Foundational Concepts

The foundational concepts are the elementary building blocks and context setting constraints of all other entries in the BoK. The latter encompass the philosophical and mathematical support for GIScience as well as data models, while the constituent elements include, among others, notions of scale, spatial data quality, and openness. This knowledge area is also the place to look for the origins and future of GIScience.

Topics in this Knowledge Area are listed thematically below. Existing topics are in regular font and linked directly to their original entries (published in 2006; these contain only Learning Objectives). Entries that have been expanded and revised are in bold. Forthcoming, future topics are italicized

Origins Basic Measures
Intro to the GIS&T Body of Knowledge First & Second Laws of Geography
Public Sector Origins Shape
Private Sector Origins Distance Operations
Academic Developments of GIS&T Directional Operations
Cognitive Areal Operations
Perceptions and Cognition of Geographic Phenomena Proximity & Distance Decay
Foundational Ontologies Adjacency and Connectivity
Ontologies for Analysis & Formation of Geospatial Concepts Resolution
Place and Landscape Spatial Autocorrelation
The Power of Maps and Mapping Geometric Primitives and Algorithms
Semantic Information Elicitation Interrogating Geographic Information
Domains of Geographic Information Set Theory
Space Structured Query Language (SQL) and Attribute Queries
Time Spatial Queries
Relationships between Space and Time  
Properties Uncertainty
Networks Defined Problems of Scale and Zoning
Events and Processes Thematic Accuracy and Assessment
Neighborhoods Conceptual Models of Error and Uncertainty
Philosophical Perspectives  


FC-37 - Spatial Autocorrelation

The scientific term spatial autocorrelation describes Tobler’s first law of geography: everything is related to everything else, but nearby things are more related than distant things. Spatial autocorrelation has a:

  • past characterized by scientists’ non-verbal awareness of it, followed by its formalization;
  • present typified by its dissemination across numerous disciplines, its explication, its visualization, and its extension to non-normal data; and
  • an anticipated future in which it becomes a standard in data analytic computer software packages, as well as a routinely considered feature of space-time data and in spatial optimization practice.

Positive spatial autocorrelation constitutes the focal point of its past and present; one expectation is that negative spatial autocorrelation will become a focal point of its future.

FC-13 - Spatial queries
  • Demonstrate the syntactic structure of spatial and temporal operators in SQL
  • State questions that can be solved by selecting features based on location or spatial relationships
  • Construct a query statement to search for a specific spatial or temporal relationship
  • Construct a spatial query to extract all point objects that fall within a polygon
  • Compare and contrast attribute query and spatial query
FC-12 - Structured Query Language (SQL) and attribute queries
  • Define basic terms of query processing (e.g., SQL, primary and foreign keys, table join)
  • Create an SQL query to retrieve elements from a GIS
  • Explain the basic logic of SQL syntax
  • Demonstrate the basic syntactic structure of SQL
FC-20 - The power of maps
  • Describe how maps such as topographic maps are produced within certain relations of power and knowledge
  • Discuss how the choices used in the design of a road map will influence the experience visitors may have of the area
  • Explain how legal issues impact the design and content of such special purpose maps as subdivision plans, nautical charts, and cadastral maps
  • Exemplify maps that illustrate the provocative, propagandistic, political, and persuasive nature of maps and geospatial data
  • Demonstrate how different methods of data classification for a single dataset can produce maps that will be interpreted very differently by the user
  • Deconstruct the silences (feature omissions) on a map of a personally well known area
  • Construct two maps about a conflict or war producing one supportive of each side’s viewpoint
FC-27 - Thematic Accuracy Assessment

Geographic Information System (GIS) applications often involve various analytical techniques and geographic data to produce thematic maps for gaining a better understanding of geospatial situations to support spatial decisions. Accuracy assessment of a thematic map is necessary for evaluating the quality of the research results and ensuring appropriate use of the geographic data. Thematic accuracy deals with evaluating the accuracy of the attributes or labels of mapped features by comparing them to a reference that is assumed to be true. The fundamental practice presents the remote sensing approach to thematic accuracy assessment as a good guidance. For instance, the accuracy of a remote sensing image can be represented as an error matrix when the map and reference classification are conducted based on categories. This entry introduces basic concepts and techniques used in conducting thematic accuracy with an emphasis on land cover classification based on remote sensing images. The entry first introduces concepts of spatial uncertainty and spatial data quality standards and further gives an example of how spatial data quality affects thematic accuracy. Additionally, the entry illustrates the techniques that can be used to access thematic accuracy as well as using spatial autocorrelation in thematic accuracy sampling design.

FC-08 - Time

Time is a fundamental concept in geography and many other disciplines. This article introduces time at three levels. At the philosophical level, the article reviews various notions on the nature of time from early mythology to modern science and reveals the dual nature of reality: external (absolute, physical) and internal (perceived, cognitive). At the analytical level, it introduces the measurement of time, the two frames of temporal reference: calendar time and clock time, and the standard time for use globally. The article continues to discuss time in GIS at the practical level. The GISystem was first created as a “static” computer-based system that stores the present status of a dynamic system. Now, GISystems can track and model the dynamics in geographical phenomena and human-environment interactions. Representations of time in dynamic GISystems adopt three perspectives: discrete time, continuous time and Minkowski’s spacetime, and three representations: ordinal, interval, and cyclical. The appropriate perspective and representation depend on the observed temporal patterns, which can be static, oscillating, chaotic, or stochastic. Recent progress in digital technology brings us opportunities and challenges to collect, manage and analyze spatio-temporal data to advance our understanding of dynamical phenomena.