Geographic Information Abstractions: Conceptual Clarity for Geographic Modeling

Just as we abstract our reality to make life intellectually manageable, we must create abstractions when we build models of geographic structure and process. Geographic information abstractions with aspects of theme, time, and space can be used to provide a comprehensive description of geographic reality in a geographic information system (GIS): In the context of geographic modeling a geographic information abstraction is defined as a simultaneous focus on important characteristics of geographic content, structure, and process while temporarily suppressing certain details—rather than elimination or deletion of detail. Geographic information abstractions can be used in a database design process to develop a more realistic description of reality in the form of a database model. The geographic information abstraction types are: classification, generalization, aggregation, and association. They are used to structure a descriptive GIS database model by using an example from urban transportation. The embedding of a practically adequate descriptive database model in explanatory and predictive models of urban change is discussed.

[1]  Steven B. Caldwell.  Modeling demographic-economic interactions: Micro, macro and linked micro/macro strategies , 1983 .

[2]  Diane C. P. Smith,et al.  Database abstractions: aggregation and generalization , 1977, TODS.

[3]  David Rhind,et al.  A GIS research agenda , 1988, Int. J. Geogr. Inf. Sci..

[4]  Mark L. Johnson.  The body in the mind: the bodily basis of meaning , 1987 .

[5]  J. Mill.  A System of Logic , 1843 .

[6]  Donna J. Peuquet,et al.  Representations of Geographic Space: Toward a Conceptual Synthesis , 1988 .

[7]  Timothy L. Nyerges,et al.  Schema integration analysis for the development of GIS databases , 1989, Int. J. Geogr. Inf. Sci..

[8]  N. Presmeg.  The body in the mind: The bodily basis of meaning, imagination and reason , 1992 .

[9]  Michael Schrefl,et al.  Comparison-criteria for semantic data models , 1984, 1984 IEEE First International Conference on Data Engineering.

[10]  Gunnar Olsson,et al.  Birds in Egg/Eggs in Bird , 1980 .

[11]  R. A. Sayer,et al.  Understanding Urban Models versus Understanding Cities , 1979 .

[12]  Roger King,et al.  Semantic database modeling: survey, applications, and research issues , 1987, CSUR.

[13]  Ronald J. Brachman,et al.  ON THE EPISTEMOLOGICAL STATUS OF SEMANTIC NETWORKS , 1979 .

[14]  Harold Moellering,et al.  Strategies of Real-time Cartography , 1980 .

[15]  Douglass B. Lee,et al.  Requiem for large-scale models , 1973, SIML.

[16]  Robert Weibel,et al.  A review and conceptual framework of automated map generalization , 1988, Int. J. Geogr. Inf. Sci..

[17]  Laurian M. Chirica,et al.  The entity-relationship model: toward a unified view of data , 1975, SIGF.

[18]  Timothy L. Nyerges.  Analytical Map Use , 1991 .

[19]  Timothy L. Nyerges,et al.  Modeling the structure of cartographic information for query processing , 1980 .

[20]  Harold Moellering.  Real Maps, Virtual Maps and Interactive Cartography , 1984 .

[21]  Arthur M. Geoffrion,et al.  An Introduction to Structured Modeling , 1987 .

[22]  Ag Wilson,et al.  Transport, location and spatial systems: planning with spatial interaction models and related approaches. , 1983 .