design is also one of the most difficult part of the cartographic process. The cartographic design process of planning, creating, critiquing, and revising maps provides a method for making maps with intentional design decisions, utilizing an understanding of aesthetics to promote clarity and cohesion to attract the user and facilitate an emotional response. In this entry, cartographic design and the cartographic design process are reviewed, and the concepts of aesthetics, style, and taste are explained in the context of cartographic design.

PD-03 - Development environments for geospatial applications
  • Develop a geospatial application using the most appropriate environment
  • Compare and contrast the relative merits of available environments for geospatial applications, including desktop software scripting (e.g., VBA), graphical modeling tools, geospatial components in standard environments, and “from-scratch” development in standard environments
DM-20 - Discrete entities
  • Discuss the human predilection to conceptualize geographic phenomena in terms of discrete entities
  • Compare and contrast differing epistemological and metaphysical viewpoints on the “reality” of geographic entities
  • Identify the types of features that need to be modeled in a particular GIS application or procedure
  • Identify phenomena that are difficult or impossible to conceptualize in terms of entities
  • Describe the difficulties in modeling entities with ill-defined edges
  • Describe the difficulties inherent in extending the “tabletop” metaphor of objects to the geographic environment
  • Evaluate the effectiveness of GIS data models for representing the identity, existence, and lifespan of entities
  • Justify or refute the conception of fields (e.g., temperature, density) as spatially-intensive attributes of (sometimes amorphous and anonymous) entities
  • Model “gray area” phenomena, such as categorical coverages (a.k.a. discrete fields), in terms of objects
  • Evaluate the influence of scale on the conceptualization of entities
  • Describe the perceptual processes (e.g., edge detection) that aid cognitive objectification
  • Describe particular entities in terms of space, time, and properties
AM-50 - Distance Operations

Distance is a central concept in geography, and consequently, there are various types of operations that leverage the concept of distance. This short article introduces common distance measures, the purpose of distance operations, different types of operations and considerations, as well as sample applications in the physical and social domains. Distance operations can be performed on both vector or raster data, but the operations and results may differ. While performing distance operations, it is important to remember how distance is conceptualized while performing the operation.

FC-14 - Distance, Length, and Direction
  • Describe several different measures of distance between two points (e.g., Euclidean, Manhattan, network distance, spherical)
  • Explain how different measures of distance can be used to calculate the spatial weights matrix
  • Explain why estimating the fractal dimension of a sinuous line has important implications for the measurement of its length
  • Explain how fractal dimension can be used in practical applications of GIS
  • Explain the differences in the calculated distance between the same two places when data used are in different projections
  • Outline the implications of differences in distance calculations on real world applications of GIS, such as routing and determining boundary lengths and service areas
  • Estimate the fractal dimension of a sinuous line
  • Describe operations that can be performed on qualitative representations of direction
  • Explain any differences in the measured direction between two places when the data are presented in a GIS in different projections
  • Compute the mean of directional data
  • Compare and contrast how direction is determined and stated in raster and vector data
  • Define “direction” and its measurement in different angular measures

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