Description Usage Arguments Details Value Author(s) Examples
View source: R/res_local_map.R
Create a stylized reserve-level map for use with the reserve level reporting template
1 2 3 4 5 6 7 8 9 10 11 | res_local_map(
nerr_site_id,
stations,
bbox,
shp,
station_labs = TRUE,
lab_loc = NULL,
bg_map = NULL,
zoom = NULL,
maptype = "toner-lite"
)
|
nerr_site_id |
chr string of the reserve to make, first three characters used by NERRS |
stations |
chr string of the reserve stations to include in the map |
bbox |
a bounding box associated with the reserve. Must be in the format of c(X1, Y1, X2, Y2) |
shp |
sf data frame (preferred) or SpatialPolygons object |
station_labs |
logical, should stations be labeled? Defaults to
|
lab_loc |
chr vector of 'R' and 'L', one letter for each station. if no
|
bg_map |
a georeferenced |
zoom |
Zoom level for the base map created when |
maptype |
Background map type from Stamen Maps (http://maps.stamen.com/); one of c("terrain", "terrain-background", "terrain-labels", "terrain-lines", "toner", "toner-2010", "toner-2011", "toner-background", "toner-hybrid", "toner-labels", "toner-lines", "toner-lite", "watercolor"). |
Creates a stylized, reserve-level base map. The user can specify the reserve and stations to plot. The user can also specify a bounding box. For multi-component reserves, the user should specify a bounding box that highlights the component of interest.
This function does not automatically detect conflicts between station
labels. The lab_loc
argument allows the user to specify "R" or "L"
for each station to prevent labels from conflicting with each other.
This function is intended to be used with mapview::mapshot
to
generate a png for the reserve-level report.
returns a ggplot object
Julie Padilla, Dave Eslinger
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | ## a compact reserve
### set plotting parameters
stations <-
sampling_stations[(sampling_stations$NERR.Site.ID == 'elk'
& sampling_stations$Status == 'Active'
& sampling_stations$isSWMP == "P"), ]$Station.Code
to_match <- c('wq', 'met')
stns <- stations[grep(paste(to_match, collapse = '|'), stations)]
shp_fl <- elk_spatial
bounding_elk <- c(-121.8005, 36.7779, -121.6966, 36.8799)
lab_dir <- c('L', 'R', 'L', 'L', 'L')
labs <- c('ap', 'cw', 'nm', 'sm', 'vm')
### Low zoom and default maptype plot (for CRAN testing, not recommended)
# Lower zoom number gives coarser text and fewer features
(x_low <- res_local_map('elk', stations = stns, bbox = bounding_elk,
lab_loc = lab_dir, shp = shp_fl,
zoom = 10))
### Default zoom and maptype
x_def <- res_local_map('elk', stations = stns, bbox = bounding_elk,
lab_loc = lab_dir, shp = shp_fl,
zoom = 10)
### A multicomponent reserve (show two different bounding boxes)
# set plotting parameters
stations <- sampling_stations[(sampling_stations$NERR.Site.ID == 'cbm'
& sampling_stations$Status == 'Active'
& sampling_stations$isSWMP == "P"), ]$Station.Code
to_match <- c('wq', 'met')
stns <- stations[grep(paste(to_match, collapse = '|'), stations)]
shp_fl <- cbm_spatial
bounding_cbm_1 <- c(-77.393, 38.277, -75.553, 39.741)
bounding_cbm_2 <- c(-76.8, 38.7, -76.62, 38.85)
lab_dir <- c('L', 'R', 'L', 'L', 'L')
labs <- c('ap', 'cw', 'nm', 'sm', 'vm')
### plot
y <- res_local_map('cbm', stations = stns, bbox = bounding_cbm_1,
lab_loc = lab_dir, shp = shp_fl)
z <- res_local_map('cbm', stations = stns, bbox = bounding_cbm_2,
lab_loc = lab_dir, shp = shp_fl)
|
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