paar paar website

R-CMD-check Lifecycle: experimental R-CMD-check

The goal of paar is to provide useful functions for precision agriculture spatial data depuration.

Installation

You can install the released version of paar from CRAN with (not-yet):

# install.packages("paar")

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("PPaccioretti/paar")

Example

The package has a complete protocol for automating error removal. Default values of all functions are optimized for precision agricultural data.

library(paar)
library(sf)
#> Warning: package 'sf' was built under R version 4.3.3
data("barley", package = 'paar')

barley data contains barley grain yield which were obtained using calibrated commercial yield monitors, mounted on combines equipped with DGPS.

#Convert barley data to an spatial object
barley_sf <- st_as_sf(barley,
                   coords = c("X", "Y"),
                   crs = 32720)

barley_dep <-
  depurate(barley_sf,
           "Yield")
#> Concave hull algorithm is computed with
#> concavity = 2 and length_threshold = 0

# Summary of depurated data
summary(barley_dep)
#>       normal point             border spatial outlier MP spatial outlier LM 
#>         5673 (77%)          964 (13%)         343 (4.6%)         309 (4.2%) 
#>         global min            outlier 
#>          99 (1.3%)         6 (0.081%)

Spatial yield values before and after depuration process can be plotted

plot(barley_sf["Yield"], main = "Before depuration")
plot(barley_dep$depurated_data["Yield"], main = "After depuration")

Also distribution of yield values can be plotted

boxplot(barley_sf[["Yield"]], main = "Before depuration")
boxplot(barley_dep$depurated_data[["Yield"]], main = "After depuration")

References