AM8-4 - Principles of kriging

You are currently viewing an archived version of Topic Kriging Interpolation. If updates or revisions have been published you can find them at Kriging Interpolation.

Author and Citation Info: 

DiBiase, D., DeMers, M., Johnson, A., Kemp, K., Luck, A. T., Plewe, B., and Wentz, E. (2006). Principles of kriging. The Geographic Information Science & Technology Body of Knowledge. Washington, DC: Association of American Geographers. (2nd Quarter 2016, first digital).

Learning Objectives: 
  • Describe the relationship between the semi-variogram and kriging
  • Explain why it is important to have a good model of the semi-variogram in kriging
  • Explain the concept of the kriging variance, and describe some of its shortcomings
  • Explain how block-kriging and its variants can be used to combine data sets with different spatial resolution (support)
  • Compare and contrast block-kriging with areal interpolation using proportional area weighting and dasymetric mapping
  • Outline the basic kriging equations in their matrix formulation
  • Conduct a spatial interpolation process using kriging from data description to final error map
  • Explain why kriging is more suitable as an interpolation method in some applications than others