MRG (version 0.3.21)

gridData: Function that converts point data to gridded data (polygon values) or a list of gridded data

Description

Function that converts point data to gridded data (polygon values) or a list of gridded data

Usage

gridData(
  ifg,
  res = 1000,
  vars = NULL,
  weights = NULL,
  nclus = 1,
  confrules = "individual",
  crsOut = NA,
  verbose = FALSE,
  locAdj = FALSE,
  centre = FALSE
)

Value

A hierarchical list of gridded data, in the different resolutions requested. Each grid also includes the count of records used for the gridding, and the sum of the weights.

Arguments

ifg

Either a data.frame or tibble or sf-object with the locations and the data of the survey or census data, or a list of such objects.

res

A resolution or a vector with the different resolutions

vars

Variable(s) of interest that should be aggregated (necessary when ifg is used for individual farm specific anonymization rules)

weights

Extrapolation factor(s) (weights) wi of unit i in the sample of units nc falling into a specific cell c. Weights are used for disclosure control measures. A weight of 1 will be used if missing. If only one weight is given, it will be used for all variables. If the length is more than one, the length has to be equal to the number of variables. If the same weight is used for several variables, it must be repeated in the weights-vector

nclus

Number of clusters to use for parallel processing. No parallelization is used for nclus = 1.

confrules

Should the frequency rule (number of holdings) refer to the number of holdings with a value of the individual vars above zero ("individual") or the total number of holdings in the data set ("total")?

crsOut

The coordinate reference system (crs) to be used

verbose

Indicates if some extra output should be printed. Usually TRUE/FALSE, but can also have a value of 2 for multiResGrid for even more output.

locAdj

parameter to adjust the coordinates if they are exactly on the borders between grid cells. The values can either be FALSE, or "jitter" (adding a small random value to the coordinates, essentially spreading them randomly around the real location), "UR", "UL", "LR" or "LL", to describe which corner of the grid cell the location belong (upper right, upper left, lower right or lower left). Please use with care in this function. It will make it possible to produce the grid,but notice that the coordinates of ifg will be left untouched, which can cause problems if it is used in other functions.

centre

logical; if the coordinate should represent the centre of the grid cell. This should never be TRUE if res is a vector of different resolutions, as the grids will not have identical starting points

Details

This will create hierarchical grids of the selected variable(s), at the requested resolution(s), and using the requested function. In reality, the function will usually be sum, mean or max3, where the last one gives the average of the three highest numbers in the grid cell.

Additionally, the function will always return the extrapolated number of farms per grid unit. The result will either be a set of sf-polygons (default) or a stars object.

Examples

# \donttest{
library(sf)
if (!require(ggplot2)) print("Plotting of results will not work without installation of ggplot2")
if (!require(viridis)) print("Some of the plots will not work without installation of ggplot2")
if (require(giscoR)) {
  useBorder = TRUE 
} else {
  useBorder = FALSE
  print("You need to install giscoR for plotting borders and clipping the gridded maps")
}

# These are SYNTHETIC agricultural FSS data 
data(ifs_dk) # Census data
# Create spatial data
ifg = fssgeo(ifs_dk, locAdj = "LL")

if (useBorder) {
# Read country borders, only used for plotting
  borders = gisco_get_nuts(nuts_level = 0)
  dkb = borders[borders$CNTR_CODE == "DK",] %>% st_transform(crs = 3035)
}

ress = c(1,5,10,20,40,80)*1000
ifl = gridData(ifg, vars = c("UAA", "UAAXK0000_ORG"), weights = "EXT_CORE", 
               res = ress)
ifl2 = gridData(ifg, vars = c("UAA", "UAAXK0000_ORG"), weights = "EXT_CORE", 
               res = ress, nclus = 2)
all.equal(ifl, ifl2)
if (require(ggplot2)) {
ifall = do.call("rbind", ifl)
g1 = ggplot() + geom_sf(data = ifall, aes(fill = count, color = count)) +
 scale_fill_viridis( name = "number of \n holdings", trans = "log10") +
 scale_color_viridis( name = "number of \n holdings", trans = "log10") +
 coord_sf(crs = 3035) +
 theme_bw() +
 ggtitle("Number of holdings for different resolutions") +
 facet_wrap(vars(res))
 if (useBorder) g1 = g1 + geom_sf(data = dkb, fill = NA, colour='black', lwd = 1)
 g1
}
#'

MRGcluster(action = "stop")

# }