Spatial data depuration (error removal)

Filters spatial point data by removing erroneous observations based on geometric, statistical, and spatial criteria. The function implements a sequential depuration workflow commonly used in precision agriculture.

Usage

depurate(
  x,
  y,
  toremove = c("edges", "outlier", "inlier"),
  crs = NULL,
  buffer = -10,
  ylimitmax = NA,
  ylimitmin = 0,
  sdout = 3,
  ldist = 0,
  udist = 40,
  criteria = c("LM", "MP"),
  zero.policy = NULL,
  poly_border = NULL
)

Arguments

x: An sf object with POINT geometries.
y: A character string indicating the variable name used for filtering. If missing and only one attribute column is present, it is used by default.
toremove: A character vector specifying which procedures to apply. Options are "edges", "outlier", and "inlier". The order of execution is fixed and cannot be modified.
crs: Coordinate reference system used when transforming longitude/latitude data. Can be an EPSG code or proj4string.
buffer: A numeric value indicating the distance (in meters) for edge removal. Negative values are recommended to shrink boundaries.
ylimitmax: Numeric upper bound for y. If NA, Inf is used.
ylimitmin: Numeric lower bound for y. If NA, -Inf is used.
sdout: Numeric multiplier for standard deviation used to detect global outliers.
ldist: Numeric lower distance bound for neighborhood definition.
udist: Numeric upper distance bound for neighborhood definition.
criteria: Character vector specifying spatial outlier detection methods: "LM" (Local Moran) and/or "MP" (Moran Plot).
zero.policy: Logical. If TRUE, allows empty neighbor sets; if FALSE, stops with an error.
poly_border: Optional sf polygon defining field boundaries. If NULL, a hull is computed automatically.

Value

An object of class paar (list) with:

depurated_data: Filtered sf object
condition: Character vector indicating the reason each observation was removed (or NA if retained)

Details

The depuration process is applied in a fixed sequence:

Edge removal ("edges")
Global outlier removal ("outlier")
Spatial outlier removal ("inlier")

The toremove argument controls which of these steps are applied, but **does not modify the order of execution**.

Available procedures are:

edges

Removes points located within a specified buffer distance from the field boundary. The boundary is computed using a concave hull (concaveman) or a convex hull if the package is not available.

outlier

Removes global outliers based on:

user-defined limits (ylimitmin, ylimitmax)
statistical thresholds defined as \(mean \pm sdout \times sd\)

inlier

Identifies and removes spatial outliers using:

Local Moran's I statistic ("LM")
Moran scatterplot influence ("MP")

Default parameter values are tuned for precision agriculture datasets (e.g., yield maps).

References

Vega, A., Córdoba, M., Castro-Franco, M. et al. (2019). Protocol for automating error removal from yield maps. Precision Agriculture, 20, 1030–1044. doi:10.1007/s11119-018-09632-8

Examples

library(sf)
data(barley, package = 'paar')
#Convert to an sf object
barley <- st_as_sf(barley, coords = c("X", "Y"), crs = 32720)

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

# Summary of depurated data
summary(depurated)
#>       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%) 

# Keep only depurate data
depurated_data <- depurated$depurated_data
# Combine the condition for all data
all_data_condition <- cbind(depurated, barley)