Built in plotting function to check automated territory class assignment.

Function plots the automatically generated territory classifications with corresponding ID numbers take note of the numbers which have been missclassified and correct them using beavertools::user_classify()

Usage

check_auto_terr(
  terr_poly,
  fill_col = c("#7EAAC7", "#F87223", "#61E265"),
  label = TRUE,
  basemap = FALSE,
  basemap_type = "osmgrayscale",
  axes_units = TRUE,
  scalebar = TRUE,
  scalebar_loc = "tl",
  north_arrow = TRUE,
  north_arrow_loc = "br",
  north_arrow_size = 0.75,
  wgs = TRUE,
  guide = TRUE,
  plot_extent
)

Arguments

terr_poly: a territory polygon created using beavertools::estimate_territories()
fill_col: character vector of R colours or HEX codes.
label: label activity areas with polygon ID. important when checking the predicted classification
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
plot_extent: 'bbox', 'sf' or 'sp' object defining the desired plot extent.

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')
#> The legacy packages maptools, rgdal, and rgeos, underpinning the sp package,
#> which was just loaded, will retire in October 2023.
#> Please refer to R-spatial evolution reports for details, especially
#> https://r-spatial.org/r/2023/05/15/evolution4.html.
#> It may be desirable to make the sf package available;
#> package maintainers should consider adding sf to Suggests:.
#> The sp package is now running under evolution status 2
#>      (status 2 uses the sf package in place of rgdal)
#> No value supplied for "kd_extent" argument: default extent will be used
#> Error in spatialEco::sp.kde(forage_points, y = forage_points$weights,     bw = kern_bw, nr = dims$nrows[1], nc = dims$ncols[1], newdata = kd_extent,     standardize = standardise): unused arguments (nr = dims$nrows[1], nc = dims$ncols[1], newdata = kd_extent)

# 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)
#> Error in purrr::map(., ~raster::quantile(forage_raster, .)): ℹ In index: 1.
#> Caused by error in `h()`:
#> ! error in evaluating the argument 'x' in selecting a method for function 'quantile': object 'ROBT_201920' not found

# create the map for checking automated territory classification
check_auto_terr(otter_poly, basemap=FALSE, label=TRUE)
#> Error in eval(expr, envir, enclos): object 'otter_poly' not found