Spatial Concept Perspectives

We have gathered ~300 excerpts from published works about fundamental spatial concept terms. These have been cross-referenced with the concept lexicon appearing on the left. Those terms were drawn from the U.S.National Science Education Standards (NSES 1996) for topic areas B - Physical Science, C - Life Science, D - Earth and Space Science, as well as from the 1994 U.S. Geography Teaching Standards for grades 9-12. Those standards can be browsed here.

spatial concept terms

disciplinary perspectives on "spatial interpolation"

interpolation

Reconstruction of the underlying continuous field of data from the limited evidence of the control points, called interpolation, is an example of the classic missing data problem in statistics. Whatever type of surface is involved and whatever control points are used, the objective is to produce a field of values to some satisfactory level of accuracy relative to the intended subsequent use of the data (p. 215). Spatial interpolation is the prediction of exact values of attributes at unsampled locations from measurements made at control points within the same area (p. 220).

Geography

O'Sullivan and Unwin (2002)

Geographic Information Analysis

interpolation

Topic AM6-2. Identify the spatial concepts that are assumed in different interpolation algorithms; Describe how surfaces can be interpolated using splines; Compare and contrast interpolation by inverse distance weighting, bi-cubic spline fitting, and kriging; Differentiate between trend surface analysis and deterministic spatial interpolation; Explain why different interpolation algorithms produce different results and suggest ways by which these can contour-type lines from point datasets using proximity polygons, spatial averages, or inverse distance weighting; Implement a trend surface analysis using either the supplied function in a GIS or a regression function from any standard statistical package.

Geography
Education

DiBiase, et al. (2006)

Geographic Information Science and Technology Body of Knowledge

interpolation

Determine value of two or more location/place-based distributions (p. 92)

Geography

Golledge, et al. (2008)

Matching geospatial concepts with geographic educational needs

modifiable areal unit

Analytic results depend on the choice of geographic analysis units; interpretations must consider districting effects, the modifiable areal unit problem, and areal interpolation

Geography

de Smith, et al. (2008)

Geospatial Analysis: A comprehensive guide to principles, techniques, and software tools

spatial interpolation

Estimating the value of a field at places where it has not been measured, using, e.g., contour interpolation, inverse distance weighting, natural neighbor, radial basis functions, linear and non-linear triangulation, and geostatistics. "If spatial sampling is an efficient way of capturing knowledge of spatial variation, then there must be reliable ways of filling in the unknown variation between sample points. Spatial interpolation attempts to do this, by providing a method of estimating the value of a field anywhere from a limited number of sample points.

Geography

de Smith, et al. (2008)

Geospatial Analysis: A comprehensive guide to principles, techniques, and software tools