group_polys {spatsoc}

Group Polygons

Description

group_polys groups rows into spatial groups by overlapping polygons (home ranges). The function accepts a data.table with relocation data, individual identifiers and an area argument. The relocation data is transformed into home range POLYGONs using build_polys() with adehabitatHR::mcp or adehabitatHR::kernelUD. If the area argument is FALSE, group_polys returns grouping calculated by spatial overlap. If the area argument is TRUE, group_polys returns the area area and proportion of overlap. Relocation data should be in two columns representing the X and Y coordinates.

Usage

group_polys(
  DT = NULL,
  area = NULL,
  hrType = NULL,
  hrParams = NULL,
  projection = NULL,
  id = NULL,
  coords = NULL,
  splitBy = NULL,
  sfPolys = NULL
)

Arguments

DT

input data.table

area

boolean indicating either overlap group (when FALSE) or area and proportion of overlap (when TRUE)

hrType

type of HR estimation, either 'mcp' or 'kernel'

hrParams

a named list of parameters for adehabitatHR functions

projection

numeric or character defining the coordinate reference system to be passed to sf::st_crs. For example, either projection = "EPSG:32736" or projection = 32736.

id

Character string of ID column name

coords

Character vector of X coordinate and Y coordinate column names

splitBy

(optional) character string or vector of grouping column name(s) upon which the grouping will be calculated

sfPolys

Alternatively, provide solely a simple features object with POLYGONs or MULTIPOLYGONs. If sfPolys are provided, id is required and splitBy cannot be used.

Details

R-spatial evolution

Please note, spatsoc has followed updates from R spatial, GDAL and PROJ for handling projections, see more below and details at https://r-spatial.org/r/2020/03/17/wkt.html.

In addition, group_polys previously used rgeos::gIntersection, rgeos::gIntersects and rgeos::gArea but has been updated to use sf::st_intersects, sf::st_intersection and sf::st_area according to the R-spatial evolution, see more at https://r-spatial.org/r/2022/04/12/evolution.html.

Notes on arguments

The DT must be a data.table. If your data is a data.frame, you can convert it by reference using data.table::setDT().

The id, coords (and optional splitBy) arguments expect the names of respective columns in DT which correspond to the individual identifier, X and Y coordinates, and additional grouping columns.

The projection argument expects a character string or numeric defining the coordinate reference system to be passed to sf::st_crs. For example, for UTM zone 36S (EPSG 32736), the projection argument is projection = "EPSG:32736" or projection = 32736. See https://spatialreference.org for a list of EPSG codes.

The hrType must be either one of "kernel" or "mcp". The hrParams must be a named list of arguments matching those of adehabitatHR::kernelUD() or adehabitatHR::mcp().

The splitBy argument offers further control over grouping. If within your DT, you have multiple populations, subgroups or other distinct parts, you can provide the name of the column which identifies them to splitBy. The grouping performed by group_polys will only consider rows within each splitBy subgroup.

Value

When area is FALSE, group_polys returns the input DT appended with a group column. As with the other grouping functions, the actual value of group is arbitrary and represents the identity of a given group where 1 or more individuals are assigned to a group. If the data was reordered, the group may change, but the contents of each group would not. When area is TRUE, group_polys returns a proportional area overlap data.table. In this case, ID refers to the focal individual of which the total area is compared against the overlapping area of ID2.

If area is FALSE, a message is returned when a column named group already exists in the input DT, because it will be overwritten.

Along with changes to follow the R-spatial evolution, group_polys also now returns area and proportion of overlap with units explicitly specified through the units package.

See Also

build_polys() group_times()

Other Spatial grouping: group_lines(), group_pts()

Examples

# Load data.table
library(data.table)


# Read example data
DT <- fread(system.file("extdata", "DT.csv", package = "spatsoc"))

# Cast the character column to POSIXct
DT[, datetime := as.POSIXct(datetime, tz = 'UTC')]

# EPSG code for example data
utm <- 32736

group_polys(DT, area = FALSE, hrType = 'mcp',
            hrParams = list(percent = 95), projection = utm,
            id = 'ID', coords = c('X', 'Y'))

areaDT <- group_polys(DT, area = TRUE, hrType = 'mcp',
                      hrParams = list(percent = 95), projection = utm,
                      id = 'ID', coords = c('X', 'Y'))
print(areaDT)