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Spatial interpolation techniques using R
Citation:
Frazier, M. AND L. McCoy. Spatial interpolation techniques using R. Presented at Geospatial Statistics Symposium, Newport, OR, May 31, 2013.
Impact/Purpose:
A WED scientist will participate in a conference on the rapidly developing field of spatial statistics, including quantitative analysis of spatial data and the statistical modeling of spatial variability and uncertainty. The WED scientist, in collaboration with a USDA collaborator, is invited to demonstrate how the statistical program R can be used to perform spatial interpolation analyses. They will also discuss statistical methods of assessing and comparing the performance of various interpolation methods. This information will provide researchers who are not GIS experts or lack access to expensive GIS programs with the tools to perform a key spatial analysis technique.
Description:
Interpolation techniques are used to predict the cell values of a raster based on sample data points. For example, interpolation can be used to predict the distribution of sediment particle size throughout an estuary based on discrete sediment samples. We demonstrate some interpolation techniques using the statistical package R. There are many options for interpolating data, and determining the best approach can be challenging. To provide guidance, we will discuss methods of assessing and comparing the performance of various interpolation methods.