Geographic information science (GISc or GISci or GIScience) is the academic theory behind the development, use, and application of geographic information systems (GIS). It is concerned with people, hardware, software, and geospatial data. GISc addresses fundamental issues raised by the use of GIS and related information technologies (Goodchild 1990, 1992; Wilson and Fotheringham 2007).
Three central issues of GISc are the modifiable areal unit problem, complete spatial randomness and spatial autocorrelation. GISc is relevant to researchers from many scientific disciplines because these three central issues are often ignored in the application of statistical hypothesis testing. GISc argues that both Bayesian and Traditional statistical inference should consider spatial structure of the data being analyzed.
Complete spatial randomness is also referred to as global spatial homogeneity. Spatial autocorrelation is also referred to as global spatial heterogeneity. These terms depend on scale. For example, a spatially homogeneous dataset at a global scale may be heterogeneous at a local scale. Likewise, globally heterogeneous spatial data can be locally homogeneous, data values at near places being more similar than values at further places.
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Geographic information science (GISc or GISci or GIScience) is the academic theory behind the development, use, and application of geographic information systems (GIS). It is concerned with people, hardware, software, and geospatial data. GISc addresses fundamental issues raised by the use of GIS and related information technologies (Goodchild 1990, 1992; Wilson and Fotheringham 2007).
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