data.prepare function

Prepare data

Function for data preparation for RFSI and STRK functions. It transforms data to a data.frame.

data.prepare(data,
             data.staid.x.y.z=NULL,
             obs.col=NULL,
             s.crs=NA
)

Arguments

• data: sf-class , sftime-class , SpatVector-class , SpatRaster-class or data.frame ; Contains target variable (observations) and covariates. If data.frame object, it should have next columns: station ID (staid), longitude (x), latitude (y), 3rd component - time, depth, ... (z) of the observation, and observation value (obs).
• data.staid.x.y.z: numeric or character vector; Positions or names of the station ID (staid), longitude (x), latitude (y) and 3rd component (z) columns in data.frame object (e.g. c(1,2,3,4)). If data is sf-class , sftime-class , or SpatVector-class object, data.staid.x.y.z is used to point staid and z position. Set z position to NA (e.g. c(1,2,3,NA)) or ommit it (e.g. c(1,2,3)) for spatial interpolation. Default is NULL.
• obs.col: numeric or character; Column name or number showing position of the observation column in the data. Default is 1.
• s.crs: st_crs or crs ; Source CRS of data. If data contains crs, s.crs will not be used. Default is NA.

Returns

A list with the following elements: - data.df: A data.frame obtained from data.

• data.staid.x.y.z: Positions of the station ID (staid), longitude (x), latitude (y) and 3rd component (z) columns in data.frame object (e.g. c(1,2,3,4)).

• s.crs: Source CRS of data.

• obs.col: Column number showing position of the observation column in the data.

Author(s)

Aleksandar Sekulic asekulic@grf.bg.ac.rs

References

Sekulić, A., Kilibarda, M., Heuvelink, G. B., Nikolić, M. & Bajat, B. Random Forest Spatial Interpolation. Remote. Sens. 12, 1687, https://doi.org/10.3390/rs12101687 (2020).

See Also

near.obs

rfsi

tune.rfsi

cv.rfsi

Examples

library(sf)
library(meteo)
library(sp)

# prepare data
demo(meuse, echo=FALSE)
meuse <- meuse[complete.cases(meuse@data),]
data = st_as_sf(meuse, coords = c("x", "y"), crs = 28992, agr = "constant")
data.df <- data.prepare(data,
                        obs.col="zinc")
str(data.df)