auto_interpolate_points: Automatically interpolates point values

In whamer/papros: PAthogen PROgnosis System

Description

This function tries to automatically interpolate points

Usage

auto_interpolate_points(
  sp_points,
  aim_variable,
  outputfile,
  co_variables = FALSE,
  procedure = c("ked", "rfk", "ok", "idw"),
  show_rmse = TRUE
)

Arguments

sp_points	SpatialPointsDataframe containing the aim variable and if "ked" should be applied the covariables
aim_variable	Character string with the name of the aim variable
outputfile	SpatialPointsDataframe, SpatialGridDataFrame or raster which should be filled with predictions; requires covariables for "ked" (if two values are given in a vector a raster is created with the resolution given by the values)
co_variables	default = FALSE, vector of covariables if needed
procedure	default = c("ked","rfk,"ok","idw"); vector containing the interpolation technic to be used; all methods are tested and the method with the lowest RMSE is used for the interpolation; KED = Kriging With external Drift; RFK = Random Forest Kriging; OK = Ordinary Kriging; IDW = Inverse distance Weighting
show_rmse	default = TRUE, should the RMSE values derived by loocv_interpolate_points be displayed?

Value

interpolated point values as sp or raster file depending on outputfile

Author(s)

Wolfgang Hamer

Examples

library(magrittr)
library(dplyr)
library(sp)
library(raster)

# Download example data
shdat <- download_statewide_hourly_station_data(state = "Schleswig-Holstein", coord = TRUE)

# Select data of specific Time / Date
da_sel <- shdat %>% filter(DateTime == sort(unique(shdat$DateTime))[5])

# Create spatial dataset
da_sel_sp <- SpatialPointsDataFrame(da_sel[,c("lon", "lat")],
                                    da_sel,
                                    proj4string = CRS("+init=epsg:4326"))

# Transform to projected (m based!) system
da_sel_sp <- spTransform(da_sel_sp, CRS("+init=epsg:25832"))

air_mean <- download_dwd_raster(parameter = "air_temperature_mean", period = "1961-1990", month = 17, crop=da_sel_sp)

da_sel_sp <- raster::extract(air_mean,da_sel_sp,sp=TRUE)

# Application of function for point data result
myintpoints <- auto_interpolate_points(sp_points = da_sel_sp,
                                       aim_variable = "Temperature",
                                       outputfile = air_mean,
                                       co_variables = c("air_temp_mean_1961.1990_17"))
plot(myintpoints)

whamer/papros documentation built on Feb. 6, 2021, 8:54 a.m.