A class for spatial predictions produced using gstat package

Description

A class containing input and output maps generated through the process of geostatistical mapping. Object of this class can be directly visualized in Google Earth by using the plotKML-method.

Slots

variable:

object of class "character"; variable name

observed:

object of class "SpatialPointsDataFrame" (must be 2D); see sp::SpatialPointsDataFrame

regModel.summary:

contains the summary of the regression model

vgmModel:

object of class "data.frame"; contains the variogram parameters passed from gstat

predicted:

object of class "SpatialPixelsDataFrame"; see sp::SpatialPixelsDataFrame

validation:

object of class "SpatialPointsDataFrame" containing results of validation

Methods

plot

signature(x = "SpatialPredictions"): spatial predictions, regression model (observed vs predicted), original variogram and variogram for residuals

plotKML

signature(obj = "SpatialPredictions"): plots all objects in Google Earth

summary

signature(obj = "SpatialPredictions"): summarize object by showing the mapping accuracy (cross-validation) and the amount of variation explained by the model

Note

"SpatialPredictions" saves results of predictions for a single target variable, which can be of type numeric or factor. Multiple variables can be combined into a list.

Author(s)

Tomislav Hengl

References

• Hengl, T. (2009) A Practical Guide to Geostatistical Mapping, 2nd Edt. University of Amsterdam, www.lulu.com, 291 p.

• Hengl, T., Nikolic, M., MacMillan, R.A., (2012) Mapping efficiency and information content. International Journal of Applied Earth Observation and Geoinformation, special issue Spatial Statistics Conference.

See Also

plotKML-method, GSIF::fit.gstatModel, gstat::gstat-class, RasterBrickSimulations-class