You are currently viewing an archived version of Topic Spatial filtering.
If updates or revisions have been published you can find them at Spatial filtering.
Author and Citation Info:
DiBiase, D., DeMers, M., Johnson, A., Kemp, K., Luck, A. T., Plewe, B., and Wentz, E. (2006). Spatial filtering. The Geographic Information Science & Technology Body of Knowledge. Washington, DC: Association of American Geographers. (2nd Quarter 2016, first digital).
Learning Objectives:
Identify modeling situations where spatial filtering might not be appropriate
Demonstrate how spatial autocorrelation can be “removed” by resampling
Explain how dissolving clusters of blocks with similar values may resolve the spatial correlation problem
Explain how the Getis and Tiefelsdorf-Griffith spatial filtering techniques incorporate spatial component variables into OLS regression analysis in order to remedy misspecification and the problem of spatially auto-correlated residuals
Explain how spatial correlation can result as a side effect of the spatial aggregation in a given dataset
Describe the relationship between factorial kriging and spatial filtering
You are currently viewing an archived version of Topic Spatial filtering. If updates or revisions have been published you can find them at Spatial filtering.
DiBiase, D., DeMers, M., Johnson, A., Kemp, K., Luck, A. T., Plewe, B., and Wentz, E. (2006). Spatial filtering. The Geographic Information Science & Technology Body of Knowledge. Washington, DC: Association of American Geographers. (2nd Quarter 2016, first digital).