Built in plotting function for territory polygons. — plot

function to create a ggplot for the territory zones.

Usage

plot_territories(
  terr_poly,
  fill_name,
  fill_col = c("#7EAAC7", "#F87223", "#61E265"),
  label = FALSE,
  basemap = TRUE,
  basemap_type = "cartolight",
  axes_units = TRUE,
  scalebar = TRUE,
  scalebar_loc = "tl",
  north_arrow = TRUE,
  north_arrow_loc = "br",
  north_arrow_size = 0.75,
  wgs = TRUE,
  guide = TRUE,
  guide_pos = "right",
  seed = NA,
  drop_act = FALSE,
  trans_type = NULL,
  catchment = NULL,
  rivers = FALSE,
  plot_extent = NULL,
  mask_fill = "grey50"
)

Arguments

terr_poly: a territory polygon created using beavertools::estimate_territories()
fill_name: a character vector containing the name of the column to be used as the fill aesthetic. choose from: 'terr_status', 'user_class', 'mean_fd', sum_fd' or 'id'.
fill_col: character vector of R colours or HEX codes.
label: label activity areas with polygon ID.
basemap: Boolean, include an OSM basemap. (optional)
basemap_type: Character vector for osm map type. for options see rosm::osm.types()
axes_units: Boolean to include coordinate values on axis.
scalebar: Boolean to include a scalebar.
scalebar_loc: character vector for the scalebar location one of:'tl', 'bl', 'tr', 'br' Meaning "top left" etc.
north_arrow: Boolean to include a north arrow
north_arrow_loc: character vector for the arrow location one of:'tl', 'bl', 'tr', 'br' Meaning "top left" etc.
north_arrow_size: numeric vector for the arrow
wgs: Boolean to transform coordinate reference system (CRS) to WGS84 (EPSG:4326)
guide: Boolean to include a legend
guide_pos: character denoting the position of the legend c('left, 'right, 'bottom', 'top)
seed: numeric seed number -useful if using 'fill_name' = 'ID' as will set the same random colour palette.
drop_act: Boolean to remove areas classified as 'activity' this creates a plot which shows only possibl and confirmed territories
trans_type: character - the transformation type to be used if fill_name=c('mean_fd', sum_fd').
catchment: An sf object or an sf-readable file. See sf::st_drivers() for available drivers. This feature should be a boundary such as a catchment or Area of interest. It is used to mask the map region outside of desired AOI.
rivers: Boolean to include river lines (downloaded automatcally using the osmdata package) OR a river network of class 'sf' which can be generated beforehand using beavertools::get_rivers().
plot_extent: 'bbox', 'sf' or 'sp' object defining the desired plot extent.
mask_fill: character vector for the fill colour of the catchment mask.

Value

ggplot object of the territory check map.

Examples

# Here we filter the filter the built in 2019-2020 ROBT feeding sign data `RivOtter_FeedSigns`
# Then pipe this 'sf' object to forage_density.

ROBT_201920 <- RivOtter_FeedSigns %>%
dplyr::filter(SurveySeason == "2019 - 2020")%>%
  forage_density(., 'FeedCat')
#> No value supplied for "kd_extent" argument: default extent will be used
#> 
#> calculating weighted kde

# Now we load the ROBT `RivOtter_OtherSigns` dataset and filter to the same
# year as the forage density raster.

CS_201920 <- RivOtter_OtherSigns %>%
dplyr::filter(SurveySeason == "2019 - 2020")

# run territory classification
otter_poly <- estimate_territories(ROBT_201920, confirm_signs = CS_201920)

# various options:
plot_territories(otter_poly, 'mean_fd', basemap=FALSE)

plot_territories(otter_poly, 'sum_fd', basemap=FALSE, trans_type = 'log10')

plot_territories(otter_poly, 'id', basemap=TRUE, guide = FALSE, label = TRUE,
                drop_act = TRUE, axes_units = FALSE, rivers = TRUE)
#> "rivers" argument ignored. A valid "catchment" area is required.
#> Zoom: 11