check_auto_terr: Built in plotting function to check automated territory class...

In h-a-graham/beavertools: Tools to monitor the expansion of beaver populations and predict future territory capacity.

Built in plotting function to check automated territory class assignment.

Description

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')

# 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)

# create the map for checking automated territory classification
check_auto_terr(otter_poly, basemap=FALSE, label=TRUE)

h-a-graham/beavertools documentation built on July 21, 2023, 12:47 a.m.