elements of geographic information

DM-24 - Integrated models
  • Discuss the contributions of early attempts to integrate the concepts of space, time, and attribute in geographic information, such as Berry (1964) and Sinton (1978)
  • Determine whether phenomena or applications exist that are not adequately represented in an existing comprehensive model
  • Discuss the degree to which these models can be implemented using current technologies
  • Design data models for specific applications based on these comprehensive general models
  • Illustrate major integrated models of geographic information, such as Peuquet’s triad, Mennis’ pyramid, and Yuan’s three-domain
DM-23 - Fields in space and time
  • Define a field in terms of properties, space, and time
  • Formalize the notion of field using mathematical functions and calculus
  • Recognize the influences of scale on the perception and meaning of fields
  • Evaluate the field view’s description of “objects” as conceptual discretizations of continuous patterns
  • Identify applications and phenomena that are not adequately modeled by the field view
  • Identify examples of discrete and continuous change found in spatial, temporal, and spatio-temporal fields
  • Relate the notion of field in GIS to the mathematical notions of scalar and vector fields
  • Differentiate various sources of fields, such as substance properties (e.g., temperature), artificial constructs (e.g., population density), and fields of potential or influence (e.g., gravity)
DM-22 - Events and processes
  • Compare and contrast the concepts of continuants (entities) and occurrents (events)
  • Describe the “actor” role that entities and fields play in events and processes
  • Discuss the difficulty of integrating process models into GIS software based on the entity and field views, and methods used to do so
  • Apply or develop formal systems for describing continuous spatio-temporal processes
  • Evaluate the assertion that “events and processes are the same thing, but viewed at different temporal scales”
  • Describe particular events or processes in terms of identity, categories, attributes, and locations
  • Compare and contrast the concepts of event and process
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
DM-24 - Integrated models
  • Discuss the contributions of early attempts to integrate the concepts of space, time, and attribute in geographic information, such as Berry (1964) and Sinton (1978)
  • Determine whether phenomena or applications exist that are not adequately represented in an existing comprehensive model
  • Discuss the degree to which these models can be implemented using current technologies
  • Design data models for specific applications based on these comprehensive general models
  • Illustrate major integrated models of geographic information, such as Peuquet’s triad, Mennis’ pyramid, and Yuan’s three-domain
DM-23 - Fields in space and time
  • Define a field in terms of properties, space, and time
  • Formalize the notion of field using mathematical functions and calculus
  • Recognize the influences of scale on the perception and meaning of fields
  • Evaluate the field view’s description of “objects” as conceptual discretizations of continuous patterns
  • Identify applications and phenomena that are not adequately modeled by the field view
  • Identify examples of discrete and continuous change found in spatial, temporal, and spatio-temporal fields
  • Relate the notion of field in GIS to the mathematical notions of scalar and vector fields
  • Differentiate various sources of fields, such as substance properties (e.g., temperature), artificial constructs (e.g., population density), and fields of potential or influence (e.g., gravity)
DM-22 - Events and processes
  • Compare and contrast the concepts of continuants (entities) and occurrents (events)
  • Describe the “actor” role that entities and fields play in events and processes
  • Discuss the difficulty of integrating process models into GIS software based on the entity and field views, and methods used to do so
  • Apply or develop formal systems for describing continuous spatio-temporal processes
  • Evaluate the assertion that “events and processes are the same thing, but viewed at different temporal scales”
  • Describe particular events or processes in terms of identity, categories, attributes, and locations
  • Compare and contrast the concepts of event and process
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
DM-24 - Integrated models
  • Discuss the contributions of early attempts to integrate the concepts of space, time, and attribute in geographic information, such as Berry (1964) and Sinton (1978)
  • Determine whether phenomena or applications exist that are not adequately represented in an existing comprehensive model
  • Discuss the degree to which these models can be implemented using current technologies
  • Design data models for specific applications based on these comprehensive general models
  • Illustrate major integrated models of geographic information, such as Peuquet’s triad, Mennis’ pyramid, and Yuan’s three-domain
DM-23 - Fields in space and time
  • Define a field in terms of properties, space, and time
  • Formalize the notion of field using mathematical functions and calculus
  • Recognize the influences of scale on the perception and meaning of fields
  • Evaluate the field view’s description of “objects” as conceptual discretizations of continuous patterns
  • Identify applications and phenomena that are not adequately modeled by the field view
  • Identify examples of discrete and continuous change found in spatial, temporal, and spatio-temporal fields
  • Relate the notion of field in GIS to the mathematical notions of scalar and vector fields
  • Differentiate various sources of fields, such as substance properties (e.g., temperature), artificial constructs (e.g., population density), and fields of potential or influence (e.g., gravity)

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