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Author and Citation Info:
DiBiase, D., DeMers, M., Johnson, A., Kemp, K., Luck, A. T., Plewe, B., and Wentz, E. (2006). Interpolation of surfaces. The Geographic Information Science & Technology Body of Knowledge. Washington, DC: Association of American Geographers. (2nd Quarter 2016, first digital).
Learning Objectives:
Identify the spatial concepts that are assumed in different interpolation algorithms
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 be evaluated in the context of a specific problem
Design an algorithm that interpolates irregular point elevation data onto a regular grid
Outline algorithms to produce repeatable 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
Describe how surfaces can be interpolated using splines
You are currently viewing an archived version of Topic . If updates or revisions have been published you can find them at .
DiBiase, D., DeMers, M., Johnson, A., Kemp, K., Luck, A. T., Plewe, B., and Wentz, E. (2006). Interpolation of surfaces. The Geographic Information Science & Technology Body of Knowledge. Washington, DC: Association of American Geographers. (2nd Quarter 2016, first digital).